1304  
1304 Program Highlights »
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Tutorial
Mon Dec 3rd 08:30 -- 10:30 AM @ Room 517 CD
Scalable Bayesian Inference
David Dunson
Tutorial
Mon Dec 3rd 08:30 -- 10:30 AM @ Room 220 E
Visualization for Machine Learning
Fernanda Viégas · Martin Wattenberg
Tutorial
Mon Dec 3rd 08:30 -- 10:30 AM @ Room 220 CD
Adversarial Robustness: Theory and Practice
J. Zico Kolter · Aleksander Madry
Break
Mon Dec 3rd 10:30 -- 11:00 AM @
Coffee Break
Tutorial
Mon Dec 3rd 11:00 AM -- 01:00 PM @ Room 220 CD
Unsupervised Deep Learning
Alex Graves · Marc'Aurelio Ranzato
Tutorial
Mon Dec 3rd 11:00 AM -- 01:00 PM @ Room 220 E
Common Pitfalls for Studying the Human Side of Machine Learning
Deirdre Mulligan · Nitin Kohli · Joshua A. Kroll
Tutorial
Mon Dec 3rd 11:00 AM -- 01:00 PM @ Rooms 517 CD
Negative Dependence, Stable Polynomials, and All That
Suvrit Sra · Stefanie Jegelka
Tutorial
Mon Dec 3rd 02:30 -- 04:30 PM @ Room 220 CD
Automatic Machine Learning
Frank Hutter · Joaquin Vanschoren
Tutorial
Mon Dec 3rd 02:30 -- 04:30 PM @ Room 517 CD
Counterfactual Inference
Susan Athey
Tutorial
Mon Dec 3rd 02:30 -- 04:30 PM @ Room 220 E
Statistical Learning Theory: a Hitchhiker's Guide
John Shawe-Taylor · Omar Rivasplata
Break
Mon Dec 3rd 04:30 -- 05:00 PM @
Coffee Break
Break
Mon Dec 3rd 05:00 -- 05:30 PM @
Opening Remarks
Invited Talk
Mon Dec 3rd 05:30 -- 06:20 PM @
The Necessity of Diversity and Inclusivity in Tech
Laura Gomez
Break
Mon Dec 3rd 06:30 -- 08:30 PM @
Opening Reception
Invited Talk
Tue Dec 4th 08:30 -- 09:20 AM @ Rooms 220 CDE
Machine Learning Meets Public Policy: What to Expect and How to Cope
Edward W Felten
Talk
Tue Dec 4th 09:20 -- 09:40 AM @
Test of Time Award
Break
Tue Dec 4th 09:40 -- 10:05 AM @
Coffee Break
Oral
Tue Dec 4th 10:05 -- 10:20 AM @ Room 220 CD
On Neuronal Capacity
Pierre Baldi · Roman Vershynin
Oral
Tue Dec 4th 10:05 -- 10:20 AM @ Room 220 E
On the Dimensionality of Word Embedding
Zi Yin · Yuanyuan Shen
Oral
Tue Dec 4th 10:05 -- 10:20 AM @ Room 517 CD
Phase Retrieval Under a Generative Prior
Paul Hand · Oscar Leong · Vlad Voroninski
Spotlight
Tue Dec 4th 10:20 -- 10:25 AM @ Room 220 CD
Learning Overparameterized Neural Networks via Stochastic Gradient Descent on Structured Data
Yuanzhi Li · Yingyu Liang
Spotlight
Tue Dec 4th 10:20 -- 10:25 AM @ Room 220 E
Unsupervised Cross-Modal Alignment of Speech and Text Embedding Spaces
Yu-An Chung · Wei-Hung Weng · Schrasing Tong · James Glass
Spotlight
Tue Dec 4th 10:20 -- 10:25 AM @ Room 517 CD
Global Geometry of Multichannel Sparse Blind Deconvolution on the Sphere
Yanjun Li · Yoram Bresler
Spotlight
Tue Dec 4th 10:25 -- 10:30 AM @ Room 220 CD
Size-Noise Tradeoffs in Generative Networks
Bolton Bailey · Matus Telgarsky
Spotlight
Tue Dec 4th 10:25 -- 10:30 AM @ Room 220 E
Diffusion Maps for Textual Network Embedding
Xinyuan Zhang · Yitong Li · Dinghan Shen · Lawrence Carin
Spotlight
Tue Dec 4th 10:25 -- 10:30 AM @ Room 517 CD
Theoretical Linear Convergence of Unfolded ISTA and Its Practical Weights and Thresholds
Xiaohan Chen · Jialin Liu · Zhangyang Wang · Wotao Yin
Oral
Tue Dec 4th 10:30 -- 10:45 AM @ Room 220 CD
Dendritic cortical microcircuits approximate the backpropagation algorithm
João Sacramento · Rui Ponte Costa · Yoshua Bengio · Walter Senn
Oral
Tue Dec 4th 10:30 -- 10:45 AM @ Room 220 E
A Retrieve-and-Edit Framework for Predicting Structured Outputs
Tatsunori Hashimoto · Kelvin Guu · Yonatan Oren · Percy Liang
Oral
Tue Dec 4th 10:30 -- 10:45 AM @ Room 517 CD
Spectral Filtering for General Linear Dynamical Systems
Elad Hazan · HOLDEN LEE · Karan Singh · Cyril Zhang · Yi Zhang
Demonstration
Tue Dec 4th 10:45 AM -- 07:30 PM @ Room 510 ABCD #D10
TextWorld: A Learning Environment for Text-based Games
Marc-Alexandre Côté · Wendy Tay · Eric Yuan
Demonstration
Tue Dec 4th 10:45 AM -- 07:30 PM @ Room 510 ABCD #D5
Deep learning to improve quality control in pharmaceutical manufacturing
Michael Sass Hansen · Sebastian Brandes Kraaijenzank
Demonstration
Tue Dec 4th 10:45 AM -- 07:30 PM @ Room 510 ABCD #D3
Ruuh: A Deep Learning Based Conversational Social Agent
Puneet Agrawal · Manoj Kumar Chinnakotla · Sonam Damani · Meghana Joshi · Kedhar Nath Narahari · Khyatti Gupta · Nitya Raviprakash · Umang Gupta · Ankush Chatterjee · Abhishek Mathur · Sneha Magapu
Demonstration
Tue Dec 4th 10:45 AM -- 07:30 PM @ Room 510
TensorFlow Dance - Learning to Dance via Machine Learning
Yaz Santissi · Jonathan DEKHTIAR
Demonstration
Tue Dec 4th 10:45 AM -- 07:30 PM @ Room 510 ABCD #D7
A Hands-free Natural User Interface (NUI) for AR/VR Head-Mounted Displays Exploiting Wearer’s Facial Gestures
Jaekwang Cha · Shiho Kim · Jinhyuk Kim
Demonstration
Tue Dec 4th 10:45 AM -- 07:30 PM @ Room 510
Reproducing Machine Learning Research on Binder
Jessica Forde · Tim Head · Chris Holdgraf · M Pacer · Félix-Antoine Fortin · Fernando Perez
Demonstration
Tue Dec 4th 10:45 AM -- 07:30 PM @ Room 510 ABCD #D8
A model-agnostic web interface for interactive music composition by inpainting
Gaëtan Hadjeres · Théis Bazin · Ashis Pati
Demonstration
Tue Dec 4th 10:45 AM -- 07:30 PM @ Room 510 ABCD #D1
Deep Neural Networks Running Onboard Anki’s Robot, Vector
Lorenzo Riano · Andrew Stein · Mark Palatucci
Demonstration
Tue Dec 4th 10:45 AM -- 07:30 PM @ Room 510 ABCD #D4
Game for Detecting Backdoor Attacks on Deep Neural Networks using Activation Clustering
Casey Dugan · Werner Geyer · Aabhas Sharma · Ingrid Lange · Dustin Ramsey Torres · Bryant Chen · Nathalie Baracaldo Angel · Heiko Ludwig
Demonstration
Tue Dec 4th 10:45 AM -- 07:30 PM @ Room 510 ABCD #D9
A machine learning environment to determine novel malaria policies
Oliver Bent · Sekou L Remy · Nelson Bore
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #1
Modelling sparsity, heterogeneity, reciprocity and community structure in temporal interaction data
Xenia Miscouridou · Francois Caron · Yee Whye Teh
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #2
The Lingering of Gradients: How to Reuse Gradients Over Time
Zeyuan Allen-Zhu · David Simchi-Levi · Xinshang Wang
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #3
Quadratic Decomposable Submodular Function Minimization
Pan Li · Niao He · Olgica Milenkovic
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #4
On the Global Convergence of Gradient Descent for Over-parameterized Models using Optimal Transport
Lénaïc Chizat · Francis Bach
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #5
Leveraging the Exact Likelihood of Deep Latent Variable Models
Pierre-Alexandre Mattei · Jes Frellsen
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #6
DVAE#: Discrete Variational Autoencoders with Relaxed Boltzmann Priors
Arash Vahdat · Evgeny Andriyash · William Macready
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #7
Amortized Inference Regularization
Rui Shu · Hung Bui · Shengjia Zhao · Mykel J Kochenderfer · Stefano Ermon
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #8
GumBolt: Extending Gumbel trick to Boltzmann priors
Amir H Khoshaman · Mohammad Amin
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #9
Constrained Generation of Semantically Valid Graphs via Regularizing Variational Autoencoders
Tengfei Ma · Jie Chen · Cao Xiao
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #10
Invertibility of Convolutional Generative Networks from Partial Measurements
Fangchang Ma · Ulas Ayaz · Sertac Karaman
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #11
Glow: Generative Flow with Invertible 1x1 Convolutions
Durk Kingma · Prafulla Dhariwal
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #12
Multimodal Generative Models for Scalable Weakly-Supervised Learning
Mike Wu · Noah Goodman
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #13
IntroVAE: Introspective Variational Autoencoders for Photographic Image Synthesis
Huaibo Huang · zhihang li · Ran He · Zhenan Sun · Tieniu Tan
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #14
Towards Text Generation with Adversarially Learned Neural Outlines
Sandeep Subramanian · Sai Rajeswar Mudumba · Alessandro Sordoni · Adam Trischler · Aaron Courville · Chris Pal
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #15
Unsupervised Image-to-Image Translation Using Domain-Specific Variational Information Bound
Hadi Kazemi · Sobhan Soleymani · Fariborz Taherkhani · Seyed Iranmanesh · Nasser Nasrabadi
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #16
Adversarial Scene Editing: Automatic Object Removal from Weak Supervision
Rakshith R Shetty · Mario Fritz · Bernt Schiele
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #17
Generalizing Point Embeddings using the Wasserstein Space of Elliptical Distributions
Boris Muzellec · Marco Cuturi
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #18
Banach Wasserstein GAN
Jonas Adler · Sebastian Lunz
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #19
A Convex Duality Framework for GANs
Farzan Farnia · David Tse
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #20
On the Convergence and Robustness of Training GANs with Regularized Optimal Transport
Maziar Sanjabi · Jimmy Ba · Meisam Razaviyayn · Jason Lee
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #21
On gradient regularizers for MMD GANs
Michael Arbel · Dougal Sutherland · Mikołaj Bińkowski · Arthur Gretton
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #22
PacGAN: The power of two samples in generative adversarial networks
Zinan Lin · Ashish Khetan · Giulia Fanti · Sewoong Oh
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #23
Are GANs Created Equal? A Large-Scale Study
Mario Lucic · Karol Kurach · Marcin Michalski · Sylvain Gelly · Olivier Bousquet
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #24
Disconnected Manifold Learning for Generative Adversarial Networks
Mahyar Khayatkhoei · Maneesh K. Singh · Ahmed Elgammal
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #25
Hessian-based Analysis of Large Batch Training and Robustness to Adversaries
Zhewei Yao · Amir Gholami · Qi Lei · Kurt Keutzer · Michael W Mahoney
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #26
Fast and Effective Robustness Certification
Gagandeep Singh · Timon Gehr · Matthew Mirman · Markus Püschel · Martin Vechev
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #27
Graphical Generative Adversarial Networks
Chongxuan LI · Max Welling · Jun Zhu · Bo Zhang
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #28
Deep Defense: Training DNNs with Improved Adversarial Robustness
Ziang Yan · Yiwen Guo · Changshui Zhang
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #29
Learning to Repair Software Vulnerabilities with Generative Adversarial Networks
Jacob Harer · Onur Ozdemir · Tomo Lazovich · Christopher Reale · Rebecca Russell · Louis Kim · peter chin
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #30
Memory Replay GANs: Learning to Generate New Categories without Forgetting
Chenshen Wu · Luis Herranz · Xialei Liu · yaxing wang · Joost van de Weijer · Bogdan Raducanu
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #31
Unsupervised Attention-guided Image-to-Image Translation
Youssef Alami Mejjati · Christian Richardt · James Tompkin · Darren Cosker · Kwang In Kim
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #32
Conditional Adversarial Domain Adaptation
Mingsheng Long · ZHANGJIE CAO · Jianmin Wang · Michael Jordan
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #33
Video-to-Video Synthesis
Ting-Chun Wang · Ming-Yu Liu · Jun-Yan Zhu · Nikolai Yakovenko · Andrew Tao · Jan Kautz · Bryan Catanzaro
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #34
Generalized Zero-Shot Learning with Deep Calibration Network
Shichen Liu · Mingsheng Long · Jianmin Wang · Michael Jordan
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #35
Low-shot Learning via Covariance-Preserving Adversarial Augmentation Networks
Hang Gao · Zheng Shou · Alireza Zareian · Hanwang Zhang · Shih-Fu Chang
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #36
Trading robust representations for sample complexity through self-supervised visual experience
Andrea Tacchetti · Stephen Voinea · Georgios Evangelopoulos
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #37
TADAM: Task dependent adaptive metric for improved few-shot learning
Boris Oreshkin · Pau Rodríguez López · Alexandre Lacoste
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #38
FishNet: A Versatile Backbone for Image, Region, and Pixel Level Prediction
Shuyang Sun · Jiangmiao Pang · Jianping Shi · Shuai Yi · Wanli Ouyang
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #39
Batch-Instance Normalization for Adaptively Style-Invariant Neural Networks
Hyeonseob Nam · Hyo-Eun Kim
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #40
A^2-Nets: Double Attention Networks
Yunpeng Chen · Yannis Kalantidis · Jianshu Li · Shuicheng Yan · Jiashi Feng
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #41
Pelee: A Real-Time Object Detection System on Mobile Devices
Jun Wang · Tanner Bohn · Charles Ling
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #42
PointCNN: Convolution On X-Transformed Points
Yangyan Li · Rui Bu · Mingchao Sun · Wei Wu · Xinhan Di · Baoquan Chen
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #43
Deep Neural Networks with Box Convolutions
Egor Burkov · Victor Lempitsky
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #44
An intriguing failing of convolutional neural networks and the CoordConv solution
Rosanne Liu · Joel Lehman · Piero Molino · Felipe Petroski Such · Eric Frank · Alex Sergeev · Jason Yosinski
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #45
3D Steerable CNNs: Learning Rotationally Equivariant Features in Volumetric Data
Maurice Weiler · Wouter Boomsma · Mario Geiger · Max Welling · Taco Cohen
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #46
Moonshine: Distilling with Cheap Convolutions
Elliot J. Crowley · Gavin Gray · Amos Storkey
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #47
Kalman Normalization: Normalizing Internal Representations Across Network Layers
Guangrun Wang · jiefeng peng · Ping Luo · Xinjiang Wang · Liang Lin
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #48
SplineNets: Continuous Neural Decision Graphs
Cem Keskin · Shahram Izadi
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #49
CapProNet: Deep Feature Learning via Orthogonal Projections onto Capsule Subspaces
Liheng Zhang · Marzieh Edraki · Guo-Jun Qi
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #50
Which Neural Net Architectures Give Rise to Exploding and Vanishing Gradients?
Boris Hanin
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #51
Exact natural gradient in deep linear networks and its application to the nonlinear case
Alberto Bernacchia · Mate Lengyel · Guillaume Hennequin
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #52
Fast Approximate Natural Gradient Descent in a Kronecker Factored Eigenbasis
Thomas George · César Laurent · Xavier Bouthillier · Nicolas Ballas · Pascal Vincent
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #53
Post: Device Placement with Cross-Entropy Minimization and Proximal Policy Optimization
Yuanxiang Gao · Li Chen · Baochun Li
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #54
Paraphrasing Complex Network: Network Compression via Factor Transfer
Jangho Kim · Seonguk Park · Nojun Kwak
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #55
Learning Compressed Transforms with Low Displacement Rank
Anna Thomas · Albert Gu · Tri Dao · Atri Rudra · Christopher Ré
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #56
Knowledge Distillation by On-the-Fly Native Ensemble
xu lan · Xiatian Zhu · Shaogang Gong
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #57
Scalable methods for 8-bit training of neural networks
Ron Banner · Itay Hubara · Elad Hoffer · Daniel Soudry
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #58
Training Deep Models Faster with Robust, Approximate Importance Sampling
Tyler Johnson · Carlos Guestrin
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #59
Collaborative Learning for Deep Neural Networks
Guocong Song · Wei Chai
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #60
A Linear Speedup Analysis of Distributed Deep Learning with Sparse and Quantized Communication
Peng Jiang · Gagan Agrawal
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #61
Bayesian Distributed Stochastic Gradient Descent
Michael Teng · Frank Wood
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #62
Regularizing by the Variance of the Activations' Sample-Variances
Etai Littwin · Lior Wolf
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #63
BML: A High-performance, Low-cost Gradient Synchronization Algorithm for DML Training
Songtao Wang · Dan Li · Yang Cheng · Jinkun Geng · Yanshu Wang · Shuai Wang · Shu-Tao Xia · Jianping Wu
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #64
L4: Practical loss-based stepsize adaptation for deep learning
Michal Rolinek · Georg Martius
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #65
Synaptic Strength For Convolutional Neural Network
CHEN LIN · Zhao Zhong · Wu Wei · Junjie Yan
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #66
ChannelNets: Compact and Efficient Convolutional Neural Networks via Channel-Wise Convolutions
Hongyang Gao · Zhengyang Wang · Shuiwang Ji
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #67
Frequency-Domain Dynamic Pruning for Convolutional Neural Networks
Zhenhua Liu · Jizheng Xu · Xiulian Peng · Ruiqin Xiong
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #68
TETRIS: TilE-matching the TRemendous Irregular Sparsity
Yu Ji · Ling Liang · Lei Deng · Youyang Zhang · Youhui Zhang · Yuan Xie
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #69
Heterogeneous Bitwidth Binarization in Convolutional Neural Networks
Joshua Fromm · Shwetak Patel · Matthai Philipose
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #70
HitNet: Hybrid Ternary Recurrent Neural Network
Peiqi Wang · Xinfeng Xie · Lei Deng · Guoqi Li · Dongsheng Wang · Yuan Xie
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #71
A General Method for Amortizing Variational Filtering
Joseph Marino · Milan Cvitkovic · Yisong Yue
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #72
Multiple Instance Learning for Efficient Sequential Data Classification on Resource-constrained Devices
Don Dennis · Chirag Pabbaraju · Harsha Vardhan Simhadri · Prateek Jain
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #73
Navigating with Graph Representations for Fast and Scalable Decoding of Neural Language Models
Minjia Zhang · Wenhan Wang · Xiaodong Liu · Jianfeng Gao · Yuxiong He
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #74
Representer Point Selection for Explaining Deep Neural Networks
Chih-Kuan Yeh · Joon Kim · Ian En-Hsu Yen · Pradeep Ravikumar
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #75
Interpreting Neural Network Judgments via Minimal, Stable, and Symbolic Corrections
Xin Zhang · Armando Solar-Lezama · Rishabh Singh
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #76
DropMax: Adaptive Variational Softmax
Hae Beom Lee · Juho Lee · Saehoon Kim · Eunho Yang · Sung Ju Hwang
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #77
Out-of-Distribution Detection using Multiple Semantic Label Representations
Gabi Shalev · Yossi Adi · Joseph Keshet
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #78
End-to-end Symmetry Preserving Inter-atomic Potential Energy Model for Finite and Extended Systems
Linfeng Zhang · Jiequn Han · Han Wang · Wissam Saidi · Roberto Car · Weinan E
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #79
Deep Predictive Coding Network with Local Recurrent Processing for Object Recognition
Kuan Han · Haiguang Wen · Yizhen Zhang · Di Fu · Eugenio Culurciello · Zhongming Liu
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #80
SLAYER: Spike Layer Error Reassignment in Time
Sumit Bam Shrestha · Garrick Orchard
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #81
DeepPINK: reproducible feature selection in deep neural networks
Yang Lu · Yingying Fan · Jinchi Lv · William Stafford Noble
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #82
Learning long-range spatial dependencies with horizontal gated recurrent units
Drew Linsley · Junkyung Kim · Vijay Veerabadran · Charles Windolf · Thomas Serre
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #83
Neural Interaction Transparency (NIT): Disentangling Learned Interactions for Improved Interpretability
Michael Tsang · Hanpeng Liu · Sanjay Purushotham · Pavankumar Murali · Yan Liu
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #84
A Bridging Framework for Model Optimization and Deep Propagation
Risheng Liu · Shichao Cheng · xiaokun liu · Long Ma · Xin Fan · Zhongxuan Luo
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #85
The Importance of Sampling inMeta-Reinforcement Learning
Bradly Stadie · Ge Yang · Rein Houthooft · Peter Chen · Yan Duan · Yuhuai Wu · Pieter Abbeel · Ilya Sutskever
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #86
Latent Alignment and Variational Attention
Yuntian Deng · Yoon Kim · Justin Chiu · Demi Guo · Alexander Rush
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #87
Variational Memory Encoder-Decoder
Hung Le · Truyen Tran · Thin Nguyen · Svetha Venkatesh
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #88
Relational recurrent neural networks
Adam Santoro · Ryan Faulkner · David Raposo · Jack Rae · Mike Chrzanowski · Theophane Weber · Daan Wierstra · Oriol Vinyals · Razvan Pascanu · Timothy Lillicrap
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #89
Learning to Reason with Third Order Tensor Products
Imanol Schlag · Jürgen Schmidhuber
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #90
Reversible Recurrent Neural Networks
Matthew MacKay · Paul Vicol · Jimmy Ba · Roger Grosse
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #91
Breaking the Activation Function Bottleneck through Adaptive Parameterization
Sebastian Flennerhag · Hujun Yin · John Keane · Mark Elliot
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #92
BRITS: Bidirectional Recurrent Imputation for Time Series
Wei Cao · Dong Wang · Jian Li · Hao Zhou · Lei Li · Yitan Li
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #93
Complex Gated Recurrent Neural Networks
Moritz Wolter · Angela Yao
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #94
Middle-Out Decoding
Shikib Mehri · Leonid Sigal
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #95
Recurrently Controlled Recurrent Networks
Yi Tay · Anh Tuan Luu · Siu Cheung Hui
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #96
Tree-to-tree Neural Networks for Program Translation
Xinyun Chen · Chang Liu · Dawn Song
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #97
HOUDINI: Lifelong Learning as Program Synthesis
Lazar Valkov · Dipak Chaudhari · Akash Srivastava · Charles Sutton · Swarat Chaudhuri
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #98
Neural Guided Constraint Logic Programming for Program Synthesis
Lisa Zhang · Gregory Rosenblatt · Ethan Fetaya · Renjie Liao · William Byrd · Matthew Might · Raquel Urtasun · Richard Zemel
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #99
Embedding Logical Queries on Knowledge Graphs
Will Hamilton · Payal Bajaj · Marinka Zitnik · Dan Jurafsky · Jure Leskovec
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #100
Expanding Holographic Embeddings for Knowledge Completion
Yexiang Xue · Yang Yuan · Zhitian Xu · Ashish Sabharwal
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #101
On the Dimensionality of Word Embedding
Zi Yin · Yuanyuan Shen
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #102
Flexible neural representation for physics prediction
Damian Mrowca · Chengxu Zhuang · Elias Wang · Nick Haber · Li Fei-Fei · Josh Tenenbaum · Daniel Yamins
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #103
Content preserving text generation with attribute controls
Lajanugen Logeswaran · Honglak Lee · Samy Bengio
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #104
Recurrent Relational Networks
Rasmus Palm · Ulrich Paquet · Ole Winther
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #105
GLoMo: Unsupervised Learning of Transferable Relational Graphs
Zhilin Yang · Jake Zhao · Bhuwan Dhingra · Kaiming He · William Cohen · Ruslan Salakhutdinov · Yann LeCun
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #106
Predictive Uncertainty Estimation via Prior Networks
Andrey Malinin · Mark Gales
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #107
Adversarial Multiple Source Domain Adaptation
Han Zhao · Shanghang Zhang · Guanhang Wu · José M. F. Moura · Joao P Costeira · Geoffrey Gordon
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #108
Adversarial Examples that Fool both Computer Vision and Time-Limited Humans
Gamaleldin Elsayed · Shreya Shankar · Brian Cheung · Nicolas Papernot · Alexey Kurakin · Ian Goodfellow · Jascha Sohl-Dickstein
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #109
A Simple Cache Model for Image Recognition
Emin Orhan
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #110
Co-teaching: Robust training of deep neural networks with extremely noisy labels
Bo Han · Quanming Yao · Xingrui Yu · Gang Niu · Miao Xu · Weihua Hu · Ivor Tsang · Masashi Sugiyama
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #111
Improved Network Robustness with Adversary Critic
Alexander Matyasko · Lap-Pui Chau
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #112
Unsupervised Learning of Object Landmarks through Conditional Image Generation
Tomas Jakab · Ankush Gupta · Hakan Bilen · Andrea Vedaldi
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #113
Multi-Task Learning as Multi-Objective Optimization
Ozan Sener · Vladlen Koltun
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #114
Deep Anomaly Detection Using Geometric Transformations
Izhak Golan · Ran El-Yaniv
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #115
Practical Deep Stereo (PDS): Toward applications-friendly deep stereo matching
Stepan Tulyakov · Anton Ivanov · François Fleuret
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #116
VideoCapsuleNet: A Simplified Network for Action Detection
Kevin Duarte · Yogesh Rawat · Mubarak Shah
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #117
With Friends Like These, Who Needs Adversaries?
Saumya Jetley · Nicholas Lord · Philip Torr
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #118
Multi-Task Zipping via Layer-wise Neuron Sharing
Xiaoxi He · Zimu Zhou · Lothar Thiele
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #119
Learning Versatile Filters for Efficient Convolutional Neural Networks
Yunhe Wang · Chang Xu · Chunjing XU · Chao Xu · Dacheng Tao
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #120
Evolutionary Stochastic Gradient Descent for Optimization of Deep Neural Networks
Xiaodong Cui · Wei Zhang · Zoltán Tüske · Michael Picheny
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #121
Structure-Aware Convolutional Neural Networks
Jianlong Chang · Jie Gu · Lingfeng Wang · GAOFENG MENG · SHIMING XIANG · Chunhong Pan
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #122
Global Gated Mixture of Second-order Pooling for Improving Deep Convolutional Neural Networks
Qilong Wang · Zilin Gao · Jiangtao Xie · Wangmeng Zuo · Peihua Li
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #123
Hybrid Macro/Micro Level Backpropagation for Training Deep Spiking Neural Networks
Yingyezhe Jin · Wenrui Zhang · Peng Li
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #124
Deep Neural Nets with Interpolating Function as Output Activation
Bao Wang · Xiyang Luo · Zhen Li · Wei Zhu · Zuoqiang Shi · Stanley Osher
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #125
Neural Edit Operations for Biological Sequences
Satoshi Koide · Keisuke Kawano · Takuro Kutsuna
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #126
Improved Expressivity Through Dendritic Neural Networks
Xundong Wu · Xiangwen Liu · wei li · qing wu
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #127
Neural Proximal Gradient Descent for Compressive Imaging
Morteza Mardani · Qingyun Sun · David Donoho · Vardan Papyan · Hatef Monajemi · Shreyas Vasanawala · John Pauly
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #128
Sigsoftmax: Reanalysis of the Softmax Bottleneck
Sekitoshi Kanai · Yasuhiro Fujiwara · Yuki Yamanaka · Shuichi Adachi
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #129
Visualizing the Loss Landscape of Neural Nets
Hao Li · Zheng Xu · Gavin Taylor · Christoph Studer · Tom Goldstein
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #130
Clebsch–Gordan Nets: a Fully Fourier Space Spherical Convolutional Neural Network
Risi Kondor · Zhen Lin · Shubhendu Trivedi
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #131
Adaptive Sampling Towards Fast Graph Representation Learning
Wenbing Huang · Tong Zhang · Yu Rong · Junzhou Huang
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #132
NAIS-Net: Stable Deep Networks from Non-Autonomous Differential Equations
Marco Ciccone · Marco Gallieri · Jonathan Masci · Christian Osendorfer · Faustino Gomez
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #133
Scaling provable adversarial defenses
Eric Wong · Frank Schmidt · Jan Hendrik Metzen · J. Zico Kolter
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #134
Lipschitz regularity of deep neural networks: analysis and efficient estimation
Aladin Virmaux · Kevin Scaman
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #135
Training DNNs with Hybrid Block Floating Point
Mario Drumond · Tao LIN · Martin Jaggi · Babak Falsafi
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #136
Mesh-TensorFlow: Deep Learning for Supercomputers
Noam Shazeer · Youlong Cheng · Niki Parmar · Dustin Tran · Ashish Vaswani · Penporn Koanantakool · Peter Hawkins · HyoukJoong Lee · Mingsheng Hong · Cliff Young · Ryan Sepassi · Blake Hechtman
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #137
Thwarting Adversarial Examples: An $L_0$-Robust Sparse Fourier Transform
Mitali Bafna · Jack Murtagh · Nikhil Vyas
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #138
Bayesian Adversarial Learning
Nanyang Ye · Zhanxing Zhu
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #139
Dendritic cortical microcircuits approximate the backpropagation algorithm
João Sacramento · Rui Ponte Costa · Yoshua Bengio · Walter Senn
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #140
Learning a latent manifold of odor representations from neural responses in piriform cortex
Anqi Wu · Stan Pashkovski · Sandeep Datta · Jonathan W Pillow
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #141
Size-Noise Tradeoffs in Generative Networks
Bolton Bailey · Matus Telgarsky
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #142
On Neuronal Capacity
Pierre Baldi · Roman Vershynin
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #143
Learning Overparameterized Neural Networks via Stochastic Gradient Descent on Structured Data
Yuanzhi Li · Yingyu Liang
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #144
Deep, complex, invertible networks for inversion of transmission effects in multimode optical fibres
Oisín Moran · Piergiorgio Caramazza · Daniele Faccio · Roderick Murray-Smith
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #145
Learning towards Minimum Hyperspherical Energy
Weiyang Liu · Rongmei Lin · Zhen Liu · Lixin Liu · Zhiding Yu · Bo Dai · Le Song
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #146
Soft-Gated Warping-GAN for Pose-Guided Person Image Synthesis
Haoye Dong · Xiaodan Liang · Ke Gong · Hanjiang Lai · Jia Zhu · Jian Yin
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #147
Deep Attentive Tracking via Reciprocative Learning
Shi Pu · Yibing Song · Chao Ma · Honggang Zhang · Ming-Hsuan Yang
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #148
Robot Learning in Homes: Improving Generalization and Reducing Dataset Bias
Abhinav Gupta · Adithyavairavan Murali · Dhiraj Prakashchand Gandhi · Lerrel Pinto
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #149
A flexible model for training action localization with varying levels of supervision
Guilhem Chéron · Jean-Baptiste Alayrac · Ivan Laptev · Cordelia Schmid
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #150
Bilinear Attention Networks
Jin-Hwa Kim · Jaehyun Jun · Byoung-Tak Zhang
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #151
MacNet: Transferring Knowledge from Machine Comprehension to Sequence-to-Sequence Models
Boyuan Pan · Yazheng Yang · Hao Li · Zhou Zhao · Yueting Zhuang · Deng Cai · Xiaofei He
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #152
Diffusion Maps for Textual Network Embedding
Xinyuan Zhang · Yitong Li · Dinghan Shen · Lawrence Carin
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #153
FRAGE: Frequency-Agnostic Word Representation
Chengyue Gong · Di He · Xu Tan · Tao Qin · Liwei Wang · Tie-Yan Liu
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #154
A Retrieve-and-Edit Framework for Predicting Structured Outputs
Tatsunori Hashimoto · Kelvin Guu · Yonatan Oren · Percy Liang
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #155
Unsupervised Text Style Transfer using Language Models as Discriminators
Zichao Yang · Zhiting Hu · Chris Dyer · Eric Xing · Taylor Berg-Kirkpatrick
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #156
Unsupervised Cross-Modal Alignment of Speech and Text Embedding Spaces
Yu-An Chung · Wei-Hung Weng · Schrasing Tong · James Glass
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #157
GradiVeQ: Vector Quantization for Bandwidth-Efficient Gradient Aggregation in Distributed CNN Training
Mingchao Yu · Zhifeng Lin · Krishna Narra · Songze Li · Youjie Li · Nam Sung Kim · Alexander Schwing · Murali Annavaram · Salman Avestimehr
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #158
Gradient Sparsification for Communication-Efficient Distributed Optimization
Jianqiao Wangni · Jialei Wang · Ji Liu · Tong Zhang
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #159
Bayesian multi-domain learning for cancer subtype discovery from next-generation sequencing count data
Ehsan Hajiramezanali · Siamak Zamani Dadaneh · Alireza Karbalayghareh · Mingyuan Zhou · Xiaoning Qian
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #160
Parsimonious Quantile Regression of Financial Asset Tail Dynamics via Sequential Learning
Xing Yan · Weizhong Zhang · Lin Ma · Wei Liu · Qi Wu
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #161
Global Geometry of Multichannel Sparse Blind Deconvolution on the Sphere
Yanjun Li · Yoram Bresler
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #162
Phase Retrieval Under a Generative Prior
Paul Hand · Oscar Leong · Vlad Voroninski
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #163
Theoretical Linear Convergence of Unfolded ISTA and Its Practical Weights and Thresholds
Xiaohan Chen · Jialin Liu · Zhangyang Wang · Wotao Yin
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #164
Modern Neural Networks Generalize on Small Data Sets
Matthew Olson · Abraham Wyner · Richard Berk
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #165
Co-regularized Alignment for Unsupervised Domain Adaptation
Abhishek Kumar · Prasanna Sattigeri · Kahini Wadhawan · Leonid Karlinsky · Rogerio Feris · Bill Freeman · Gregory Wornell
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #166
Neural Networks Trained to Solve Differential Equations Learn General Representations
Martin Magill · Faisal Qureshi · Hendrick de Haan
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #167
Spectral Filtering for General Linear Dynamical Systems
Elad Hazan · HOLDEN LEE · Karan Singh · Cyril Zhang · Yi Zhang
Poster
Tue Dec 4th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #168
Where Do You Think You're Going?: Inferring Beliefs about Dynamics from Behavior
Sid Reddy · Anca Dragan · Sergey Levine
Break
Tue Dec 4th 12:45 -- 02:15 PM @
Lunch on your own
Break
Tue Dec 4th 12:45 -- 02:15 PM @
Lunch on your own
Break
Tue Dec 4th 01:15 -- 02:15 PM @ Room 517 CD
Town Hall
Invited Talk
Tue Dec 4th 02:15 -- 03:05 PM @ Rooms 220 CDE
What Bodies Think About: Bioelectric Computation Outside the Nervous System, Primitive Cognition, and Synthetic Morphology
Michael Levin
Break
Tue Dec 4th 03:05 -- 03:30 PM @
Coffee Break
Spotlight
Tue Dec 4th 03:30 -- 03:35 PM @ Room 220 CD
Neural Voice Cloning with a Few Samples
Sercan Arik · Jitong Chen · Kainan Peng · Wei Ping · Yanqi Zhou
Spotlight
Tue Dec 4th 03:30 -- 03:35 PM @ Room 220 E
Evolved Policy Gradients
Rein Houthooft · Yuhua Chen · Phillip Isola · Bradly Stadie · Filip Wolski · OpenAI Jonathan Ho · Pieter Abbeel
Spotlight
Tue Dec 4th 03:30 -- 03:35 PM @ Room 517 CD
Differentially Private Testing of Identity and Closeness of Discrete Distributions
Jayadev Acharya · Ziteng Sun · Huanyu Zhang
Spotlight
Tue Dec 4th 03:35 -- 03:40 PM @ Room 220 CD
Answerer in Questioner's Mind: Information Theoretic Approach to Goal-Oriented Visual Dialog
Sang-Woo Lee · Yu-Jung Heo · Byoung-Tak Zhang
Spotlight
Tue Dec 4th 03:35 -- 03:40 PM @ Room 220 E
Adapted Deep Embeddings: A Synthesis of Methods for k-Shot Inductive Transfer Learning
Tyler Scott · Karl Ridgeway · Michael Mozer
Spotlight
Tue Dec 4th 03:35 -- 03:40 PM @ Room 517 CD
Local Differential Privacy for Evolving Data
Matthew Joseph · Aaron Roth · Jonathan Ullman · Bo Waggoner
Spotlight
Tue Dec 4th 03:40 -- 03:45 PM @ Room 220 CD
Neural-Symbolic VQA: Disentangling Reasoning from Vision and Language Understanding
Kexin Yi · Jiajun Wu · Chuang Gan · Antonio Torralba · Pushmeet Kohli · Josh Tenenbaum
Spotlight
Tue Dec 4th 03:40 -- 03:45 PM @ Room 220 E
Bayesian Model-Agnostic Meta-Learning
Jaesik Yoon · Taesup Kim · Ousmane Dia · Sungwoong Kim · Yoshua Bengio · Sungjin Ahn
Spotlight
Tue Dec 4th 03:40 -- 03:45 PM @ Room 517 CD
Differentially Private k-Means with Constant Multiplicative Error
Uri Stemmer · Haim Kaplan
Spotlight
Tue Dec 4th 03:45 -- 03:50 PM @ Room 220 CD
Learning to Optimize Tensor Programs
Tianqi Chen · Lianmin Zheng · Eddie Yan · Ziheng Jiang · Thierry Moreau · Luis Ceze · Carlos Guestrin · Arvind Krishnamurthy
Spotlight
Tue Dec 4th 03:45 -- 03:50 PM @ Room 220 E
Probabilistic Neural Programmed Networks for Scene Generation
Zhiwei Deng · Jiacheng Chen · YIFANG FU · Greg Mori
Spotlight
Tue Dec 4th 03:45 -- 03:50 PM @ Room 517 CD
A Spectral View of Adversarially Robust Features
Shivam Garg · Vatsal Sharan · Brian Zhang · Gregory Valiant
Oral
Tue Dec 4th 03:50 -- 04:05 PM @ Room 220 CD
Generalisation of structural knowledge in the hippocampal-entorhinal system
James Whittington · Timothy Muller · Shirely Mark · Caswell Barry · Tim Behrens
Oral
Tue Dec 4th 03:50 -- 04:05 PM @ Room 220 E
Neural Ordinary Differential Equations
Tian Qi Chen · Yulia Rubanova · Jesse Bettencourt · David Duvenaud
Oral
Tue Dec 4th 03:50 -- 04:05 PM @ Room 517 CD
Model-Agnostic Private Learning
Raef Bassily · Abhradeep Guha Thakurta · Om Dipakbhai Thakkar
Spotlight
Tue Dec 4th 04:05 -- 04:10 PM @ Room 220 CD
A Likelihood-Free Inference Framework for Population Genetic Data using Exchangeable Neural Networks
Jeffrey Chan · Valerio Perrone · Jeffrey Spence · Paul Jenkins · Sara Mathieson · Yun Song
Spotlight
Tue Dec 4th 04:05 -- 04:10 PM @ Room 220 E
Bias and Generalization in Deep Generative Models: An Empirical Study
Shengjia Zhao · Hongyu Ren · Arianna Yuan · Jiaming Song · Noah Goodman · Stefano Ermon
Spotlight
Tue Dec 4th 04:05 -- 04:10 PM @ Room 517 CD
Bounded-Loss Private Prediction Markets
Rafael Frongillo · Bo Waggoner
Spotlight
Tue Dec 4th 04:10 -- 04:15 PM @ Room 220 CD
Generalizing Tree Probability Estimation via Bayesian Networks
Cheng Zhang · Frederick A Matsen IV
Spotlight
Tue Dec 4th 04:10 -- 04:15 PM @ Room 220 E
Robustness of conditional GANs to noisy labels
Kiran Thekumparampil · Ashish Khetan · Zinan Lin · Sewoong Oh
Spotlight
Tue Dec 4th 04:10 -- 04:15 PM @ Room 517 CD
cpSGD: Communication-efficient and differentially-private distributed SGD
Naman Agarwal · Ananda Theertha Suresh · Felix Xinnan Yu · Sanjiv Kumar · Brendan McMahan
Spotlight
Tue Dec 4th 04:15 -- 04:20 PM @ Room 220 CD
Geometry Based Data Generation
Ofir Lindenbaum · Jay Stanley · Guy Wolf · Smita Krishnaswamy
Spotlight
Tue Dec 4th 04:15 -- 04:20 PM @ Room 220 E
BourGAN: Generative Networks with Metric Embeddings
Chang Xiao · Peilin Zhong · Changxi Zheng
Spotlight
Tue Dec 4th 04:15 -- 04:20 PM @ Room 517 CD
Adversarially Robust Generalization Requires More Data
Ludwig Schmidt · Shibani Santurkar · Dimitris Tsipras · Kunal Talwar · Aleksander Madry
Spotlight
Tue Dec 4th 04:20 -- 04:25 PM @ Room 220 CD
Point process latent variable models of larval zebrafish behavior
Anuj Sharma · Scott Linderman · Robert Johnson · Florian Engert
Spotlight
Tue Dec 4th 04:20 -- 04:25 PM @ Room 220 E
Loss Surfaces, Mode Connectivity, and Fast Ensembling of DNNs
Timur Garipov · Pavel Izmailov · Dmitrii Podoprikhin · Dmitry Vetrov · Andrew Wilson
Spotlight
Tue Dec 4th 04:20 -- 04:25 PM @ Room 517 CD
Attacks Meet Interpretability: Attribute-steered Detection of Adversarial Samples
Guanhong Tao · Shiqing Ma · Yingqi Liu · Xiangyu Zhang
Oral
Tue Dec 4th 04:25 -- 04:40 PM @ Room 220 CD
A probabilistic population code based on neural samples
Sabyasachi Shivkumar · Richard Lange · Ankani Chattoraj · Ralf Haefner
Oral
Tue Dec 4th 04:25 -- 04:40 PM @ Room 220 E
How Does Batch Normalization Help Optimization?
Shibani Santurkar · Dimitris Tsipras · Andrew Ilyas · Aleksander Madry
Oral
Tue Dec 4th 04:25 -- 04:40 PM @ Room 517 CD
Learning to Solve SMT Formulas
Mislav Balunovic · Pavol Bielik · Martin Vechev
Spotlight
Tue Dec 4th 04:40 -- 04:45 PM @ Room 220 CD
Sparse Attentive Backtracking: Temporal Credit Assignment Through Reminding
Nan Rosemary Ke · Anirudh Goyal ALIAS PARTH GOYAL · Olexa Bilaniuk · Jonathan Binas · Michael Mozer · Chris Pal · Yoshua Bengio
Spotlight
Tue Dec 4th 04:40 -- 04:45 PM @ Room 220 E
Training Neural Networks Using Features Replay
Zhouyuan Huo · Bin Gu · Heng Huang
Spotlight
Tue Dec 4th 04:40 -- 04:45 PM @ Room 517 CD
Towards Robust Detection of Adversarial Examples
Tianyu Pang · Chao Du · Yinpeng Dong · Jun Zhu
Spotlight
Tue Dec 4th 04:45 -- 04:50 PM @ Room 220 CD
Learning Temporal Point Processes via Reinforcement Learning
Shuang Li · Shuai Xiao · Shixiang Zhu · Nan Du · Yao Xie · Le Song
Spotlight
Tue Dec 4th 04:45 -- 04:50 PM @ Room 220 E
Step Size Matters in Deep Learning
Kamil Nar · Shankar Sastry
Spotlight
Tue Dec 4th 04:45 -- 04:50 PM @ Room 517 CD
Neural Architecture Search with Bayesian Optimisation and Optimal Transport
Kirthevasan Kandasamy · Willie Neiswanger · Jeff Schneider · Barnabas Poczos · Eric Xing
Spotlight
Tue Dec 4th 04:50 -- 04:55 PM @ Room 220 CD
Precision and Recall for Time Series
Nesime Tatbul · Tae Jun Lee · Stan Zdonik · Mejbah Alam · Justin Gottschlich
Spotlight
Tue Dec 4th 04:50 -- 04:55 PM @ Room 220 E
Neural Tangent Kernel: Convergence and Generalization in Neural Networks
Arthur Jacot-Guillarmod · Clement Hongler · Franck Gabriel
Spotlight
Tue Dec 4th 04:50 -- 04:55 PM @ Room 517 CD
Data-Driven Clustering via Parameterized Lloyd's Families
Maria-Florina Balcan · Travis Dick · Colin White
Spotlight
Tue Dec 4th 04:55 -- 05:00 PM @ Room 220 CD
Bayesian Nonparametric Spectral Estimation
Felipe Tobar
Spotlight
Tue Dec 4th 04:55 -- 05:00 PM @ Room 220 E
Hierarchical Graph Representation Learning with Differentiable Pooling
Zhitao Ying · Jiaxuan You · Christopher Morris · Xiang Ren · Will Hamilton · Jure Leskovec
Spotlight
Tue Dec 4th 04:55 -- 05:00 PM @ Room 517 CD
Supervising Unsupervised Learning
Vikas Garg · Adam Kalai
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #1
Point process latent variable models of larval zebrafish behavior
Anuj Sharma · Scott Linderman · Robert Johnson · Florian Engert
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #2
Provably Correct Automatic Sub-Differentiation for Qualified Programs
Sham Kakade · Jason Lee
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #3
Neural Ordinary Differential Equations
Tian Qi Chen · Yulia Rubanova · Jesse Bettencourt · David Duvenaud
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #4
Information Constraints on Auto-Encoding Variational Bayes
Romain Lopez · Jeffrey Regier · Michael Jordan · Nir Yosef
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #5
Robustness of conditional GANs to noisy labels
Kiran Thekumparampil · Ashish Khetan · Zinan Lin · Sewoong Oh
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #6
Bias and Generalization in Deep Generative Models: An Empirical Study
Shengjia Zhao · Hongyu Ren · Arianna Yuan · Jiaming Song · Noah Goodman · Stefano Ermon
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #7
Probabilistic Neural Programmed Networks for Scene Generation
Zhiwei Deng · Jiacheng Chen · YIFANG FU · Greg Mori
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #8
Step Size Matters in Deep Learning
Kamil Nar · Shankar Sastry
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #9
Neural Tangent Kernel: Convergence and Generalization in Neural Networks
Arthur Jacot-Guillarmod · Clement Hongler · Franck Gabriel
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #10
How Does Batch Normalization Help Optimization?
Shibani Santurkar · Dimitris Tsipras · Andrew Ilyas · Aleksander Madry
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #11
Towards Robust Detection of Adversarial Examples
Tianyu Pang · Chao Du · Yinpeng Dong · Jun Zhu
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #12
Training Neural Networks Using Features Replay
Zhouyuan Huo · Bin Gu · Heng Huang
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #13
Faster Neural Networks Straight from JPEG
Lionel Gueguen · Alex Sergeev · Ben Kadlec · Rosanne Liu · Jason Yosinski
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #14
Hierarchical Graph Representation Learning with Differentiable Pooling
Zhitao Ying · Jiaxuan You · Christopher Morris · Xiang Ren · Will Hamilton · Jure Leskovec
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #15
Bayesian Model-Agnostic Meta-Learning
Jaesik Yoon · Taesup Kim · Ousmane Dia · Sungwoong Kim · Yoshua Bengio · Sungjin Ahn
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #16
Evolved Policy Gradients
Rein Houthooft · Yuhua Chen · Phillip Isola · Bradly Stadie · Filip Wolski · OpenAI Jonathan Ho · Pieter Abbeel
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #17
BourGAN: Generative Networks with Metric Embeddings
Chang Xiao · Peilin Zhong · Changxi Zheng
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #18
Scalable End-to-End Autonomous Vehicle Testing via Rare-event Simulation
Matthew O'Kelly · Aman Sinha · Hongseok Namkoong · Russ Tedrake · John Duchi
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #19
Generalisation of structural knowledge in the hippocampal-entorhinal system
James Whittington · Timothy Muller · Shirely Mark · Caswell Barry · Tim Behrens
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #20
Task-Driven Convolutional Recurrent Models of the Visual System
Aran Nayebi · Daniel Bear · Jonas Kubilius · Kohitij Kar · Surya Ganguli · David Sussillo · James J DiCarlo · Daniel Yamins
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #21
Neural-Symbolic VQA: Disentangling Reasoning from Vision and Language Understanding
Kexin Yi · Jiajun Wu · Chuang Gan · Antonio Torralba · Pushmeet Kohli · Josh Tenenbaum
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #22
Extracting Relationships by Multi-Domain Matching
Yitong Li · michael Murias · geraldine Dawson · David Carlson
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #23
Sparse Attentive Backtracking: Temporal Credit Assignment Through Reminding
Nan Rosemary Ke · Anirudh Goyal ALIAS PARTH GOYAL · Olexa Bilaniuk · Jonathan Binas · Michael Mozer · Chris Pal · Yoshua Bengio
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #24
Beauty-in-averageness and its contextual modulations: A Bayesian statistical account
Chaitanya Ryali · Angela J Yu
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #25
Stimulus domain transfer in recurrent models for large scale cortical population prediction on video
Fabian Sinz · Alexander Ecker · Paul Fahey · Edgar Walker · Erick Cobos · Emmanouil Froudarakis · Dimitri Yatsenko · Zachary Pitkow · Jacob Reimer · Andreas Tolias
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #26
A probabilistic population code based on neural samples
Sabyasachi Shivkumar · Richard Lange · Ankani Chattoraj · Ralf Haefner
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #27
cpSGD: Communication-efficient and differentially-private distributed SGD
Naman Agarwal · Ananda Theertha Suresh · Felix Xinnan Yu · Sanjiv Kumar · Brendan McMahan
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #28
Bounded-Loss Private Prediction Markets
Rafael Frongillo · Bo Waggoner
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #29
Ex ante coordination and collusion in zero-sum multi-player extensive-form games
Gabriele Farina · Andrea Celli · Nicola Gatti · Tuomas Sandholm
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #30
Model-Agnostic Private Learning
Raef Bassily · Abhradeep Guha Thakurta · Om Dipakbhai Thakkar
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #31
Adversarially Robust Generalization Requires More Data
Ludwig Schmidt · Shibani Santurkar · Dimitris Tsipras · Kunal Talwar · Aleksander Madry
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #32
Probabilistic Pose Graph Optimization via Bingham Distributions and Tempered Geodesic MCMC
Tolga Birdal · Umut Simsekli · Mustafa Onur Eken · Slobodan Ilic
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #33
A Statistical Recurrent Model on the Manifold of Symmetric Positive Definite Matrices
Rudrasis Chakraborty · Chun-Hao Yang · Xingjian Zhen · Monami Banerjee · Derek Archer · David Vaillancourt · Vikas Singh · Baba Vemuri
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #34
Designing by Training: Acceleration Neural Network for Fast High-Dimensional Convolution
Longquan Dai · Liang Tang · Yuan Xie · Jinhui Tang
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #35
Greedy Hash: Towards Fast Optimization for Accurate Hash Coding in CNN
Shupeng Su · Chao Zhang · Kai Han · Yonghong Tian
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #36
Generative Probabilistic Novelty Detection with Adversarial Autoencoders
Stanislav Pidhorskyi · Ranya Almohsen · Gianfranco Doretto
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #37
Joint Sub-bands Learning with Clique Structures for Wavelet Domain Super-Resolution
Zhisheng Zhong · Tiancheng Shen · Yibo Yang · Zhouchen Lin · Chao Zhang
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #38
Compact Generalized Non-local Network
Kaiyu Yue · Ming Sun · Yuchen Yuan · Feng Zhou · Errui Ding · Fuxin Xu
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #39
BinGAN: Learning Compact Binary Descriptors with a Regularized GAN
Maciej Zieba · Piotr Semberecki · Tarek El-Gaaly · Tomasz Trzcinski
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #40
RenderNet: A deep convolutional network for differentiable rendering from 3D shapes
Thu H Nguyen-Phuoc · Chuan Li · Stephen Balaban · Yongliang Yang
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #41
LF-Net: Learning Local Features from Images
Yuki Ono · Eduard Trulls · Pascal Fua · Kwang Moo Yi
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #42
Unsupervised Learning of Shape and Pose with Differentiable Point Clouds
Eldar Insafutdinov · Alexey Dosovitskiy
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #43
Modelling and unsupervised learning of symmetric deformable object categories
James Thewlis · Hakan Bilen · Andrea Vedaldi
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #44
Multi-View Silhouette and Depth Decomposition for High Resolution 3D Object Representation
Edward Smith · Scott Fujimoto · David Meger
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #45
Image Inpainting via Generative Multi-column Convolutional Neural Networks
Yi Wang · Xin Tao · Xiaojuan Qi · Xiaoyong Shen · Jiaya Jia
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #46
Beyond Grids: Learning Graph Representations for Visual Recognition
Yin Li · Abhinav Gupta
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #47
Foreground Clustering for Joint Segmentation and Localization in Videos and Images
Abhishek Sharma
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #48
LinkNet: Relational Embedding for Scene Graph
Sanghyun Woo · Dahun Kim · Donghyeon Cho · In So Kweon
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #49
Context-aware Synthesis and Placement of Object Instances
Donghoon Lee · Ming-Yu Liu · Ming-Hsuan Yang · Sifei Liu · Jinwei Gu · Jan Kautz
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #50
Geometry-Aware Recurrent Neural Networks for Active Visual Recognition
Ricson Cheng · Ziyan Wang · Katerina Fragkiadaki
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #51
See and Think: Disentangling Semantic Scene Completion
Shice Liu · YU HU · Yiming Zeng · Qiankun Tang · Beibei Jin · Yinhe Han · Xiaowei Li
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #52
Active Matting
Xin Yang · Ke Xu · Shaozhe Chen · Shengfeng He · Baocai Yin Yin · Rynson Lau
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #53
A Unified Feature Disentangler for Multi-Domain Image Translation and Manipulation
Alexander H. Liu · Yen-Cheng Liu · Yu-Ying Yeh · Yu-Chiang Frank Wang
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #54
Turbo Learning for CaptionBot and DrawingBot
Qiuyuan Huang · Pengchuan Zhang · Dapeng Wu · Lei Zhang
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #55
Dialog-based Interactive Image Retrieval
Xiaoxiao Guo · Hui Wu · Yu Cheng · Steven Rennie · Gerald Tesauro · Rogerio Feris
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #56
Hybrid Retrieval-Generation Reinforced Agent for Medical Image Report Generation
Yuan Li · Xiaodan Liang · Zhiting Hu · Eric Xing
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #57
Sequential Context Encoding for Duplicate Removal
Lu Qi · Shu Liu · Jianping Shi · Jiaya Jia
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #58
Hybrid Knowledge Routed Modules for Large-scale Object Detection
ChenHan Jiang · Hang Xu · Xiaodan Liang · Liang Lin
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #59
SNIPER: Efficient Multi-Scale Training
Bharat Singh · Mahyar Najibi · Larry Davis
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #60
Revisiting Multi-Task Learning with ROCK: a Deep Residual Auxiliary Block for Visual Detection
Taylor Mordan · Nicolas THOME · Gilles Henaff · Matthieu Cord
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #61
MetaAnchor: Learning to Detect Objects with Customized Anchors
Tong Yang · Xiangyu Zhang · Zeming Li · Wenqiang Zhang · Jian Sun
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #62
Learning Hierarchical Semantic Image Manipulation through Structured Representations
Seunghoon Hong · Xinchen Yan · Honglak Lee · Thomas Huang
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #63
Cooperative Holistic Scene Understanding: Unifying 3D Object, Layout, and Camera Pose Estimation
Siyuan Huang · Siyuan Qi · Yinxue Xiao · Yixin Zhu · Ying Nian Wu · Song-Chun Zhu
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #64
3D-Aware Scene Manipulation via Inverse Graphics
Shunyu Yao · Tzu Ming Hsu · Jun-Yan Zhu · Jiajun Wu · Antonio Torralba · Bill Freeman · Josh Tenenbaum
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #65
FD-GAN: Pose-guided Feature Distilling GAN for Robust Person Re-identification
Yixiao Ge · Zhuowan Li · Haiyu Zhao · Guojun Yin · Shuai Yi · Xiaogang Wang · hongsheng Li
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #66
Sequence-to-Segment Networks for Segment Detection
Zijun Wei · Boyu Wang · Minh Hoai Nguyen · Jianming Zhang · Zhe Lin · Xiaohui Shen · Radomir Mech · Dimitris Samaras
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #67
Stacked Semantics-Guided Attention Model for Fine-Grained Zero-Shot Learning
yunlong yu · Zhong Ji · Yanwei Fu · Jichang Guo · Yanwei Pang · Zhongfei (Mark) Zhang
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #68
DeepExposure: Learning to Expose Photos with Asynchronously Reinforced Adversarial Learning
Runsheng Yu · Wenyu Liu · Yasen Zhang · Zhi Qu · Deli Zhao · Bo Zhang
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #69
Self-Erasing Network for Integral Object Attention
Qibin Hou · PengTao Jiang · Yunchao Wei · Ming-Ming Cheng
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #70
Searching for Efficient Multi-Scale Architectures for Dense Image Prediction
Liang-Chieh Chen · Maxwell Collins · Yukun Zhu · George Papandreou · Barret Zoph · Florian Schroff · Hartwig Adam · Jon Shlens
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #71
DifNet: Semantic Segmentation by Diffusion Networks
Peng Jiang · Fanglin Gu · Yunhai Wang · Changhe Tu · Baoquan Chen
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #72
Learning a High Fidelity Pose Invariant Model for High-resolution Face Frontalization
Jie Cao · Yibo Hu · Hongwen Zhang · Ran He · Zhenan Sun
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #73
Attention in Convolutional LSTM for Gesture Recognition
Liang Zhang · Guangming Zhu · Lin Mei · Peiyi Shen · Syed Afaq Ali Shah · Mohammed Bennamoun
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #74
Partially-Supervised Image Captioning
Peter Anderson · Stephen Gould · Mark Johnson
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #75
Learning to Specialize with Knowledge Distillation for Visual Question Answering
Jonghwan Mun · Kimin Lee · Jinwoo Shin · Bohyung Han
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #76
Chain of Reasoning for Visual Question Answering
Chenfei Wu · Jinlai Liu · Xiaojie Wang · Xuan Dong
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #77
Learning Conditioned Graph Structures for Interpretable Visual Question Answering
Will Norcliffe-Brown · Stathis Vafeias · Sarah Parisot
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #78
Out of the Box: Reasoning with Graph Convolution Nets for Factual Visual Question Answering
Medhini Narasimhan · Svetlana Lazebnik · Alexander Schwing
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #79
Overcoming Language Priors in Visual Question Answering with Adversarial Regularization
Sainandan Ramakrishnan · Aishwarya Agrawal · Stefan Lee
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #80
Non-Local Recurrent Network for Image Restoration
Ding Liu · Bihan Wen · Yuchen Fan · Chen Change Loy · Thomas Huang
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #81
Neural Nearest Neighbors Networks
Tobias Plötz · Stefan Roth
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #82
Training deep learning based denoisers without ground truth data
Shakarim Soltanayev · Se Young Chun
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #83
Adversarial Regularizers in Inverse Problems
Sebastian Lunz · Carola Schoenlieb · Ozan Öktem
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #84
Densely Connected Attention Propagation for Reading Comprehension
Yi Tay · Anh Tuan Luu · Siu Cheung Hui · Jian Su
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #85
Layer-Wise Coordination between Encoder and Decoder for Neural Machine Translation
Tianyu He · Xu Tan · Yingce Xia · Di He · Tao Qin · Zhibo Chen · Tie-Yan Liu
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #86
e-SNLI: Natural Language Inference with Natural Language Explanations
Oana-Maria Camburu · Tim Rocktäschel · Thomas Lukasiewicz · Phil Blunsom
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #87
The challenge of realistic music generation: modelling raw audio at scale
Sander Dieleman · Aaron van den Oord · Karen Simonyan
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #88
Fully Neural Network Based Speech Recognition on Mobile and Embedded Devices
Jinhwan Park · Yoonho Boo · Iksoo Choi · Sungho Shin · Wonyong Sung
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #89
Transfer Learning from Speaker Verification to Multispeaker Text-To-Speech Synthesis
Ye Jia · Yu Zhang · Ron Weiss · Quan Wang · Jonathan Shen · Fei Ren · zhifeng Chen · Patrick Nguyen · Ruoming Pang · Ignacio Lopez Moreno · Yonghui Wu
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #90
SING: Symbol-to-Instrument Neural Generator
Alexandre Defossez · Neil Zeghidour · Nicolas Usunier · Leon Bottou · Francis Bach
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #91
Neural Voice Cloning with a Few Samples
Sercan Arik · Jitong Chen · Kainan Peng · Wei Ping · Yanqi Zhou
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #92
GroupReduce: Block-Wise Low-Rank Approximation for Neural Language Model Shrinking
Patrick Chen · Si Si · Yang Li · Ciprian Chelba · Cho-Jui Hsieh
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #93
Dialog-to-Action: Conversational Question Answering Over a Large-Scale Knowledge Base
Daya Guo · Duyu Tang · Nan Duan · Ming Zhou · Jian Yin
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #94
Generating Informative and Diverse Conversational Responses via Adversarial Information Maximization
Yizhe Zhang · Michel Galley · Jianfeng Gao · Zhe Gan · Xiujun Li · Chris Brockett · Bill Dolan
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #95
Answerer in Questioner's Mind: Information Theoretic Approach to Goal-Oriented Visual Dialog
Sang-Woo Lee · Yu-Jung Heo · Byoung-Tak Zhang
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #96
Trajectory Convolution for Action Recognition
Yue Zhao · Yuanjun Xiong · Dahua Lin
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #97
Video Prediction via Selective Sampling
Jingwei Xu · Bingbing Ni · Xiaokang Yang
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #98
Unsupervised Learning of Artistic Styles with Archetypal Style Analysis
Daan Wynen · Cordelia Schmid · Julien Mairal
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #99
Attacks Meet Interpretability: Attribute-steered Detection of Adversarial Samples
Guanhong Tao · Shiqing Ma · Yingqi Liu · Xiangyu Zhang
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #100
Speaker-Follower Models for Vision-and-Language Navigation
Daniel Fried · Ronghang Hu · Volkan Cirik · Anna Rohrbach · Jacob Andreas · Louis-Philippe Morency · Taylor Berg-Kirkpatrick · Kate Saenko · Dan Klein · Trevor Darrell
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #101
Neural Code Comprehension: A Learnable Representation of Code Semantics
Tal Ben-Nun · Alice Shoshana Jakobovits · Torsten Hoefler
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #102
MiME: Multilevel Medical Embedding of Electronic Health Records for Predictive Healthcare
Edward Choi · Cao Xiao · Walter Stewart · Jimeng Sun
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #103
Distilled Wasserstein Learning for Word Embedding and Topic Modeling
Hongteng Xu · Wenlin Wang · Wei Liu · Lawrence Carin
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #104
Learning to Optimize Tensor Programs
Tianqi Chen · Lianmin Zheng · Eddie Yan · Ziheng Jiang · Thierry Moreau · Luis Ceze · Carlos Guestrin · Arvind Krishnamurthy
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #105
Learning to Solve SMT Formulas
Mislav Balunovic · Pavol Bielik · Martin Vechev
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #106
Data center cooling using model-predictive control
Nevena Lazic · Craig Boutilier · Tyler Lu · Eehern Wong · Binz Roy · MK Ryu · Greg Imwalle
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #107
Bayesian Inference of Temporal Task Specifications from Demonstrations
Ankit Shah · Pritish Kamath · Julie A Shah · Shen Li
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #108
Training Deep Neural Networks with 8-bit Floating Point Numbers
Naigang Wang · Jungwook Choi · Daniel Brand · Chia-Yu Chen · Kailash Gopalakrishnan
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #109
Snap ML: A Hierarchical Framework for Machine Learning
Celestine Dünner · Thomas Parnell · Dimitrios Sarigiannis · Nikolas Ioannou · Andreea Anghel · Gummadi Ravi · Madhusudanan Kandasamy · Haralampos Pozidis
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #110
Learning filter widths of spectral decompositions with wavelets
Haidar Khan · Bulent Yener
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #111
A Likelihood-Free Inference Framework for Population Genetic Data using Exchangeable Neural Networks
Jeffrey Chan · Valerio Perrone · Jeffrey Spence · Paul Jenkins · Sara Mathieson · Yun Song
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #112
Latent Gaussian Activity Propagation: Using Smoothness and Structure to Separate and Localize Sounds in Large Noisy Environments
Daniel Johnson · Daniel Gorelik · Ross E Mawhorter · Kyle Suver · Weiqing Gu · Steven Xing · Cody Gabriel · Peter Sankhagowit
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #113
Inferring Latent Velocities from Weather Radar Data using Gaussian Processes
Rico Angell · Daniel Sheldon
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #114
Bayesian Nonparametric Spectral Estimation
Felipe Tobar
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #115
Learning a Warping Distance from Unlabeled Time Series Using Sequence Autoencoders
Abubakar Abid · James Zou
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #116
Precision and Recall for Time Series
Nesime Tatbul · Tae Jun Lee · Stan Zdonik · Mejbah Alam · Justin Gottschlich
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #117
Deep Generative Markov State Models
Hao Wu · Andreas Mardt · Luca Pasquali · Frank Noe
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #118
Doubly Robust Bayesian Inference for Non-Stationary Streaming Data with $\beta$-Divergences
Jeremias Knoblauch · Jack E Jewson · Theodoros Damoulas
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #119
Regularization Learning Networks: Deep Learning for Tabular Datasets
Ira Shavitt · Eran Segal
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #120
Generative modeling for protein structures
Namrata Anand · Possu Huang
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #121
Geometry Based Data Generation
Ofir Lindenbaum · Jay Stanley · Guy Wolf · Smita Krishnaswamy
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #122
Learning Concave Conditional Likelihood Models for Improved Analysis of Tandem Mass Spectra
John T Halloran · David M Rocke
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #123
Generalizing Tree Probability Estimation via Bayesian Networks
Cheng Zhang · Frederick A Matsen IV
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #124
Learning Temporal Point Processes via Reinforcement Learning
Shuang Li · Shuai Xiao · Shixiang Zhu · Nan Du · Yao Xie · Le Song
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #125
Exponentially Weighted Imitation Learning for Batched Historical Data
Qing Wang · Jiechao Xiong · Lei Han · peng sun · Han Liu · Tong Zhang
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #126
Evidential Deep Learning to Quantify Classification Uncertainty
Murat Sensoy · Lance Kaplan · Melih Kandemir
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #127
Explanations based on the Missing: Towards Contrastive Explanations with Pertinent Negatives
Amit Dhurandhar · Pin-Yu Chen · Ronny Luss · Chun-Chen Tu · Paishun Ting · Karthikeyan Shanmugam · Payel Das
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #128
Towards Robust Interpretability with Self-Explaining Neural Networks
David Alvarez Melis · Tommi Jaakkola
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #129
Model Agnostic Supervised Local Explanations
Gregory Plumb · Denali Molitor · Ameet Talwalkar
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #130
To Trust Or Not To Trust A Classifier
Heinrich Jiang · Been Kim · Melody Guan · Maya Gupta
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #131
Predict Responsibly: Improving Fairness and Accuracy by Learning to Defer
David Madras · Toni Pitassi · Richard Zemel
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #132
Hunting for Discriminatory Proxies in Linear Regression Models
Samuel Yeom · Anupam Datta · Matt Fredrikson
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #133
Empirical Risk Minimization Under Fairness Constraints
Michele Donini · Luca Oneto · Shai Ben-David · John Shawe-Taylor · Massimiliano Pontil
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #134
Approximation algorithms for stochastic clustering
David Harris · Shi Li · Aravind Srinivasan · Khoa Trinh · Thomas Pensyl
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #135
Re-evaluating evaluation
David Balduzzi · Karl Tuyls · Julien Perolat · Thore Graepel
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #136
Does mitigating ML's impact disparity require treatment disparity?
Zachary Lipton · Julian McAuley · Alexandra Chouldechova
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #137
Enhancing the Accuracy and Fairness of Human Decision Making
Isabel Valera · Adish Singla · Manuel Gomez Rodriguez
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #138
The Price of Fair PCA: One Extra dimension
Samira Samadi · Uthaipon Tantipongpipat · Jamie Morgenstern · Mohit Singh · Santosh Vempala
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #139
Practical Methods for Graph Two-Sample Testing
Debarghya Ghoshdastidar · Ulrike von Luxburg
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #140
Topkapi: Parallel and Fast Sketches for Finding Top-K Frequent Elements
Ankush Mandal · He Jiang · Anshumali Shrivastava · Vivek Sarkar
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #141
KDGAN: Knowledge Distillation with Generative Adversarial Networks
Xiaojie Wang · Rui Zhang · Yu Sun · Jianzhong Qi
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #142
Modeling Dynamic Missingness of Implicit Feedback for Recommendation
Menghan Wang · Mingming Gong · Xiaolin Zheng · Kun Zhang
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #143
Gamma-Poisson Dynamic Matrix Factorization Embedded with Metadata Influence
Trong Dinh Thac Do · Longbing Cao
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #144
Non-metric Similarity Graphs for Maximum Inner Product Search
Stanislav Morozov · Artem Babenko
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #145
Norm-Ranging LSH for Maximum Inner Product Search
Xiao Yan · Jinfeng Li · Xinyan Dai · Hongzhi Chen · James Cheng
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #146
A Dual Framework for Low-rank Tensor Completion
Madhav Nimishakavi · Pratik Kumar Jawanpuria · Bamdev Mishra
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #147
Low-Rank Tucker Decomposition of Large Tensors Using TensorSketch
Osman Asif Malik · Stephen Becker
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #148
Dropping Symmetry for Fast Symmetric Nonnegative Matrix Factorization
Zhihui Zhu · Xiao Li · Kai Liu · Qiuwei Li
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #149
Semidefinite relaxations for certifying robustness to adversarial examples
Aditi Raghunathan · Jacob Steinhardt · Percy Liang
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #150
Privacy Amplification by Subsampling: Tight Analyses via Couplings and Divergences
Borja Balle · Gilles Barthe · Marco Gaboardi
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #151
Differentially Private Testing of Identity and Closeness of Discrete Distributions
Jayadev Acharya · Ziteng Sun · Huanyu Zhang
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #152
Differentially Private k-Means with Constant Multiplicative Error
Uri Stemmer · Haim Kaplan
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #153
Local Differential Privacy for Evolving Data
Matthew Joseph · Aaron Roth · Jonathan Ullman · Bo Waggoner
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #154
Adversarial Attacks on Stochastic Bandits
Kwang-Sung Jun · Lihong Li · Yuzhe Ma · Jerry Zhu
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #155
Distributed Learning without Distress: Privacy-Preserving Empirical Risk Minimization
Bargav Jayaraman · Lingxiao Wang · David Evans · Quanquan Gu
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #156
A Spectral View of Adversarially Robust Features
Shivam Garg · Vatsal Sharan · Brian Zhang · Gregory Valiant
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #157
Efficient Formal Safety Analysis of Neural Networks
Shiqi Wang · Kexin Pei · Justin Whitehouse · Junfeng Yang · Suman Jana
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #158
Contamination Attacks and Mitigation in Multi-Party Machine Learning
Jamie Hayes · Olga Ohrimenko
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #159
Explaining Deep Learning Models -- A Bayesian Non-parametric Approach
Wenbo Guo · Sui Huang · Yunzhe Tao · Xinyu Xing · Lin Lin
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #160
Data-Driven Clustering via Parameterized Lloyd's Families
Maria-Florina Balcan · Travis Dick · Colin White
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #161
Manifold Structured Prediction
Alessandro Rudi · Carlo Ciliberto · GianMaria Marconi · Lorenzo Rosasco
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #162
Loss Surfaces, Mode Connectivity, and Fast Ensembling of DNNs
Timur Garipov · Pavel Izmailov · Dmitrii Podoprikhin · Dmitry Vetrov · Andrew Wilson
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #163
Masking: A New Perspective of Noisy Supervision
Bo Han · Jiangchao Yao · Gang Niu · Mingyuan Zhou · Ivor Tsang · Ya Zhang · Masashi Sugiyama
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #164
Supervising Unsupervised Learning
Vikas Garg · Adam Kalai
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #165
One-Shot Unsupervised Cross Domain Translation
Sagie Benaim · Lior Wolf
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #166
Neural Architecture Search with Bayesian Optimisation and Optimal Transport
Kirthevasan Kandasamy · Willie Neiswanger · Jeff Schneider · Barnabas Poczos · Eric Xing
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #167
Adapted Deep Embeddings: A Synthesis of Methods for k-Shot Inductive Transfer Learning
Tyler Scott · Karl Ridgeway · Michael Mozer
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #168
Completing State Representations using Spectral Learning
Nan Jiang · Alex Kulesza · Satinder Singh
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #169
Data-Efficient Hierarchical Reinforcement Learning
Ofir Nachum · Shixiang (Shane) Gu · Honglak Lee · Sergey Levine
Poster
Tue Dec 4th 05:00 -- 07:00 PM @ Room 210 & 230 AB #170
The Cluster Description Problem - Complexity Results, Formulations and Approximations
Ian Davidson · Antoine Gourru · S Ravi
Invited Talk (Posner Lecture)
Wed Dec 5th 08:30 -- 09:20 AM @ Rooms 220 CDE
Reproducible, Reusable, and Robust Reinforcement Learning
Joelle Pineau
Break
Wed Dec 5th 09:20 -- 09:45 AM @
Coffee Break
Spotlight
Wed Dec 5th 09:45 -- 09:50 AM @ Room 220 CD
A Smoothed Analysis of the Greedy Algorithm for the Linear Contextual Bandit Problem
Sampath Kannan · Jamie Morgenstern · Aaron Roth · Bo Waggoner · Zhiwei Steven Wu
Spotlight
Wed Dec 5th 09:45 -- 09:50 AM @ Room 220 E
Deep Network for the Integrated 3D Sensing of Multiple People in Natural Images
Andrei Zanfir · Elisabeta Marinoiu · Mihai Zanfir · Alin-Ionut Popa · Cristian Sminchisescu
Spotlight
Wed Dec 5th 09:45 -- 09:50 AM @ Room 517 CD
Revisiting $(\epsilon, \gamma, \tau)$-similarity learning for domain adaptation
Sofiane Dhouib · Ievgen Redko
Spotlight
Wed Dec 5th 09:50 -- 09:55 AM @ Room 220 CD
Almost Optimal Algorithms for Linear Stochastic Bandits with Heavy-Tailed Payoffs
Han Shao · Xiaotian Yu · Irwin King · Michael Lyu
Spotlight
Wed Dec 5th 09:50 -- 09:55 AM @ Room 220 E
Delta-encoder: an effective sample synthesis method for few-shot object recognition
Eli Schwartz · Leonid Karlinsky · Joseph Shtok · Sivan Harary · Mattias Marder · Abhishek Kumar · Rogerio Feris · Raja Giryes · Alex Bronstein
Spotlight
Wed Dec 5th 09:50 -- 09:55 AM @ Room 517 CD
Leveraged volume sampling for linear regression
Michal Derezinski · Manfred Warmuth · Daniel Hsu
Spotlight
Wed Dec 5th 09:55 -- 10:00 AM @ Room 220 CD
End-to-End Differentiable Physics for Learning and Control
Filipe de Avila Belbute-Peres · Kevin Smith · Kelsey Allen · Josh Tenenbaum · J. Zico Kolter
Spotlight
Wed Dec 5th 09:55 -- 10:00 AM @ Room 220 E
Text-Adaptive Generative Adversarial Networks: Manipulating Images with Natural Language
Seonghyeon Nam · Yunji Kim · Seon Joo Kim
Spotlight
Wed Dec 5th 09:55 -- 10:00 AM @ Room 517 CD
Synthesize Policies for Transfer and Adaptation across Tasks and Environments
Hexiang Hu · Liyu Chen · Boqing Gong · Fei Sha
Spotlight
Wed Dec 5th 10:00 -- 10:05 AM @ Room 220 CD
Near Optimal Exploration-Exploitation in Non-Communicating Markov Decision Processes
Ronan Fruit · Matteo Pirotta · Alessandro Lazaric
Spotlight
Wed Dec 5th 10:00 -- 10:05 AM @ Room 220 E
Neighbourhood Consensus Networks
Ignacio Rocco · Mircea Cimpoi · Relja Arandjelović · Akihiko Torii · Tomas Pajdla · Josef Sivic
Spotlight
Wed Dec 5th 10:00 -- 10:05 AM @ Room 517 CD
Sublinear Time Low-Rank Approximation of Distance Matrices
Ainesh Bakshi · David Woodruff
Oral
Wed Dec 5th 10:05 -- 10:20 AM @ Room 220 CD
Exploration in Structured Reinforcement Learning
Jungseul Ok · Alexandre Proutiere · Damianos Tranos
Oral
Wed Dec 5th 10:05 -- 10:20 AM @ Room 220 E
Visual Memory for Robust Path Following
Ashish Kumar · Saurabh Gupta · David Fouhey · Sergey Levine · Jitendra Malik
Oral
Wed Dec 5th 10:05 -- 10:20 AM @ Room 517 CD
Nearly tight sample complexity bounds for learning mixtures of Gaussians via sample compression schemes
Hassan Ashtiani · Shai Ben-David · Nick Harvey · Christopher Liaw · Abbas Mehrabian · Yaniv Plan
Spotlight
Wed Dec 5th 10:20 -- 10:25 AM @ Room 220 CD
Acceleration through Optimistic No-Regret Dynamics
Jun-Kun Wang · Jacob Abernethy
Spotlight
Wed Dec 5th 10:20 -- 10:25 AM @ Room 220 E
Recurrent Transformer Networks for Semantic Correspondence
Seungryong Kim · Stephen Lin · SANG RYUL JEON · Dongbo Min · Kwanghoon Sohn
Spotlight
Wed Dec 5th 10:20 -- 10:25 AM @ Room 517 CD
Minimax Statistical Learning with Wasserstein distances
Jaeho Lee · Maxim Raginsky
Spotlight
Wed Dec 5th 10:25 -- 10:30 AM @ Room 220 CD
On Oracle-Efficient PAC RL with Rich Observations
Christoph Dann · Nan Jiang · Akshay Krishnamurthy · Alekh Agarwal · John Langford · Robert Schapire
Spotlight
Wed Dec 5th 10:25 -- 10:30 AM @ Room 220 E
Sequential Attend, Infer, Repeat: Generative Modelling of Moving Objects
Adam Kosiorek · Hyunjik Kim · Yee Whye Teh · Ingmar Posner
Spotlight
Wed Dec 5th 10:25 -- 10:30 AM @ Room 517 CD
Generalization Bounds for Uniformly Stable Algorithms
Vitaly Feldman · Jan Vondrak
Spotlight
Wed Dec 5th 10:30 -- 10:35 AM @ Room 220 CD
Constant Regret, Generalized Mixability, and Mirror Descent
Zakaria Mhammedi · Robert Williamson
Spotlight
Wed Dec 5th 10:30 -- 10:35 AM @ Room 220 E
Sanity Checks for Saliency Maps
Julius Adebayo · Justin Gilmer · Michael Muelly · Ian Goodfellow · Moritz Hardt · Been Kim
Spotlight
Wed Dec 5th 10:30 -- 10:35 AM @ Room 517 CD
A loss framework for calibrated anomaly detection
Aditya Menon · Robert Williamson
Spotlight
Wed Dec 5th 10:35 -- 10:40 AM @ Room 220 CD
Efficient Online Portfolio with Logarithmic Regret
Haipeng Luo · Chen-Yu Wei · Kai Zheng
Spotlight
Wed Dec 5th 10:35 -- 10:40 AM @ Room 220 E
A Probabilistic U-Net for Segmentation of Ambiguous Images
Simon Kohl · Bernardino Romera-Paredes · Clemens Meyer · Jeffrey De Fauw · Joseph R. Ledsam · Klaus Maier-Hein · S. M. Ali Eslami · Danilo Jimenez Rezende · Olaf Ronneberger
Spotlight
Wed Dec 5th 10:35 -- 10:40 AM @ Room 517 CD
Sharp Bounds for Generalized Uniformity Testing
Ilias Diakonikolas · Daniel M. Kane · Alistair Stewart
Spotlight
Wed Dec 5th 10:40 -- 10:45 AM @ Room 220 CD
Solving Large Sequential Games with the Excessive Gap Technique
Christian Kroer · Gabriele Farina · Tuomas Sandholm
Spotlight
Wed Dec 5th 10:40 -- 10:45 AM @ Room 220 E
Virtual Class Enhanced Discriminative Embedding Learning
Binghui Chen · Weihong Deng · Haifeng Shen
Spotlight
Wed Dec 5th 10:40 -- 10:45 AM @ Room 517 CD
Convex Elicitation of Continuous Properties
Jessica Finocchiaro · Rafael Frongillo
Demonstration
Wed Dec 5th 10:45 AM -- 07:30 PM @ Room 510 ABCD #D9
A Cooperative Visually Grounded Dialogue Game with a Humanoid Robot
Jordan Prince Tremblay · Ismael Balafrej · Felix Labelle · Félix Martel-Denis · Eric Matte · Julien Chouinard-Beaupré · Adam Letourneau · Antoine Mercier-Nicol · Simon Brodeur · François Ferland · Jean ROUAT
Demonstration
Wed Dec 5th 10:45 AM -- 07:30 PM @ Room 510 ABCD #D4
RieszNets: Accurate Real-Time 2D/3D Image Super-Resolution
Saarthak Sachdeva · Mohnish Chakravarti
Demonstration
Wed Dec 5th 10:45 AM -- 07:30 PM @ Room 510 ABCD #D6
Deep Reinforcement Learning for Online Order Dispatching and Driver Repositioning in Ride-sharing
Zhiwei Qin · Xiaocheng Tang · yan jiao · Chenxi Wang
Demonstration
Wed Dec 5th 10:45 AM -- 07:30 PM @ Room 510 ABCD #D10
Automatic Curriculum Generation Applied to Teaching Novices a Short Bach Piano Segment
Emma Brunskill · Tong Mu · Karan Goel · Jonathan Bragg
Demonstration
Wed Dec 5th 10:45 AM -- 07:30 PM @ Room 510 ABCD #D7
Multi-Word Imputation and Sentence Expansion
Osman Ramadan · Douglas Orr · Dmitry Stratiychuk · Błażej Czapp
Demonstration
Wed Dec 5th 10:45 AM -- 07:30 PM @ Room 510 ABCD #D1
BigBlueBot: A Demonstration of How to Detect Egregious Conversations with Chatbots
Casey Dugan · Justin D Weisz · Narendra Nath Joshi · Ingrid Lange · J Johnson · Mohit Jain · Werner Geyer
Demonstration
Wed Dec 5th 10:45 AM -- 07:30 PM @ Room 510 ABCD #D2
Perception, sensing, motion planning and robot control using AI for automated feeding of upper-extremity mobility impaired people
Tapomayukh Bhattacharjee · Daniel Gallenberger · David Dubois · Siddhartha Srinivasa · Louis L'Écuyer-Lapierre
Demonstration
Wed Dec 5th 10:45 AM -- 07:30 PM @ Room 510 ABCD #D3
Play Imperfect Information Games against Neural Networks
Andy C Kitchen · Michela Benedetti · Hon Weng Chong
Demonstration
Wed Dec 5th 10:45 AM -- 07:30 PM @ Room 510 ABCD #D8
Autonomous robotic manipulation with a desktop research platform
Jonathan Long · Brandon Pereira · Max Reynolds · Rahul Rawat
Demonstration
Wed Dec 5th 10:45 AM -- 07:30 PM @ Room 510 ABCD #D5
PatentAI: IP Infringement Detection with Enhanced Paraphrase Identification
Youssef Drissi
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #1
Balanced Policy Evaluation and Learning
Nathan Kallus
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #2
Exponentiated Strongly Rayleigh Distributions
Zelda Mariet · Suvrit Sra · Stefanie Jegelka
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #3
Parsimonious Bayesian deep networks
Mingyuan Zhou
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #4
Stein Variational Gradient Descent as Moment Matching
Qiang Liu · Dilin Wang
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #5
Hamiltonian Variational Auto-Encoder
Anthony L Caterini · Arnaud Doucet · Dino Sejdinovic
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #6
Predictive Approximate Bayesian Computation via Saddle Points
Yingxiang Yang · Bo Dai · Negar Kiyavash · Niao He
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #7
Importance Weighting and Variational Inference
Justin Domke · Daniel Sheldon
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #8
Orthogonally Decoupled Variational Gaussian Processes
Hugh Salimbeni · Ching-An Cheng · Byron Boots · Marc Deisenroth
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #9
ATOMO: Communication-efficient Learning via Atomic Sparsification
Hongyi Wang · Scott Sievert · Shengchao Liu · Zachary Charles · Dimitris Papailiopoulos · Stephen Wright
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #10
Sparsified SGD with Memory
Sebastian Stich · Jean-Baptiste Cordonnier · Martin Jaggi
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #11
SEGA: Variance Reduction via Gradient Sketching
Filip Hanzely · Konstantin Mishchenko · Peter Richtarik
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #12
Non-monotone Submodular Maximization in Exponentially Fewer Iterations
Eric Balkanski · Adam Breuer · Yaron Singer
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #13
Stochastic Primal-Dual Method for Empirical Risk Minimization with O(1) Per-Iteration Complexity
Conghui Tan · Tong Zhang · Shiqian Ma · Ji Liu
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #14
Rest-Katyusha: Exploiting the Solution's Structure via Scheduled Restart Schemes
Junqi Tang · Mohammad Golbabaee · Francis Bach · Mike E davies
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #15
Inexact trust-region algorithms on Riemannian manifolds
Hiroyuki Kasai · Bamdev Mishra
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #16
On Markov Chain Gradient Descent
Tao Sun · Yuejiao Sun · Wotao Yin
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #17
Gradient Descent Meets Shift-and-Invert Preconditioning for Eigenvector Computation
Zhiqiang Xu
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #18
Global Non-convex Optimization with Discretized Diffusions
Murat A Erdogdu · Lester Mackey · Ohad Shamir
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #19
A theory on the absence of spurious solutions for nonconvex and nonsmooth optimization
Cedric Josz · Yi Ouyang · Richard Zhang · Javad Lavaei · Somayeh Sojoudi
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #20
The Limit Points of (Optimistic) Gradient Descent in Min-Max Optimization
Constantinos Daskalakis · Ioannis Panageas
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #21
Porcupine Neural Networks: Approximating Neural Network Landscapes
Soheil Feizi · Hamid Javadi · Jesse Zhang · David Tse
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #22
Adding One Neuron Can Eliminate All Bad Local Minima
SHIYU LIANG · Ruoyu Sun · Jason Lee · R. Srikant
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #23
Improving Explorability in Variational Inference with Annealed Variational Objectives
Chin-Wei Huang · Shawn Tan · Alexandre Lacoste · Aaron Courville
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #24
Sequential Attend, Infer, Repeat: Generative Modelling of Moving Objects
Adam Kosiorek · Hyunjik Kim · Yee Whye Teh · Ingmar Posner
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #25
Delta-encoder: an effective sample synthesis method for few-shot object recognition
Eli Schwartz · Leonid Karlinsky · Joseph Shtok · Sivan Harary · Mattias Marder · Abhishek Kumar · Rogerio Feris · Raja Giryes · Alex Bronstein
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #26
Joint Active Feature Acquisition and Classification with Variable-Size Set Encoding
Hajin Shim · Sung Ju Hwang · Eunho Yang
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #27
PCA of high dimensional random walks with comparison to neural network training
Joseph Antognini · Jascha Sohl-Dickstein
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #28
Insights on representational similarity in neural networks with canonical correlation
Ari Morcos · Maithra Raghu · Samy Bengio
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #29
Adversarial vulnerability for any classifier
Alhussein Fawzi · Hamza Fawzi · Omar Fawzi
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #30
Sanity Checks for Saliency Maps
Julius Adebayo · Justin Gilmer · Michael Muelly · Ian Goodfellow · Moritz Hardt · Been Kim
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #31
MetaGAN: An Adversarial Approach to Few-Shot Learning
Ruixiang ZHANG · Tong Che · Zoubin Ghahramani · Yoshua Bengio · Yangqiu Song
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #32
Deep Generative Models with Learnable Knowledge Constraints
Zhiting Hu · Zichao Yang · Ruslan Salakhutdinov · LIANHUI Qin · Xiaodan Liang · Haoye Dong · Eric Xing
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #33
Learning Attractor Dynamics for Generative Memory
Yan Wu · Gregory Wayne · Karol Gregor · Timothy Lillicrap
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #34
Fast deep reinforcement learning using online adjustments from the past
Steven Hansen · Alexander Pritzel · Pablo Sprechmann · Andre Barreto · Charles Blundell
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #35
Blockwise Parallel Decoding for Deep Autoregressive Models
Mitchell Stern · Noam Shazeer · Jakob Uszkoreit
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #36
Automatic Program Synthesis of Long Programs with a Learned Garbage Collector
Amit Zohar · Lior Wolf
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #37
The Global Anchor Method for Quantifying Linguistic Shifts and Domain Adaptation
Zi Yin · Vin Sachidananda · Balaji Prabhakar
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #38
End-to-End Differentiable Physics for Learning and Control
Filipe de Avila Belbute-Peres · Kevin Smith · Kelsey Allen · Josh Tenenbaum · J. Zico Kolter
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #39
Neural Arithmetic Logic Units
Andrew Trask · Felix Hill · Scott Reed · Jack Rae · Chris Dyer · Phil Blunsom
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #40
Reinforced Continual Learning
Ju Xu · Zhanxing Zhu
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #41
Poison Frogs! Targeted Clean-Label Poisoning Attacks on Neural Networks
Ali Shafahi · W. Ronny Huang · Mahyar Najibi · Octavian Suciu · Christoph Studer · Tudor Dumitras · Tom Goldstein
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #42
Generalizing to Unseen Domains via Adversarial Data Augmentation
Riccardo Volpi · Hongseok Namkoong · Ozan Sener · John Duchi · Vittorio Murino · Silvio Savarese
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #43
On the Local Hessian in Back-propagation
Huishuai Zhang · Wei Chen · Tie-Yan Liu
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #44
Lipschitz-Margin Training: Scalable Certification of Perturbation Invariance for Deep Neural Networks
Yusuke Tsuzuku · Issei Sato · Masashi Sugiyama
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #45
Tangent: Automatic differentiation using source-code transformation for dynamically typed array programming
Bart van Merrienboer · Dan Moldovan · Alexander Wiltschko
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #46
Simple, Distributed, and Accelerated Probabilistic Programming
Dustin Tran · Matthew Hoffman · Dave Moore · Christopher Suter · Srinivas Vasudevan · Alexey Radul · Matthew Johnson · Rif A. Saurous
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #47
Power-law efficient neural codes provide general link between perceptual bias and discriminability
Michael Morais · Jonathan W Pillow
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #48
DropBlock: A regularization method for convolutional networks
Golnaz Ghiasi · Tsung-Yi Lin · Quoc V Le
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #49
Learning sparse neural networks via sensitivity-driven regularization
Enzo Tartaglione · Skjalg Lepsøy · Attilio Fiandrotti · Gianluca Francini
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #50
Critical initialisation for deep signal propagation in noisy rectifier neural networks
Arnu Pretorius · Elan van Biljon · Steve Kroon · Herman Kamper
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #51
The streaming rollout of deep networks - towards fully model-parallel execution
Volker Fischer · Jan Koehler · Thomas Pfeil
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #52
The Spectrum of the Fisher Information Matrix of a Single-Hidden-Layer Neural Network
Jeffrey Pennington · Pratik Worah
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #53
Learning Optimal Reserve Price against Non-myopic Bidders
Jinyan Liu · Zhiyi Huang · Xiangning Wang
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #54
Beyond Log-concavity: Provable Guarantees for Sampling Multi-modal Distributions using Simulated Tempering Langevin Monte Carlo
HOLDEN LEE · Andrej Risteski · Rong Ge
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #55
On Binary Classification in Extreme Regions
Hamid JALALZAI · Stephan Clémençon · Anne Sabourin
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #56
PAC-Bayes bounds for stable algorithms with instance-dependent priors
Omar Rivasplata · Csaba Szepesvari · John Shawe-Taylor · Emilio Parrado-Hernandez · Shiliang Sun
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #57
Improved Algorithms for Collaborative PAC Learning
Huy Nguyen · Lydia Zakynthinou
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #58
Data Amplification: A Unified and Competitive Approach to Property Estimation
Yi HAO · Alon Orlitsky · Ananda Theertha Suresh · Yihong Wu
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #59
Mean-field theory of graph neural networks in graph partitioning
Tatsuro Kawamoto · Masashi Tsubaki · Tomoyuki Obuchi
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #60
Statistical mechanics of low-rank tensor decomposition
Jonathan Kadmon · Surya Ganguli
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #61
Plug-in Estimation in High-Dimensional Linear Inverse Problems: A Rigorous Analysis
Alyson Fletcher · Parthe Pandit · Sundeep Rangan · Subrata Sarkar · Philip Schniter
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #62
The Description Length of Deep Learning models
Léonard Blier · Yann Ollivier
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #63
Deepcode: Feedback Codes via Deep Learning
Hyeji Kim · Yihan Jiang · Sreeram Kannan · Sewoong Oh · Pramod Viswanath
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #64
Binary Rating Estimation with Graph Side Information
Kwangjun Ahn · Kangwook Lee · Hyunseung Cha · Changho Suh
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #65
Optimization of Smooth Functions with Noisy Observations: Local Minimax Rates
Yining Wang · Sivaraman Balakrishnan · Aarti Singh
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #66
Parameters as interacting particles: long time convergence and asymptotic error scaling of neural networks
Grant Rotskoff · Eric Vanden-Eijnden
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #67
Towards Understanding Acceleration Tradeoff between Momentum and Asynchrony in Nonconvex Stochastic Optimization
Tianyi Liu · Shiyang Li · Jianping Shi · Enlu Zhou · Tuo Zhao
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #68
Asymptotic optimality of adaptive importance sampling
François Portier · Bernard Delyon
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #69
Inference Aided Reinforcement Learning for Incentive Mechanism Design in Crowdsourcing
Zehong Hu · Yitao Liang · Jie Zhang · Zhao Li · Yang Liu
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #70
A Game-Theoretic Approach to Recommendation Systems with Strategic Content Providers
Omer Ben-Porat · Moshe Tennenholtz
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #71
A Mathematical Model For Optimal Decisions In A Representative Democracy
Malik Magdon-Ismail · Lirong Xia
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #72
Universal Growth in Production Economies
Simina Branzei · Ruta Mehta · Noam Nisan
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #73
Convex Elicitation of Continuous Properties
Jessica Finocchiaro · Rafael Frongillo
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #74
Contextual Pricing for Lipschitz Buyers
Jieming Mao · Renato Leme · Jon Schneider
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #75
Learning in Games with Lossy Feedback
Zhengyuan Zhou · Panayotis Mertikopoulos · Susan Athey · Nicholas Bambos · Peter W Glynn · Yinyu Ye
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #76
Multiplicative Weights Updates with Constant Step-Size in Graphical Constant-Sum Games
Yun Kuen Cheung
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #77
Solving Large Sequential Games with the Excessive Gap Technique
Christian Kroer · Gabriele Farina · Tuomas Sandholm
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #78
Practical exact algorithm for trembling-hand equilibrium refinements in games
Gabriele Farina · Nicola Gatti · Tuomas Sandholm
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #79
Improving Online Algorithms via ML Predictions
Manish Purohit · Zoya Svitkina · Ravi Kumar
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #80
Variance-Reduced Stochastic Gradient Descent on Streaming Data
Ellango Jothimurugesan · Ashraf Tahmasbi · Phillip Gibbons · Srikanta Tirthapura
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #81
Regret Bounds for Robust Adaptive Control of the Linear Quadratic Regulator
Sarah Dean · Horia Mania · Nikolai Matni · Benjamin Recht · Stephen Tu
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #82
PAC-learning in the presence of adversaries
Daniel Cullina · Arjun Nitin Bhagoji · Prateek Mittal
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #83
Tight Bounds for Collaborative PAC Learning via Multiplicative Weights
Jiecao Chen · Qin Zhang · Yuan Zhou
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #84
Understanding Weight Normalized Deep Neural Networks with Rectified Linear Units
Yixi Xu · Xiao Wang
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #85
Generalization Bounds for Uniformly Stable Algorithms
Vitaly Feldman · Jan Vondrak
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #86
Minimax Statistical Learning with Wasserstein distances
Jaeho Lee · Maxim Raginsky
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #87
Differentially Private Uniformly Most Powerful Tests for Binomial Data
Jordan Awan · Aleksandra Slavković
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #88
Sketching Method for Large Scale Combinatorial Inference
Wei Sun · Junwei Lu · Han Liu
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #89
An Improved Analysis of Alternating Minimization for Structured Multi-Response Regression
Sheng Chen · Arindam Banerjee
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #90
MixLasso: Generalized Mixed Regression via Convex Atomic-Norm Regularization
Ian En-Hsu Yen · Wei-Cheng Lee · Kai Zhong · Sung-En Chang · Pradeep Ravikumar · Shou-De Lin
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #91
A Theory-Based Evaluation of Nearest Neighbor Models Put Into Practice
Hendrik Fichtenberger · Dennis Rohde
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #92
Sharp Bounds for Generalized Uniformity Testing
Ilias Diakonikolas · Daniel M. Kane · Alistair Stewart
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #93
Testing for Families of Distributions via the Fourier Transform
Alistair Stewart · Ilias Diakonikolas · Clement Canonne
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #94
High Dimensional Linear Regression using Lattice Basis Reduction
Ilias Zadik · David Gamarnik
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #95
$\ell_1$-regression with Heavy-tailed Distributions
Lijun Zhang · Zhi-Hua Zhou
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #96
Constant Regret, Generalized Mixability, and Mirror Descent
Zakaria Mhammedi · Robert Williamson
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #97
Stochastic Composite Mirror Descent: Optimal Bounds with High Probabilities
Yunwen Lei · Ke Tang
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #98
Uniform Convergence of Gradients for Non-Convex Learning and Optimization
Dylan Foster · Ayush Sekhari · Karthik Sridharan
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #99
Fast Rates of ERM and Stochastic Approximation: Adaptive to Error Bound Conditions
Mingrui Liu · Xiaoxuan Zhang · Lijun Zhang · Jing Rong · Tianbao Yang
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #100
Nearly tight sample complexity bounds for learning mixtures of Gaussians via sample compression schemes
Hassan Ashtiani · Shai Ben-David · Nick Harvey · Christopher Liaw · Abbas Mehrabian · Yaniv Plan
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #101
Early Stopping for Nonparametric Testing
Meimei Liu · Guang Cheng
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #102
Chaining Mutual Information and Tightening Generalization Bounds
Amir Asadi · Emmanuel Abbe · Sergio Verdu
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #103
Dimensionality Reduction has Quantifiable Imperfections: Two Geometric Bounds
Kry Lui · Gavin Weiguang Ding · Ruitong Huang · Robert McCann
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #104
Minimax Estimation of Neural Net Distance
Kaiyi Ji · Yingbin Liang
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #105
Quantifying Learning Guarantees for Convex but Inconsistent Surrogates
Kirill Struminsky · Simon Lacoste-Julien · Anton Osokin
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #106
Learning Signed Determinantal Point Processes through the Principal Minor Assignment Problem
Victor-Emmanuel Brunel
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #107
Data-dependent PAC-Bayes priors via differential privacy
Gintare Karolina Dziugaite · Daniel Roy
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #108
Computationally and statistically efficient learning of causal Bayes nets using path queries
Kevin Bello · Jean Honorio
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #109
PAC-Bayes Tree: weighted subtrees with guarantees
Tin D Nguyen · Samory Kpotufe
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #110
A loss framework for calibrated anomaly detection
Aditya Menon · Robert Williamson
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #111
On Oracle-Efficient PAC RL with Rich Observations
Christoph Dann · Nan Jiang · Akshay Krishnamurthy · Alekh Agarwal · John Langford · Robert Schapire
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #112
Adversarial Risk and Robustness: General Definitions and Implications for the Uniform Distribution
Dimitrios Diochnos · Saeed Mahloujifar · Mohammad Mahmoody
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #113
Learning from discriminative feature feedback
Sanjoy Dasgupta · Sivan Sabato · Nicholas Roberts · Akansha Dey
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #114
How to Start Training: The Effect of Initialization and Architecture
Boris Hanin · David Rolnick
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #115
Bilevel Distance Metric Learning for Robust Image Recognition
Jie Xu · Lei Luo · Cheng Deng · Heng Huang
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #116
Deep Non-Blind Deconvolution via Generalized Low-Rank Approximation
Wenqi Ren · Jiawei Zhang · Lin Ma · Jinshan Pan · Xiaochun Cao · Wangmeng Zuo · Wei Liu · Ming-Hsuan Yang
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #117
Unsupervised Depth Estimation, 3D Face Rotation and Replacement
Joel Ruben Antony Moniz · Christopher Beckham · Simon Rajotte · Sina Honari · Chris Pal
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #118
Neighbourhood Consensus Networks
Ignacio Rocco · Mircea Cimpoi · Relja Arandjelović · Akihiko Torii · Tomas Pajdla · Josef Sivic
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #119
Recurrent Transformer Networks for Semantic Correspondence
Seungryong Kim · Stephen Lin · SANG RYUL JEON · Dongbo Min · Kwanghoon Sohn
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #120
Deep Network for the Integrated 3D Sensing of Multiple People in Natural Images
Andrei Zanfir · Elisabeta Marinoiu · Mihai Zanfir · Alin-Ionut Popa · Cristian Sminchisescu
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #121
A Neural Compositional Paradigm for Image Captioning
Bo Dai · Sanja Fidler · Dahua Lin
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #122
Visual Memory for Robust Path Following
Ashish Kumar · Saurabh Gupta · David Fouhey · Sergey Levine · Jitendra Malik
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #123
Learning to Exploit Stability for 3D Scene Parsing
Yilun Du · Zhijian Liu · Hector Basevi · Ales Leonardis · Bill Freeman · Josh Tenenbaum · Jiajun Wu
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #124
Learning to Decompose and Disentangle Representations for Video Prediction
Jun-Ting Hsieh · Bingbin Liu · De-An Huang · Li Fei-Fei · Juan Carlos Niebles
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #125
Weakly Supervised Dense Event Captioning in Videos
Xuguang Duan · Wenbing Huang · Chuang Gan · Jingdong Wang · Wenwu Zhu · Junzhou Huang
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #126
Text-Adaptive Generative Adversarial Networks: Manipulating Images with Natural Language
Seonghyeon Nam · Yunji Kim · Seon Joo Kim
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #127
A Probabilistic U-Net for Segmentation of Ambiguous Images
Simon Kohl · Bernardino Romera-Paredes · Clemens Meyer · Jeffrey De Fauw · Joseph R. Ledsam · Klaus Maier-Hein · S. M. Ali Eslami · Danilo Jimenez Rezende · Olaf Ronneberger
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #128
Forward Modeling for Partial Observation Strategy Games - A StarCraft Defogger
Gabriel Synnaeve · Zeming Lin · Jonas Gehring · Dan Gant · Vegard Mella · Vasil Khalidov · Nicolas Carion · Nicolas Usunier
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #129
Adversarial Text Generation via Feature-Mover's Distance
Liqun Chen · Shuyang Dai · Chenyang Tao · Haichao Zhang · Zhe Gan · Dinghan Shen · Yizhe Zhang · Guoyin Wang · Ruiyi Zhang · Lawrence Carin
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #130
Virtual Class Enhanced Discriminative Embedding Learning
Binghui Chen · Weihong Deng · Haifeng Shen
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #131
Learning Pipelines with Limited Data and Domain Knowledge: A Study in Parsing Physics Problems
Mrinmaya Sachan · Kumar Avinava Dubey · Tom Mitchell · Dan Roth · Eric Xing
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #132
Pipe-SGD: A Decentralized Pipelined SGD Framework for Distributed Deep Net Training
Youjie Li · Mingchao Yu · Songze Li · Salman Avestimehr · Nam Sung Kim · Alexander Schwing
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #133
MULAN: A Blind and Off-Grid Method for Multichannel Echo Retrieval
Helena Peic Tukuljac · Antoine Deleforge · Remi Gribonval
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #134
Diminishing Returns Shape Constraints for Interpretability and Regularization
Maya Gupta · Dara Bahri · Andrew Cotter · Kevin Canini
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #135
Fairness Through Computationally-Bounded Awareness
Michael Kim · Omer Reingold · Guy Rothblum
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #136
On preserving non-discrimination when combining expert advice
Avrim Blum · Suriya Gunasekar · Thodoris Lykouris · Nati Srebro
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #137
Fairness Behind a Veil of Ignorance: A Welfare Analysis for Automated Decision Making
Hoda Heidari · Claudio Ferrari · Krishna Gummadi · Andreas Krause
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #138
Inequity aversion improves cooperation in intertemporal social dilemmas
Edward Hughes · Joel Leibo · Matthew Phillips · Karl Tuyls · Edgar Dueñez-Guzman · Antonio García Castañeda · Iain Dunning · Tina Zhu · Kevin McKee · Raphael Koster · Heather Roff · Thore Graepel
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #139
On Misinformation Containment in Online Social Networks
Amo Tong · Ding-Zhu Du · Weili Wu
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #140
Found Graph Data and Planted Vertex Covers
Austin Benson · Jon Kleinberg
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #141
Inferring Networks From Random Walk-Based Node Similarities
Jeremy Hoskins · Cameron Musco · Christopher Musco · Babis Tsourakakis
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #142
Fast Greedy MAP Inference for Determinantal Point Process to Improve Recommendation Diversity
Laming Chen · Guoxin Zhang · Eric Zhou
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #143
Unorganized Malicious Attacks Detection
Ming Pang · Wei Gao · Min Tao · Zhi-Hua Zhou
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #144
Scalable Robust Matrix Factorization with Nonconvex Loss
Quanming Yao · James Kwok
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #145
Differentially Private Robust Low-Rank Approximation
Raman Arora · Vladimir braverman · Jalaj Upadhyay
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #146
Differential Privacy for Growing Databases
Rachel Cummings · Sara Krehbiel · Kevin A Lai · Uthaipon Tantipongpipat
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #147
Efficient Neural Network Robustness Certification with General Activation Functions
Huan Zhang · Tsui-Wei Weng · Pin-Yu Chen · Cho-Jui Hsieh · Luca Daniel
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #148
Spectral Signatures in Backdoor Attacks
Brandon Tran · Jerry Li · Aleksander Madry
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #149
Constructing Unrestricted Adversarial Examples with Generative Models
Yang Song · Rui Shu · Nate Kushman · Stefano Ermon
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #150
Sublinear Time Low-Rank Approximation of Distance Matrices
Ainesh Bakshi · David Woodruff
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #151
Leveraged volume sampling for linear regression
Michal Derezinski · Manfred Warmuth · Daniel Hsu
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #152
Revisiting $(\epsilon, \gamma, \tau)$-similarity learning for domain adaptation
Sofiane Dhouib · Ievgen Redko
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #153
Differential Properties of Sinkhorn Approximation for Learning with Wasserstein Distance
Giulia Luise · Alessandro Rudi · Massimiliano Pontil · Carlo Ciliberto
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #154
Algorithms and Theory for Multiple-Source Adaptation
Judy Hoffman · Mehryar Mohri · Ningshan Zhang
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #155
Synthesize Policies for Transfer and Adaptation across Tasks and Environments
Hexiang Hu · Liyu Chen · Boqing Gong · Fei Sha
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #156
Acceleration through Optimistic No-Regret Dynamics
Jun-Kun Wang · Jacob Abernethy
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #157
Efficient Online Portfolio with Logarithmic Regret
Haipeng Luo · Chen-Yu Wei · Kai Zheng
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #158
Almost Optimal Algorithms for Linear Stochastic Bandits with Heavy-Tailed Payoffs
Han Shao · Xiaotian Yu · Irwin King · Michael Lyu
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #159
A Smoothed Analysis of the Greedy Algorithm for the Linear Contextual Bandit Problem
Sampath Kannan · Jamie Morgenstern · Aaron Roth · Bo Waggoner · Zhiwei Steven Wu
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #160
Exploration in Structured Reinforcement Learning
Jungseul Ok · Alexandre Proutiere · Damianos Tranos
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #161
Near Optimal Exploration-Exploitation in Non-Communicating Markov Decision Processes
Ronan Fruit · Matteo Pirotta · Alessandro Lazaric
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #162
A Block Coordinate Ascent Algorithm for Mean-Variance Optimization
Tengyang Xie · Bo Liu · Yangyang Xu · Mohammad Ghavamzadeh · Yinlam Chow · Daoming Lyu · Daesub Yoon
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #163
Learning Safe Policies with Expert Guidance
Jessie Huang · Fa Wu · Doina Precup · Yang Cai
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #164
M-Walk: Learning to Walk over Graphs using Monte Carlo Tree Search
Yelong Shen · Jianshu Chen · Po-Sen Huang · Yuqing Guo · Jianfeng Gao
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #165
Is Q-Learning Provably Efficient?
Chi Jin · Zeyuan Allen-Zhu · Sebastien Bubeck · Michael Jordan
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #166
Variational Inverse Control with Events: A General Framework for Data-Driven Reward Definition
Justin Fu · Avi Singh · Dibya Ghosh · Larry Yang · Sergey Levine
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #167
An Off-policy Policy Gradient Theorem Using Emphatic Weightings
Ehsan Imani · Eric Graves · Martha White
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #168
Near-Optimal Time and Sample Complexities for Solving Markov Decision Processes with a Generative Model
Aaron Sidford · Mengdi Wang · Xian Wu · Lin Yang · Yinyu Ye
Poster
Wed Dec 5th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #169
Monte-Carlo Tree Search for Constrained POMDPs
Jongmin Lee · Geon-hyeong Kim · Pascal Poupart · Kee-Eung Kim
Invited Talk
Wed Dec 5th 02:15 -- 03:05 PM @ Rooms 220 CDE
Investigations into the Human-AI Trust Phenomenon
Ayanna Howard
Break
Wed Dec 5th 03:05 -- 03:30 PM @
Coffee Break
Spotlight
Wed Dec 5th 03:30 -- 03:35 PM @ Room 220 CD
Breaking the Curse of Horizon: Infinite-Horizon Off-Policy Estimation
Qiang Liu · Lihong Li · Ziyang Tang · Dengyong Zhou
Spotlight
Wed Dec 5th 03:30 -- 03:35 PM @ Room 220 E
Dynamic Network Model from Partial Observations
Elahe Ghalebi · Baharan Mirzasoleiman · Radu Grosu · Jure Leskovec
Spotlight
Wed Dec 5th 03:30 -- 03:35 PM @ Room 517 CD
The Nearest Neighbor Information Estimator is Adaptively Near Minimax Rate-Optimal
Jiantao Jiao · Weihao Gao · Yanjun Han
Spotlight
Wed Dec 5th 03:35 -- 03:40 PM @ Room 220 CD
Graph Convolutional Policy Network for Goal-Directed Molecular Graph Generation
Jiaxuan You · Bowen Liu · Zhitao Ying · Vijay Pande · Jure Leskovec
Spotlight
Wed Dec 5th 03:35 -- 03:40 PM @ Room 220 E
Stochastic Nonparametric Event-Tensor Decomposition
Shandian Zhe · Yishuai Du
Spotlight
Wed Dec 5th 03:35 -- 03:40 PM @ Room 517 CD
Contextual Stochastic Block Models
Yash Deshpande · Subhabrata Sen · Andrea Montanari · Elchanan Mossel
Spotlight
Wed Dec 5th 03:40 -- 03:45 PM @ Room 220 CD
Memory Augmented Policy Optimization for Program Synthesis and Semantic Parsing
Chen Liang · Mohammad Norouzi · Jonathan Berant · Quoc V Le · Ni Lao
Spotlight
Wed Dec 5th 03:40 -- 03:45 PM @ Room 220 E
On GANs and GMMs
Eitan Richardson · Yair Weiss
Spotlight
Wed Dec 5th 03:40 -- 03:45 PM @ Room 517 CD
Entropy Rate Estimation for Markov Chains with Large State Space
Yanjun Han · Jiantao Jiao · Chuan-Zheng Lee · Tsachy Weissman · Yihong Wu · Tiancheng Yu
Spotlight
Wed Dec 5th 03:45 -- 03:50 PM @ Room 220 CD
Meta-Reinforcement Learning of Structured Exploration Strategies
Abhishek Gupta · Russell Mendonca · YuXuan Liu · Pieter Abbeel · Sergey Levine
Spotlight
Wed Dec 5th 03:45 -- 03:50 PM @ Room 220 E
GILBO: One Metric to Measure Them All
Alexander Alemi · Ian Fischer
Spotlight
Wed Dec 5th 03:45 -- 03:50 PM @ Room 517 CD
Blind Deconvolutional Phase Retrieval via Convex Programming
Ali Ahmed · Alireza Aghasi · Paul Hand
Oral
Wed Dec 5th 03:50 -- 04:05 PM @ Room 220 CD
Policy Optimization via Importance Sampling
Alberto Maria Metelli · Matteo Papini · Francesco Faccio · Marcello Restelli
Oral
Wed Dec 5th 03:50 -- 04:05 PM @ Room 220 E
Isolating Sources of Disentanglement in Variational Autoencoders
Tian Qi Chen · Xuechen Li · Roger Grosse · David Duvenaud
Oral
Wed Dec 5th 03:50 -- 04:05 PM @ Room 517 CD
Stochastic Cubic Regularization for Fast Nonconvex Optimization
Nilesh Tripuraneni · Mitchell Stern · Chi Jin · Jeffrey Regier · Michael Jordan
Spotlight
Wed Dec 5th 04:05 -- 04:10 PM @ Room 220 CD
A Bayesian Approach to Generative Adversarial Imitation Learning
Wonseok Jeon · Seokin Seo · Kee-Eung Kim
Spotlight
Wed Dec 5th 04:05 -- 04:10 PM @ Room 220 E
Sparse Covariance Modeling in High Dimensions with Gaussian Processes
Rui Li · Kishan KC · Feng Cui · Justin Domke · Anne Haake
Spotlight
Wed Dec 5th 04:05 -- 04:10 PM @ Room 517 CD
Stochastic Nested Variance Reduced Gradient Descent for Nonconvex Optimization
Dongruo Zhou · Pan Xu · Quanquan Gu
Spotlight
Wed Dec 5th 04:10 -- 04:15 PM @ Room 220 CD
Visual Reinforcement Learning with Imagined Goals
Ashvin Nair · Vitchyr Pong · Murtaza Dalal · Shikhar Bahl · Steven Lin · Sergey Levine
Spotlight
Wed Dec 5th 04:10 -- 04:15 PM @ Room 220 E
Efficient High Dimensional Bayesian Optimization with Additivity and Quadrature Fourier Features
Mojmir Mutny · Andreas Krause
Spotlight
Wed Dec 5th 04:10 -- 04:15 PM @ Room 517 CD
On the Local Minima of the Empirical Risk
Chi Jin · Lydia T. Liu · Rong Ge · Michael Jordan
Spotlight
Wed Dec 5th 04:15 -- 04:20 PM @ Room 220 CD
Randomized Prior Functions for Deep Reinforcement Learning
Ian Osband · John Aslanides · Albin Cassirer
Spotlight
Wed Dec 5th 04:15 -- 04:20 PM @ Room 220 E
Regret bounds for meta Bayesian optimization with an unknown Gaussian process prior
Zi Wang · Beomjoon Kim · Leslie Kaelbling
Spotlight
Wed Dec 5th 04:15 -- 04:20 PM @ Room 517 CD
How Much Restricted Isometry is Needed In Nonconvex Matrix Recovery?
Richard Zhang · Cedric Josz · Somayeh Sojoudi · Javad Lavaei
Spotlight
Wed Dec 5th 04:20 -- 04:25 PM @ Room 220 CD
Playing hard exploration games by watching YouTube
Yusuf Aytar · Tobias Pfaff · David Budden · Thomas Paine · Ziyu Wang · Nando de Freitas
Spotlight
Wed Dec 5th 04:20 -- 04:25 PM @ Room 220 E
Adversarially Robust Optimization with Gaussian Processes
Ilija Bogunovic · Jonathan Scarlett · Stefanie Jegelka · Volkan Cevher
Spotlight
Wed Dec 5th 04:20 -- 04:25 PM @ Room 517 CD
SPIDER: Near-Optimal Non-Convex Optimization via Stochastic Path-Integrated Differential Estimator
Cong Fang · Chris Junchi Li · Zhouchen Lin · Tong Zhang
Oral
Wed Dec 5th 04:25 -- 04:40 PM @ Room 220 CD
Recurrent World Models Facilitate Policy Evolution
David Ha · Jürgen Schmidhuber
Oral
Wed Dec 5th 04:25 -- 04:40 PM @ Room 220 E
Approximate Knowledge Compilation by Online Collapsed Importance Sampling
Tal Friedman · Guy Van den Broeck
Oral
Wed Dec 5th 04:25 -- 04:40 PM @ Room 517 CD
Analysis of Krylov Subspace Solutions of Regularized Non-Convex Quadratic Problems
Yair Carmon · John Duchi
Spotlight
Wed Dec 5th 04:40 -- 04:45 PM @ Room 220 CD
Reducing Network Agnostophobia
Akshay Raj Dhamija · Manuel Günther · Terrance Boult
Spotlight
Wed Dec 5th 04:40 -- 04:45 PM @ Room 220 E
DAGs with NO TEARS: Continuous Optimization for Structure Learning
Xun Zheng · Bryon Aragam · Pradeep Ravikumar · Eric Xing
Spotlight
Wed Dec 5th 04:40 -- 04:45 PM @ Room 517 CD
Natasha 2: Faster Non-Convex Optimization Than SGD
Zeyuan Allen-Zhu
Spotlight
Wed Dec 5th 04:45 -- 04:50 PM @ Room 220 CD
Life-Long Disentangled Representation Learning with Cross-Domain Latent Homologies
Alessandro Achille · Tom Eccles · Loic Matthey · Chris Burgess · Nicholas Watters · Alexander Lerchner · Irina Higgins
Spotlight
Wed Dec 5th 04:45 -- 04:50 PM @ Room 220 E
Proximal Graphical Event Models
Debarun Bhattacharjya · Dharmashankar Subramanian · Tian Gao
Spotlight
Wed Dec 5th 04:45 -- 04:50 PM @ Room 517 CD
Escaping Saddle Points in Constrained Optimization
Aryan Mokhtari · Asuman Ozdaglar · Ali Jadbabaie
Spotlight
Wed Dec 5th 04:50 -- 04:55 PM @ Room 220 CD
Geometrically Coupled Monte Carlo Sampling
Mark Rowland · Krzysztof Choromanski · François Chalus · Aldo Pacchiano · Tamas Sarlos · Richard E Turner · Adrian Weller
Spotlight
Wed Dec 5th 04:50 -- 04:55 PM @ Room 220 E
Heterogeneous Multi-output Gaussian Process Prediction
Pablo Moreno-Muñoz · Antonio Artés · Mauricio Álvarez
Spotlight
Wed Dec 5th 04:50 -- 04:55 PM @ Room 517 CD
On Coresets for Logistic Regression
Alexander Munteanu · Chris Schwiegelshohn · Christian Sohler · David Woodruff
Spotlight
Wed Dec 5th 04:55 -- 05:00 PM @ Room 220 CD
Scalable Laplacian K-modes
Imtiaz Ziko · Eric Granger · Ismail Ben Ayed
Spotlight
Wed Dec 5th 04:55 -- 05:00 PM @ Room 220 E
GPyTorch: Blackbox Matrix-Matrix Gaussian Process Inference with GPU Acceleration
Jacob Gardner · Geoff Pleiss · Kilian Weinberger · David Bindel · Andrew Wilson
Spotlight
Wed Dec 5th 04:55 -- 05:00 PM @ Room 517 CD
Legendre Decomposition for Tensors
Mahito Sugiyama · Hiroyuki Nakahara · Koji Tsuda
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #1
Equality of Opportunity in Classification: A Causal Approach
Junzhe Zhang · Elias Bareinboim
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #2
Confounding-Robust Policy Improvement
Nathan Kallus · Angela Zhou
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #3
Causal Discovery from Discrete Data using Hidden Compact Representation
Ruichu Cai · Jie Qiao · Kun Zhang · Zhenjie Zhang · Zhifeng Hao
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #4
Dirichlet belief networks for topic structure learning
He Zhao · Lan Du · Wray Buntine · Mingyuan Zhou
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #5
Approximate Knowledge Compilation by Online Collapsed Importance Sampling
Tal Friedman · Guy Van den Broeck
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #6
Proximal Graphical Event Models
Debarun Bhattacharjya · Dharmashankar Subramanian · Tian Gao
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #7
Dynamic Network Model from Partial Observations
Elahe Ghalebi · Baharan Mirzasoleiman · Radu Grosu · Jure Leskovec
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #8
HOGWILD!-Gibbs can be PanAccurate
Constantinos Daskalakis · Nishanth Dikkala · Siddhartha Jayanti
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #9
DAGs with NO TEARS: Continuous Optimization for Structure Learning
Xun Zheng · Bryon Aragam · Pradeep Ravikumar · Eric Xing
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #10
Mean Field for the Stochastic Blockmodel: Optimization Landscape and Convergence Issues
Soumendu Sundar Mukherjee · Purnamrita Sarkar · Y. X. Rachel Wang · Bowei Yan
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #11
Coupled Variational Bayes via Optimization Embedding
Bo Dai · Hanjun Dai · Niao He · Weiyang Liu · Zhen Liu · Jianshu Chen · Lin Xiao · Le Song
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #12
Stochastic Nonparametric Event-Tensor Decomposition
Shandian Zhe · Yishuai Du
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #13
GPyTorch: Blackbox Matrix-Matrix Gaussian Process Inference with GPU Acceleration
Jacob Gardner · Geoff Pleiss · Kilian Weinberger · David Bindel · Andrew Wilson
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #14
Heterogeneous Multi-output Gaussian Process Prediction
Pablo Moreno-Muñoz · Antonio Artés · Mauricio Álvarez
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #15
Probabilistic Matrix Factorization for Automated Machine Learning
Nicolo Fusi · Rishit Sheth · Melih Elibol
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #16
Stochastic Expectation Maximization with Variance Reduction
Jianfei Chen · Jun Zhu · Yee Whye Teh · Tong Zhang
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #17
Generative Neural Machine Translation
Harshil Shah · David Barber
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #18
Sparse Covariance Modeling in High Dimensions with Gaussian Processes
Rui Li · Kishan KC · Feng Cui · Justin Domke · Anne Haake
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #19
Variational Learning on Aggregate Outputs with Gaussian Processes
Ho Chung Law · Dino Sejdinovic · Ewan Cameron · Tim Lucas · Seth Flaxman · Katherine Battle · Kenji Fukumizu
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #20
Learning Invariances using the Marginal Likelihood
Mark van der Wilk · Matthias Bauer · ST John · James Hensman
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #21
Dirichlet-based Gaussian Processes for Large-scale Calibrated Classification
Dimitrios Milios · Raffaello Camoriano · Pietro Michiardi · Lorenzo Rosasco · Maurizio Filippone
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #22
Regret bounds for meta Bayesian optimization with an unknown Gaussian process prior
Zi Wang · Beomjoon Kim · Leslie Kaelbling
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #23
Efficient High Dimensional Bayesian Optimization with Additivity and Quadrature Fourier Features
Mojmir Mutny · Andreas Krause
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #24
Adversarially Robust Optimization with Gaussian Processes
Ilija Bogunovic · Jonathan Scarlett · Stefanie Jegelka · Volkan Cevher
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #25
Multi-objective Maximization of Monotone Submodular Functions with Cardinality Constraint
Rajan Udwani
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #26
Variational PDEs for Acceleration on Manifolds and Application to Diffeomorphisms
Ganesh Sundaramoorthi · Anthony Yezzi
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #27
Zeroth-order (Non)-Convex Stochastic Optimization via Conditional Gradient and Gradient Updates
Krishnakumar Balasubramanian · Saeed Ghadimi
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #28
Computing Higher Order Derivatives of Matrix and Tensor Expressions
Soeren Laue · Matthias Mitterreiter · Joachim Giesen
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #29
How SGD Selects the Global Minima in Over-parameterized Learning: A Dynamical Stability Perspective
Lei Wu · Chao Ma · Weinan E
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #30
The Effect of Network Width on the Performance of Large-batch Training
Lingjiao Chen · Hongyi Wang · Jinman Zhao · Dimitris Papailiopoulos · Paraschos Koutris
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #31
COLA: Decentralized Linear Learning
Lie He · An Bian · Martin Jaggi
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #32
Distributed Stochastic Optimization via Adaptive SGD
Ashok Cutkosky · Róbert Busa-Fekete
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #33
Non-Ergodic Alternating Proximal Augmented Lagrangian Algorithms with Optimal Rates
Quoc Tran Dinh
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #34
Breaking the Span Assumption Yields Fast Finite-Sum Minimization
Robert Hannah · Yanli Liu · Daniel O'Connor · Wotao Yin
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #35
Optimization for Approximate Submodularity
Yaron Singer · Avinatan Hassidim
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #36
Submodular Maximization via Gradient Ascent: The Case of Deep Submodular Functions
Wenruo Bai · William Stafford Noble · Jeff Bilmes
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #37
Maximizing Induced Cardinality Under a Determinantal Point Process
Jennifer Gillenwater · Alex Kulesza · Sergei Vassilvitskii · Zelda Mariet
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #38
Efficient Algorithms for Non-convex Isotonic Regression through Submodular Optimization
Francis Bach
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #39
Revisiting Decomposable Submodular Function Minimization with Incidence Relations
Pan Li · Olgica Milenkovic
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #40
Coordinate Descent with Bandit Sampling
Farnood Salehi · Patrick Thiran · Elisa Celis
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #41
Accelerated Stochastic Matrix Inversion: General Theory and Speeding up BFGS Rules for Faster Second-Order Optimization
Robert Gower · Filip Hanzely · Peter Richtarik · Sebastian Stich
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #42
Stochastic Cubic Regularization for Fast Nonconvex Optimization
Nilesh Tripuraneni · Mitchell Stern · Chi Jin · Jeffrey Regier · Michael Jordan
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #43
On the Local Minima of the Empirical Risk
Chi Jin · Lydia T. Liu · Rong Ge · Michael Jordan
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #44
Stochastic Nested Variance Reduced Gradient Descent for Nonconvex Optimization
Dongruo Zhou · Pan Xu · Quanquan Gu
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #45
NEON2: Finding Local Minima via First-Order Oracles
Zeyuan Allen-Zhu · Yuanzhi Li
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #46
How Much Restricted Isometry is Needed In Nonconvex Matrix Recovery?
Richard Zhang · Cedric Josz · Somayeh Sojoudi · Javad Lavaei
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #47
Escaping Saddle Points in Constrained Optimization
Aryan Mokhtari · Asuman Ozdaglar · Ali Jadbabaie
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #48
Analysis of Krylov Subspace Solutions of Regularized Non-Convex Quadratic Problems
Yair Carmon · John Duchi
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #49
SPIDER: Near-Optimal Non-Convex Optimization via Stochastic Path-Integrated Differential Estimator
Cong Fang · Chris Junchi Li · Zhouchen Lin · Tong Zhang
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #50
Natasha 2: Faster Non-Convex Optimization Than SGD
Zeyuan Allen-Zhu
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #51
Zeroth-Order Stochastic Variance Reduction for Nonconvex Optimization
Sijia Liu · Bhavya Kailkhura · Pin-Yu Chen · Paishun Ting · Shiyu Chang · Lisa Amini
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #52
Structured Local Minima in Sparse Blind Deconvolution
Yuqian Zhang · Han-wen Kuo · John Wright
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #53
Algorithmic Regularization in Learning Deep Homogeneous Models: Layers are Automatically Balanced
Simon Du · Wei Hu · Jason Lee
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #54
Are ResNets Provably Better than Linear Predictors?
Ohad Shamir
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #55
Adaptive Methods for Nonconvex Optimization
Manzil Zaheer · Sashank Reddi · Devendra Sachan · Satyen Kale · Sanjiv Kumar
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #56
Alternating optimization of decision trees, with application to learning sparse oblique trees
Miguel A. Carreira-Perpinan · Pooya Tavallali
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #57
GILBO: One Metric to Measure Them All
Alexander Alemi · Ian Fischer
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #58
Isolating Sources of Disentanglement in Variational Autoencoders
Tian Qi Chen · Xuechen Li · Roger Grosse · David Duvenaud
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #59
On GANs and GMMs
Eitan Richardson · Yair Weiss
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #60
Assessing Generative Models via Precision and Recall
Mehdi S. M. Sajjadi · Olivier Bachem · Mario Lucic · Olivier Bousquet · Sylvain Gelly
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #61
Gather-Excite: Exploiting Feature Context in Convolutional Neural Networks
Jie Hu · Li Shen · Samuel Albanie · Gang Sun · Andrea Vedaldi
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #62
Uncertainty-Aware Attention for Reliable Interpretation and Prediction
Jay Heo · Hae Beom Lee · Saehoon Kim · Juho Lee · Kwang Joon Kim · Eunho Yang · Sung Ju Hwang
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #63
Forecasting Treatment Responses Over Time Using Recurrent Marginal Structural Networks
Bryan Lim · Ahmed M. Alaa · Mihaela van der Schaar
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #64
Backpropagation with Callbacks: Foundations for Efficient and Expressive Differentiable Programming
Fei Wang · James Decker · Xilun Wu · Gregory Essertel · Tiark Rompf
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #65
Recurrent World Models Facilitate Policy Evolution
David Ha · Jürgen Schmidhuber
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #66
Long short-term memory and Learning-to-learn in networks of spiking neurons
Guillaume Bellec · Darjan Salaj · Anand Subramoney · Robert Legenstein · Wolfgang Maass
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #67
Distributed Weight Consolidation: A Brain Segmentation Case Study
Patrick McClure · Charles Zheng · Jakub Kaczmarzyk · John Rogers-Lee · Satra Ghosh · Dylan Nielson · Peter A Bandettini · Francisco Pereira
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #68
Learning to Play With Intrinsically-Motivated, Self-Aware Agents
Nick Haber · Damian Mrowca · Stephanie Wang · Li Fei-Fei · Daniel Yamins
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #69
Gradient Descent for Spiking Neural Networks
Dongsung Huh · Terrence J Sejnowski
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #70
Demystifying excessively volatile human learning: A Bayesian persistent prior and a neural approximation
Chaitanya Ryali · Gautam Reddy · Angela J Yu
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #71
Temporal alignment and latent Gaussian process factor inference in population spike trains
Lea Duncker · Maneesh Sahani
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #72
Information-based Adaptive Stimulus Selection to Optimize Communication Efficiency in Brain-Computer Interfaces
Boyla Mainsah · Dmitry Kalika · Leslie Collins · Siyuan Liu · Chandra Throckmorton
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #73
Model-based targeted dimensionality reduction for neuronal population data
Mikio Aoi · Jonathan W Pillow
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #74
Objective and efficient inference for couplings in neuronal networks
Yu Terada · Tomoyuki Obuchi · Takuya Isomura · Yoshiyuki Kabashima
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #75
The emergence of multiple retinal cell types through efficient coding of natural movies
Samuel Ocko · Jack Lindsey · Surya Ganguli · Stephane Deny
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #76
Benefits of over-parameterization with EM
Ji Xu · Daniel Hsu · Arian Maleki
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #77
On Coresets for Logistic Regression
Alexander Munteanu · Chris Schwiegelshohn · Christian Sohler · David Woodruff
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #78
On Learning Markov Chains
Yi HAO · Alon Orlitsky · Venkatadheeraj Pichapati
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #79
Contextual Stochastic Block Models
Yash Deshpande · Subhabrata Sen · Andrea Montanari · Elchanan Mossel
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #80
Estimators for Multivariate Information Measures in General Probability Spaces
Arman Rahimzamani · Himanshu Asnani · Pramod Viswanath · Sreeram Kannan
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #81
Blind Deconvolutional Phase Retrieval via Convex Programming
Ali Ahmed · Alireza Aghasi · Paul Hand
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #82
Entropy Rate Estimation for Markov Chains with Large State Space
Yanjun Han · Jiantao Jiao · Chuan-Zheng Lee · Tsachy Weissman · Yihong Wu · Tiancheng Yu
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #83
Bandit Learning in Concave N-Person Games
Mario Bravo · David Leslie · Panayotis Mertikopoulos
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #84
Depth-Limited Solving for Imperfect-Information Games
Noam Brown · Tuomas Sandholm · Brandon Amos
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #85
The Physical Systems Behind Optimization Algorithms
Lin Yang · Raman Arora · Vladimir braverman · Tuo Zhao
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #86
The Nearest Neighbor Information Estimator is Adaptively Near Minimax Rate-Optimal
Jiantao Jiao · Weihao Gao · Yanjun Han
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #87
Robust Learning of Fixed-Structure Bayesian Networks
Yu Cheng · Ilias Diakonikolas · Daniel Kane · Alistair Stewart
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #88
Information-theoretic Limits for Community Detection in Network Models
Chuyang Ke · Jean Honorio
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #89
Generalizing Graph Matching beyond Quadratic Assignment Model
Tianshu Yu · Junchi Yan · Yilin Wang · Wei Liu · baoxin Li
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #90
Improving Simple Models with Confidence Profiles
Amit Dhurandhar · Karthikeyan Shanmugam · Ronny Luss · Peder A Olsen
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #91
Online Learning with an Unknown Fairness Metric
Stephen Gillen · Christopher Jung · Michael Kearns · Aaron Roth
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #92
Legendre Decomposition for Tensors
Mahito Sugiyama · Hiroyuki Nakahara · Koji Tsuda
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #93
The Price of Privacy for Low-rank Factorization
Jalaj Upadhyay
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #94
Empirical Risk Minimization in Non-interactive Local Differential Privacy Revisited
Di Wang · Marco Gaboardi · Jinhui Xu
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #95
Differentially Private Change-Point Detection
Sara Krehbiel · Rachel Cummings · Wanrong Zhang · Yajun Mei · Rui Tuo
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #96
Scalable Laplacian K-modes
Imtiaz Ziko · Eric Granger · Ismail Ben Ayed
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #97
Geometrically Coupled Monte Carlo Sampling
Mark Rowland · Krzysztof Choromanski · François Chalus · Aldo Pacchiano · Tamas Sarlos · Richard E Turner · Adrian Weller
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #98
Continuous-time Value Function Approximation in Reproducing Kernel Hilbert Spaces
Motoya Ohnishi · Masahiro Yukawa · Mikael Johansson · Masashi Sugiyama
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #99
Faster Online Learning of Optimal Threshold for Consistent F-measure Optimization
Xiaoxuan Zhang · Mingrui Liu · Xun Zhou · Tianbao Yang
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #100
Reducing Network Agnostophobia
Akshay Raj Dhamija · Manuel Günther · Terrance Boult
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #101
Life-Long Disentangled Representation Learning with Cross-Domain Latent Homologies
Alessandro Achille · Tom Eccles · Loic Matthey · Chris Burgess · Nicholas Watters · Alexander Lerchner · Irina Higgins
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #102
Near-Optimal Policies for Dynamic Multinomial Logit Assortment Selection Models
Yining Wang · Xi Chen · Yuan Zhou
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #103
The Everlasting Database: Statistical Validity at a Fair Price
Blake Woodworth · Vitaly Feldman · Saharon Rosset · Nati Srebro
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #104
Scalar Posterior Sampling with Applications
Georgios Theocharous · Zheng Wen · Yasin Abbasi · Nikos Vlassis
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #105
Iterative Value-Aware Model Learning
Amir-massoud Farahmand
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #106
A Lyapunov-based Approach to Safe Reinforcement Learning
Yinlam Chow · Ofir Nachum · Edgar Duenez-Guzman · Mohammad Ghavamzadeh
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #107
Temporal Regularization for Markov Decision Process
Pierre Thodoroff · Audrey Durand · Joelle Pineau · Doina Precup
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #108
Maximum Causal Tsallis Entropy Imitation Learning
Kyungjae Lee · Sungjoon Choi · Songhwai Oh
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #109
Policy Optimization via Importance Sampling
Alberto Maria Metelli · Matteo Papini · Francesco Faccio · Marcello Restelli
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #110
Reinforcement Learning of Theorem Proving
Cezary Kaliszyk · Josef Urban · Henryk Michalewski · Miroslav Olšák
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #111
Simple random search of static linear policies is competitive for reinforcement learning
Horia Mania · Aurelia Guy · Benjamin Recht
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #112
Meta-Gradient Reinforcement Learning
Zhongwen Xu · Hado van Hasselt · David Silver
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #113
Reinforcement Learning for Solving the Vehicle Routing Problem
MohammadReza Nazari · Afshin Oroojlooy · Lawrence Snyder · Martin Takac
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #114
Learn What Not to Learn: Action Elimination with Deep Reinforcement Learning
Tom Zahavy · Matan Haroush · Nadav Merlis · Daniel J Mankowitz · Shie Mannor
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #115
REFUEL: Exploring Sparse Features in Deep Reinforcement Learning for Fast Disease Diagnosis
Yu-Shao Peng · Kai-Fu Tang · Hsuan-Tien Lin · Edward Chang
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #116
Learning Plannable Representations with Causal InfoGAN
Thanard Kurutach · Aviv Tamar · Ge Yang · Stuart Russell · Pieter Abbeel
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #117
Improving Exploration in Evolution Strategies for Deep Reinforcement Learning via a Population of Novelty-Seeking Agents
Edoardo Conti · Vashisht Madhavan · Felipe Petroski Such · Joel Lehman · Kenneth Stanley · Jeff Clune
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #118
Transfer of Deep Reactive Policies for MDP Planning
Aniket (Nick) Bajpai · Sankalp Garg · Mausam
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #119
Q-learning with Nearest Neighbors
Devavrat Shah · Qiaomin Xie
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #120
Distributed Multitask Reinforcement Learning with Quadratic Convergence
Rasul Tutunov · Dongho Kim · Haitham Bou Ammar
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #121
Breaking the Curse of Horizon: Infinite-Horizon Off-Policy Estimation
Qiang Liu · Lihong Li · Ziyang Tang · Dengyong Zhou
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #122
Constrained Cross-Entropy Method for Safe Reinforcement Learning
Min Wen · Ufuk Topcu
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #123
Representation Balancing MDPs for Off-policy Policy Evaluation
Yao Liu · Omer Gottesman · Aniruddh Raghu · Matthieu Komorowski · Aldo A Faisal · Finale Doshi-Velez · Emma Brunskill
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #124
Dual Policy Iteration
Wen Sun · Geoffrey Gordon · Byron Boots · J. Bagnell
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #125
Occam's razor is insufficient to infer the preferences of irrational agents
Stuart Armstrong · Sören Mindermann
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #126
Transfer of Value Functions via Variational Methods
Andrea Tirinzoni · Rafael Rodriguez Sanchez · Marcello Restelli
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #127
Reinforcement Learning with Multiple Experts: A Bayesian Model Combination Approach
Michael Gimelfarb · Scott Sanner · Chi-Guhn Lee
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #128
Online Robust Policy Learning in the Presence of Unknown Adversaries
Aaron Havens · Zhanhong Jiang · Soumik Sarkar
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #129
A Bayesian Approach to Generative Adversarial Imitation Learning
Wonseok Jeon · Seokin Seo · Kee-Eung Kim
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #130
Verifiable Reinforcement Learning via Policy Extraction
Osbert Bastani · Yewen Pu · Armando Solar-Lezama
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #131
Deep Reinforcement Learning of Marked Temporal Point Processes
Utkarsh Upadhyay · Abir De · Manuel Gomez Rodriguez
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #132
On Learning Intrinsic Rewards for Policy Gradient Methods
Zeyu Zheng · Junhyuk Oh · Satinder Singh
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #133
Evolution-Guided Policy Gradient in Reinforcement Learning
Shauharda Khadka · Kagan Tumer
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #134
Meta-Reinforcement Learning of Structured Exploration Strategies
Abhishek Gupta · Russell Mendonca · YuXuan Liu · Pieter Abbeel · Sergey Levine
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #135
Diversity-Driven Exploration Strategy for Deep Reinforcement Learning
Zhang-Wei Hong · Tzu-Yun Shann · Shih-Yang Su · Yi-Hsiang Chang · Tsu-Jui Fu · Chun-Yi Lee
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #136
Genetic-Gated Networks for Deep Reinforcement Learning
Simyung Chang · John Yang · Jaeseok Choi · Nojun Kwak
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #137
Memory Augmented Policy Optimization for Program Synthesis and Semantic Parsing
Chen Liang · Mohammad Norouzi · Jonathan Berant · Quoc V Le · Ni Lao
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #138
Hardware Conditioned Policies for Multi-Robot Transfer Learning
Tao Chen · Adithyavairavan Murali · Abhinav Gupta
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #139
Reward learning from human preferences and demonstrations in Atari
Jan Leike · Borja Ibarz · Dario Amodei · Geoffrey Irving · Shane Legg
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #140
Graph Convolutional Policy Network for Goal-Directed Molecular Graph Generation
Jiaxuan You · Bowen Liu · Zhitao Ying · Vijay Pande · Jure Leskovec
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #141
Visual Reinforcement Learning with Imagined Goals
Ashvin Nair · Vitchyr Pong · Murtaza Dalal · Shikhar Bahl · Steven Lin · Sergey Levine
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #142
Playing hard exploration games by watching YouTube
Yusuf Aytar · Tobias Pfaff · David Budden · Thomas Paine · Ziyu Wang · Nando de Freitas
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #143
Unsupervised Video Object Segmentation for Deep Reinforcement Learning
Vikash Goel · Jameson Weng · Pascal Poupart
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #144
Learning to Navigate in Cities Without a Map
Piotr Mirowski · Matt Grimes · Mateusz Malinowski · Karl Moritz Hermann · Keith Anderson · Denis Teplyashin · Karen Simonyan · koray kavukcuoglu · Andrew Zisserman · Raia Hadsell
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #145
Learning Abstract Options
Matthew Riemer · Miao Liu · Gerald Tesauro
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #146
Object-Oriented Dynamics Predictor
Guangxiang Zhu · Zhiao Huang · Chongjie Zhang
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #147
A Deep Bayesian Policy Reuse Approach Against Non-Stationary Agents
YAN ZHENG · Zhaopeng Meng · Jianye Hao · Zongzhang Zhang · Tianpei Yang · Changjie Fan
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #148
Learning Attentional Communication for Multi-Agent Cooperation
Jiechuan Jiang · Zongqing Lu
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #149
Deep Dynamical Modeling and Control of Unsteady Fluid Flows
Jeremy Morton · Antony Jameson · Mykel J Kochenderfer · Freddie Witherden
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #150
Adaptive Skip Intervals: Temporal Abstraction for Recurrent Dynamical Models
Alexander Neitz · Giambattista Parascandolo · Stefan Bauer · Bernhard Schölkopf
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #151
Zero-Shot Transfer with Deictic Object-Oriented Representation in Reinforcement Learning
Ofir Marom · Benjamin Rosman
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #152
Total stochastic gradient algorithms and applications in reinforcement learning
Paavo Parmas
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #153
Fighting Boredom in Recommender Systems with Linear Reinforcement Learning
Romain WARLOP · Alessandro Lazaric · Jérémie Mary
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #154
Randomized Prior Functions for Deep Reinforcement Learning
Ian Osband · John Aslanides · Albin Cassirer
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #155
Scalable Coordinated Exploration in Concurrent Reinforcement Learning
Maria Dimakopoulou · Ian Osband · Benjamin Van Roy
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #156
Context-dependent upper-confidence bounds for directed exploration
Raksha Kumaraswamy · Matthew Schlegel · Adam White · Martha White
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #157
Multi-Agent Generative Adversarial Imitation Learning
Jiaming Song · Hongyu Ren · Dorsa Sadigh · Stefano Ermon
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #158
Actor-Critic Policy Optimization in Partially Observable Multiagent Environments
Sriram Srinivasan · Marc Lanctot · Vinicius Zambaldi · Julien Perolat · Karl Tuyls · Remi Munos · Michael Bowling
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #159
Learning to Share and Hide Intentions using Information Regularization
Daniel Strouse · Max Kleiman-Weiner · Josh Tenenbaum · Matt Botvinick · David Schwab
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #160
Credit Assignment For Collective Multiagent RL With Global Rewards
Duc Thien Nguyen · Akshat Kumar · Hoong Chuin Lau
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #161
Multi-Agent Reinforcement Learning via Double Averaging Primal-Dual Optimization
Hoi-To Wai · Zhuoran Yang · Princeton Zhaoran Wang · Mingyi Hong
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #162
Learning Others' Intentional Models in Multi-Agent Settings Using Interactive POMDPs
Yanlin Han · Piotr Gmytrasiewicz
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #163
Bayesian Control of Large MDPs with Unknown Dynamics in Data-Poor Environments
Mahdi Imani · Seyede Fatemeh Ghoreishi · Ulisses M. Braga-Neto
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #164
Negotiable Reinforcement Learning for Pareto Optimal Sequential Decision-Making
Nishant Desai · Andrew Critch · Stuart J Russell
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #165
rho-POMDPs have Lipschitz-Continuous epsilon-Optimal Value Functions
Mathieu Fehr · Olivier Buffet · Vincent Thomas · Jilles Dibangoye
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #166
Learning Task Specifications from Demonstrations
Marcell Vazquez-Chanlatte · Susmit Jha · Ashish Tiwari · Mark Ho · Sanjit Seshia
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #167
Teaching Inverse Reinforcement Learners via Features and Demonstrations
Luis Haug · Sebastian Tschiatschek · Adish Singla
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #168
Single-Agent Policy Tree Search With Guarantees
Laurent Orseau · Levi Lelis · Tor Lattimore · Theophane Weber
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #169
From Stochastic Planning to Marginal MAP
Hao Cui · Radu Marinescu · Roni Khardon
Poster
Wed Dec 5th 05:00 -- 07:00 PM @ Room 210 & 230 AB #170
Dual Principal Component Pursuit: Improved Analysis and Efficient Algorithms
Zhihui Zhu · Yifan Wang · Daniel Robinson · Daniel Naiman · Rene Vidal · Manolis Tsakiris
Invited Talk (Breiman Lecture)
Thu Dec 6th 08:30 -- 09:20 AM @ Rooms 220 CDE
Making Algorithms Trustworthy: What Can Statistical Science Contribute to Transparency, Explanation and Validation?
David Spiegelhalter
Break
Thu Dec 6th 09:20 -- 09:45 AM @
Coffee Break
Spotlight
Thu Dec 6th 09:45 -- 09:50 AM @ Room 220 CD
Learning with SGD and Random Features
Luigi Carratino · Alessandro Rudi · Lorenzo Rosasco
Spotlight
Thu Dec 6th 09:45 -- 09:50 AM @ Room 220 E
Graphical model inference: Sequential Monte Carlo meets deterministic approximations
Fredrik Lindsten · Jouni Helske · Matti Vihola
Spotlight
Thu Dec 6th 09:45 -- 09:50 AM @ Room 517 CD
Boolean Decision Rules via Column Generation
Sanjeeb Dash · Oktay Gunluk · Dennis Wei
Spotlight
Thu Dec 6th 09:50 -- 09:55 AM @ Room 220 CD
KONG: Kernels for ordered-neighborhood graphs
Moez Draief · Konstantin Kutzkov · Kevin Scaman · Milan Vojnovic
Spotlight
Thu Dec 6th 09:50 -- 09:55 AM @ Room 220 E
Boosting Black Box Variational Inference
Francesco Locatello · Gideon Dresdner · Rajiv Khanna · Isabel Valera · Gunnar Raetsch
Spotlight
Thu Dec 6th 09:50 -- 09:55 AM @ Room 517 CD
Fast greedy algorithms for dictionary selection with generalized sparsity constraints
Kaito Fujii · Tasuku Soma
Spotlight
Thu Dec 6th 09:55 -- 10:00 AM @ Room 220 CD
Quadrature-based features for kernel approximation
Marina Munkhoeva · Yermek Kapushev · Evgeny Burnaev · Ivan Oseledets
Spotlight
Thu Dec 6th 09:55 -- 10:00 AM @ Room 220 E
Discretely Relaxing Continuous Variables for tractable Variational Inference
Trefor Evans · Prasanth Nair
Spotlight
Thu Dec 6th 09:55 -- 10:00 AM @ Room 517 CD
Distributed $k$-Clustering for Data with Heavy Noise
Shi Li · Xiangyu Guo
Spotlight
Thu Dec 6th 10:00 -- 10:05 AM @ Room 220 CD
Statistical and Computational Trade-Offs in Kernel K-Means
Daniele Calandriello · Lorenzo Rosasco
Spotlight
Thu Dec 6th 10:00 -- 10:05 AM @ Room 220 E
Implicit Reparameterization Gradients
Mikhail Figurnov · Shakir Mohamed · Andriy Mnih
Spotlight
Thu Dec 6th 10:00 -- 10:05 AM @ Room 517 CD
Do Less, Get More: Streaming Submodular Maximization with Subsampling
Moran Feldman · Amin Karbasi · Ehsan Kazemi
Oral
Thu Dec 6th 10:05 -- 10:20 AM @ Room 220 CD
Integrated accounts of behavioral and neuroimaging data using flexible recurrent neural network models
Amir Dezfouli · Richard Morris · Fabio Ramos · Peter Dayan · Bernard Balleine
Oral
Thu Dec 6th 10:05 -- 10:20 AM @ Room 220 E
Variational Inference with Tail-adaptive f-Divergence
Dilin Wang · Hao Liu · Qiang Liu
Oral
Thu Dec 6th 10:05 -- 10:20 AM @ Room 517 CD
Optimal Algorithms for Continuous Non-monotone Submodular and DR-Submodular Maximization
Rad Niazadeh · Tim Roughgarden · Joshua Wang
Spotlight
Thu Dec 6th 10:20 -- 10:25 AM @ Room 220 CD
Why Is My Classifier Discriminatory?
Irene Chen · Fredrik Johansson · David Sontag
Spotlight
Thu Dec 6th 10:20 -- 10:25 AM @ Room 220 E
Mirrored Langevin Dynamics
Ya-Ping Hsieh · Ali Kavis · Paul Rolland · Volkan Cevher
Spotlight
Thu Dec 6th 10:20 -- 10:25 AM @ Room 517 CD
Overlapping Clustering Models, and One (class) SVM to Bind Them All
Xueyu Mao · Purnamrita Sarkar · Deepayan Chakrabarti
Spotlight
Thu Dec 6th 10:25 -- 10:30 AM @ Room 220 CD
Human-in-the-Loop Interpretability Prior
Isaac Lage · Andrew Ross · Samuel J Gershman · Been Kim · Finale Doshi-Velez
Spotlight
Thu Dec 6th 10:25 -- 10:30 AM @ Room 220 E
Global Convergence of Langevin Dynamics Based Algorithms for Nonconvex Optimization
Pan Xu · Jinghui Chen · Difan Zou · Quanquan Gu
Spotlight
Thu Dec 6th 10:25 -- 10:30 AM @ Room 517 CD
Removing the Feature Correlation Effect of Multiplicative Noise
Zijun Zhang · Yining Zhang · Zongpeng Li
Spotlight
Thu Dec 6th 10:30 -- 10:35 AM @ Room 220 CD
Link Prediction Based on Graph Neural Networks
Muhan Zhang · Yixin Chen
Spotlight
Thu Dec 6th 10:30 -- 10:35 AM @ Room 220 E
Identification and Estimation of Causal Effects from Dependent Data
Eli Sherman · Ilya Shpitser
Spotlight
Thu Dec 6th 10:30 -- 10:35 AM @ Room 517 CD
Connectionist Temporal Classification with Maximum Entropy Regularization
Hu Liu · Sheng Jin · Changshui Zhang
Spotlight
Thu Dec 6th 10:35 -- 10:40 AM @ Room 220 CD
Realistic Evaluation of Deep Semi-Supervised Learning Algorithms
Avital Oliver · Augustus Odena · Colin A Raffel · Ekin Dogus Cubuk · Ian Goodfellow
Spotlight
Thu Dec 6th 10:35 -- 10:40 AM @ Room 220 E
Causal Inference via Kernel Deviance Measures
Jovana Mitrovic · Dino Sejdinovic · Yee Whye Teh
Spotlight
Thu Dec 6th 10:35 -- 10:40 AM @ Room 517 CD
Entropy and mutual information in models of deep neural networks
Marylou Gabrié · Andre Manoel · Clément Luneau · jean barbier · Nicolas Macris · Florent Krzakala · Lenka Zdeborová
Spotlight
Thu Dec 6th 10:40 -- 10:45 AM @ Room 220 CD
Automatic differentiation in ML: Where we are and where we should be going
Bart van Merrienboer · Olivier Breuleux · Arnaud Bergeron · Pascal Lamblin
Spotlight
Thu Dec 6th 10:40 -- 10:45 AM @ Room 220 E
Removing Hidden Confounding by Experimental Grounding
Nathan Kallus · Aahlad Manas Puli · Uri Shalit
Spotlight
Thu Dec 6th 10:40 -- 10:45 AM @ Room 517 CD
The committee machine: Computational to statistical gaps in learning a two-layers neural network
Benjamin Aubin · Antoine Maillard · jean barbier · Florent Krzakala · Nicolas Macris · Lenka Zdeborová
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #1
Experimental Design for Cost-Aware Learning of Causal Graphs
Erik Lindgren · Murat Kocaoglu · Alexandros Dimakis · Sriram Vishwanath
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #2
Removing Hidden Confounding by Experimental Grounding
Nathan Kallus · Aahlad Manas Puli · Uri Shalit
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #3
Domain Adaptation by Using Causal Inference to Predict Invariant Conditional Distributions
Sara Magliacane · Thijs van Ommen · Tom Claassen · Stephan Bongers · Philip Versteeg · Joris M Mooij
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #4
Structural Causal Bandits: Where to Intervene?
Sanghack Lee · Elias Bareinboim
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #5
Uplift Modeling from Separate Labels
Ikko Yamane · Florian Yger · Jamal Atif · Masashi Sugiyama
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #6
Causal Inference with Noisy and Missing Covariates via Matrix Factorization
Nathan Kallus · Xiaojie Mao · Madeleine Udell
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #7
Fast Estimation of Causal Interactions using Wold Processes
Flavio Figueiredo · Guilherme Resende Borges · Pedro O.S. Vaz de Melo · Renato Assunção
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #8
Learning and Testing Causal Models with Interventions
Jayadev Acharya · Arnab Bhattacharyya · Constantinos Daskalakis · Saravanan Kandasamy
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #9
Causal Inference via Kernel Deviance Measures
Jovana Mitrovic · Dino Sejdinovic · Yee Whye Teh
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #10
Multi-domain Causal Structure Learning in Linear Systems
AmirEmad Ghassami · Negar Kiyavash · Biwei Huang · Kun Zhang
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #11
Causal Inference and Mechanism Clustering of A Mixture of Additive Noise Models
Shoubo Hu · Zhitang Chen · Vahid Partovi Nia · Laiwan CHAN · Yanhui Geng
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #12
Direct Estimation of Differences in Causal Graphs
Yuhao Wang · Chandler Squires · Anastasiya Belyaeva · Caroline Uhler
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #13
Identification and Estimation of Causal Effects from Dependent Data
Eli Sherman · Ilya Shpitser
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #14
Multilingual Anchoring: Interactive Topic Modeling and Alignment Across Languages
Michelle Yuan · Benjamin Van Durme · Jordan Ying
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #15
Submodular Field Grammars: Representation, Inference, and Application to Image Parsing
Abram L Friesen · Pedro Domingos
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #16
Autoconj: Recognizing and Exploiting Conjugacy Without a Domain-Specific Language
Matthew D. Hoffman · Matthew Johnson · Dustin Tran
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #17
Distributionally Robust Graphical Models
Rizal Fathony · Ashkan Rezaei · Mohammad Ali Bashiri · Xinhua Zhang · Brian Ziebart
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #18
Flexible and accurate inference and learning for deep generative models
Eszter Vértes · Maneesh Sahani
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #19
Provable Gaussian Embedding with One Observation
Ming Yu · Zhuoran Yang · Tuo Zhao · Mladen Kolar · Princeton Zhaoran Wang
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #20
Learning and Inference in Hilbert Space with Quantum Graphical Models
Siddarth Srinivasan · Carlton Downey · Byron Boots
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #21
Multi-value Rule Sets for Interpretable Classification with Feature-Efficient Representations
Tong Wang
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #22
Nonparametric Bayesian Lomax delegate racing for survival analysis with competing risks
Quan Zhang · Mingyuan Zhou
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #23
Theoretical guarantees for EM under misspecified Gaussian mixture models
Raaz Dwivedi · nhật Hồ · Koulik Khamaru · Martin Wainwright · Michael Jordan
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #24
Nonparametric learning from Bayesian models with randomized objective functions
Simon Lyddon · Stephen Walker · Chris C Holmes
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #25
Rectangular Bounding Process
Xuhui Fan · Bin Li · Scott SIsson
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #26
A Bayesian Nonparametric View on Count-Min Sketch
Diana Cai · Michael Mitzenmacher · Ryan Adams
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #27
Communication Efficient Parallel Algorithms for Optimization on Manifolds
Bayan Saparbayeva · Michael Zhang · Lizhen Lin
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #28
Lifted Weighted Mini-Bucket
Nicholas Gallo · Alexander Ihler
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #29
Cluster Variational Approximations for Structure Learning of Continuous-Time Bayesian Networks from Incomplete Data
Dominik Linzner · Heinz Koeppl
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #30
Faithful Inversion of Generative Models for Effective Amortized Inference
Stefan Webb · Adam Golinski · Rob Zinkov · Siddharth Narayanaswamy · Tom Rainforth · Yee Whye Teh · Frank Wood
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #31
A Stein variational Newton method
Gianluca Detommaso · Tiangang Cui · Youssef Marzouk · Alessio Spantini · Robert Scheichl
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #32
Reparameterization Gradient for Non-differentiable Models
Wonyeol Lee · Hangyeol Yu · Hongseok Yang
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #33
Implicit Reparameterization Gradients
Mikhail Figurnov · Shakir Mohamed · Andriy Mnih
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #34
SLANG: Fast Structured Covariance Approximations for Bayesian Deep Learning with Natural Gradient
Aaron Mishkin · Frederik Kunstner · Didrik Nielsen · Mark Schmidt · Mohammad Emtiyaz Khan
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #35
Wasserstein Variational Inference
Luca Ambrogioni · Umut Güçlü · Yağmur Güçlütürk · Max Hinne · Marcel A. J. van Gerven · Eric Maris
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #36
Adaptive Path-Integral Autoencoders: Representation Learning and Planning for Dynamical Systems
Jung-Su Ha · Young-Jin Park · Hyeok-Joo Chae · Soon-Seo Park · Han-Lim Choi
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #37
Variational Inference with Tail-adaptive f-Divergence
Dilin Wang · Hao Liu · Qiang Liu
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #38
Boosting Black Box Variational Inference
Francesco Locatello · Gideon Dresdner · Rajiv Khanna · Isabel Valera · Gunnar Raetsch
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #39
Discretely Relaxing Continuous Variables for tractable Variational Inference
Trefor Evans · Prasanth Nair
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #40
Using Large Ensembles of Control Variates for Variational Inference
Tomas Geffner · Justin Domke
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #41
The promises and pitfalls of Stochastic Gradient Langevin Dynamics
Nicolas Brosse · Alain Durmus · Eric Moulines
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #42
Large-Scale Stochastic Sampling from the Probability Simplex
Jack Baker · Paul Fearnhead · Emily Fox · Christopher Nemeth
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #43
Mirrored Langevin Dynamics
Ya-Ping Hsieh · Ali Kavis · Paul Rolland · Volkan Cevher
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #44
Thermostat-assisted continuously-tempered Hamiltonian Monte Carlo for Bayesian learning
Rui Luo · Jianhong Wang · Yaodong Yang · Jun WANG · Zhanxing Zhu
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #45
Dimensionally Tight Bounds for Second-Order Hamiltonian Monte Carlo
Oren Mangoubi · Nisheeth Vishnoi
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #46
Global Convergence of Langevin Dynamics Based Algorithms for Nonconvex Optimization
Pan Xu · Jinghui Chen · Difan Zou · Quanquan Gu
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #47
Meta-Learning MCMC Proposals
Tongzhou Wang · YI WU · Dave Moore · Stuart Russell
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #48
Posterior Concentration for Sparse Deep Learning
Veronika Rockova · nicholas polson
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #49
Analytic solution and stationary phase approximation for the Bayesian lasso and elastic net
Tom Michoel
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #50
Bayesian Model Selection Approach to Boundary Detection with Non-Local Priors
Fei Jiang · Guosheng Yin · Francesca Dominici
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #51
Graphical model inference: Sequential Monte Carlo meets deterministic approximations
Fredrik Lindsten · Jouni Helske · Matti Vihola
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #52
Implicit Probabilistic Integrators for ODEs
Onur Teymur · Han Cheng Lie · Tim Sullivan · Ben Calderhead
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #53
A Bayes-Sard Cubature Method
Toni Karvonen · Chris J Oates · Simo Sarkka
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #54
Deep State Space Models for Time Series Forecasting
Syama Sundar Rangapuram · Matthias W Seeger · Jan Gasthaus · Lorenzo Stella · Yuyang Wang · Tim Januschowski
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #55
BRUNO: A Deep Recurrent Model for Exchangeable Data
Iryna Korshunova · Jonas Degrave · Ferenc Huszar · Yarin Gal · Arthur Gretton · Joni Dambre
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #56
Scaling Gaussian Process Regression with Derivatives
David Eriksson · Kun Dong · Eric Lee · David Bindel · Andrew Wilson
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #57
Algebraic tests of general Gaussian latent tree models
Dennis Leung · Mathias Drton
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #58
Differentially Private Bayesian Inference for Exponential Families
Garrett Bernstein · Daniel Sheldon
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #59
Semi-crowdsourced Clustering with Deep Generative Models
Yucen Luo · TIAN TIAN · Jiaxin Shi · Jun Zhu · Bo Zhang
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #60
Deep Poisson gamma dynamical systems
Dandan Guo · Bo Chen · Hao Zhang · Mingyuan Zhou
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #61
Deep State Space Models for Unconditional Word Generation
Florian Schmidt · Thomas Hofmann
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #62
Modular Networks: Learning to Decompose Neural Computation
Louis Kirsch · Julius Kunze · David Barber
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #63
Gaussian Process Prior Variational Autoencoders
Francesco Paolo Casale · Adrian Dalca · Luca Saglietti · Jennifer Listgarten · Nicolo Fusi
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #64
Bayesian Semi-supervised Learning with Graph Gaussian Processes
Yin Cheng Ng · Nicolò Colombo · Ricardo Silva
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #65
Inference in Deep Gaussian Processes using Stochastic Gradient Hamiltonian Monte Carlo
Marton Havasi · José Miguel Hernández-Lobato · Juan José Murillo-Fuentes
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #66
Variational Bayesian Monte Carlo
Luigi Acerbi
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #67
Bayesian Alignments of Warped Multi-Output Gaussian Processes
Markus Kaiser · Clemens Otte · Thomas Runkler · Carl Henrik Ek
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #68
Automating Bayesian optimization with Bayesian optimization
Gustavo Malkomes · Roman Garnett
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #69
Infinite-Horizon Gaussian Processes
Arno Solin · James Hensman · Richard E Turner
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #70
Learning Gaussian Processes by Minimizing PAC-Bayesian Generalization Bounds
David Reeb · Andreas Doerr · Sebastian Gerwinn · Barbara Rakitsch
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #71
Algorithmic Linearly Constrained Gaussian Processes
Markus Lange-Hegermann
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #72
Efficient Projection onto the Perfect Phylogeny Model
Bei Jia · Surjyendu Ray · Sam Safavi · José Bento
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #73
Distributed $k$-Clustering for Data with Heavy Noise
Shi Li · Xiangyu Guo
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #74
Communication Compression for Decentralized Training
Hanlin Tang · Shaoduo Gan · Ce Zhang · Tong Zhang · Ji Liu
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #75
Do Less, Get More: Streaming Submodular Maximization with Subsampling
Moran Feldman · Amin Karbasi · Ehsan Kazemi
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #76
Optimal Algorithms for Continuous Non-monotone Submodular and DR-Submodular Maximization
Rad Niazadeh · Tim Roughgarden · Joshua Wang
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #77
Provable Variational Inference for Constrained Log-Submodular Models
Josip Djolonga · Stefanie Jegelka · Andreas Krause
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #78
Fast greedy algorithms for dictionary selection with generalized sparsity constraints
Kaito Fujii · Tasuku Soma
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #79
Boolean Decision Rules via Column Generation
Sanjeeb Dash · Oktay Gunluk · Dennis Wei
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #80
Computing Kantorovich-Wasserstein Distances on $d$-dimensional histograms using $(d+1)$-partite graphs
Gennaro Auricchio · Federico Bassetti · Stefano Gualandi · Marco Veneroni
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #81
Adaptive Negative Curvature Descent with Applications in Non-convex Optimization
Mingrui Liu · Zhe Li · Xiaoyu Wang · Jinfeng Yi · Tianbao Yang
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #82
Implicit Bias of Gradient Descent on Linear Convolutional Networks
Suriya Gunasekar · Jason Lee · Daniel Soudry · Nati Srebro
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #83
Deep Generative Models for Distribution-Preserving Lossy Compression
Michael Tschannen · Eirikur Agustsson · Mario Lucic
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #84
Visual Object Networks: Image Generation with Disentangled 3D Representations
Jun-Yan Zhu · Zhoutong Zhang · Chengkai Zhang · Jiajun Wu · Antonio Torralba · Josh Tenenbaum · Bill Freeman
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #85
Nonlocal Neural Networks, Nonlocal Diffusion and Nonlocal Modeling
Yunzhe Tao · Qi Sun · Qiang Du · Wei Liu
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #86
Can We Gain More from Orthogonality Regularizations in Training Deep Networks?
Nitin Bansal · Xiaohan Chen · Zhangyang Wang
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #87
Discrimination-aware Channel Pruning for Deep Neural Networks
Zhuangwei Zhuang · Mingkui Tan · Bohan Zhuang · Jing Liu · Yong Guo · Qingyao Wu · Junzhou Huang · Jinhui Zhu
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #88
Probabilistic Model-Agnostic Meta-Learning
Chelsea Finn · Kelvin Xu · Sergey Levine
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #89
FastGRNN: A Fast, Accurate, Stable and Tiny Kilobyte Sized Gated Recurrent Neural Network
Aditya Kusupati · Manish Singh · Kush Bhatia · Ashish Kumar · Prateek Jain · Manik Varma
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #90
Understanding Batch Normalization
Nils Bjorck · Carla P Gomes · Bart Selman · Kilian Weinberger
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #91
How Many Samples are Needed to Estimate a Convolutional Neural Network?
Simon Du · Yining Wang · Xiyu Zhai · Sivaraman Balakrishnan · Ruslan Salakhutdinov · Aarti Singh
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #92
Robust Detection of Adversarial Attacks by Modeling the Intrinsic Properties of Deep Neural Networks
Zhihao Zheng · Pengyu Hong
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #93
Combinatorial Optimization with Graph Convolutional Networks and Guided Tree Search
Zhuwen Li · Qifeng Chen · Vladlen Koltun
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #94
Automatic differentiation in ML: Where we are and where we should be going
Bart van Merrienboer · Olivier Breuleux · Arnaud Bergeron · Pascal Lamblin
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #95
Realistic Evaluation of Deep Semi-Supervised Learning Algorithms
Avital Oliver · Augustus Odena · Colin A Raffel · Ekin Dogus Cubuk · Ian Goodfellow
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #96
Toddler-Inspired Visual Object Learning
Sven Bambach · David Crandall · Linda Smith · Chen Yu
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #97
Generalisation in humans and deep neural networks
Robert Geirhos · Carlos R. M. Temme · Jonas Rauber · Heiko H. Schütt · Matthias Bethge · Felix A. Wichmann
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #98
Assessing the Scalability of Biologically-Motivated Deep Learning Algorithms and Architectures
Sergey Bartunov · Adam Santoro · Blake Richards · Luke Marris · Geoffrey E Hinton · Timothy Lillicrap
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #99
Incorporating Context into Language Encoding Models for fMRI
Shailee Jain · Alexander Huth
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #100
Why so gloomy? A Bayesian explanation of human pessimism bias in the multi-armed bandit task
Dalin Guo · Angela J Yu
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #101
Mental Sampling in Multimodal Representations
Jianqiao Zhu · Adam Sanborn · Nick Chater
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #102
Integrated accounts of behavioral and neuroimaging data using flexible recurrent neural network models
Amir Dezfouli · Richard Morris · Fabio Ramos · Peter Dayan · Bernard Balleine
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #103
Efficient inference for time-varying behavior during learning
Nicholas Roy · Ji Hyun Bak · Athena Akrami · Carlos Brody · Jonathan W Pillow
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #104
Multivariate Convolutional Sparse Coding for Electromagnetic Brain Signals
Tom Dupré la Tour · Thomas Moreau · Mainak Jas · Alexandre Gramfort
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #105
Manifold-tiling Localized Receptive Fields are Optimal in Similarity-preserving Neural Networks
Anirvan Sengupta · Cengiz Pehlevan · Mariano Tepper · Alexander Genkin · Dmitri Chklovskii
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #106
Connectionist Temporal Classification with Maximum Entropy Regularization
Hu Liu · Sheng Jin · Changshui Zhang
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #107
Removing the Feature Correlation Effect of Multiplicative Noise
Zijun Zhang · Yining Zhang · Zongpeng Li
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #108
Overfitting or perfect fitting? Risk bounds for classification and regression rules that interpolate
Mikhail Belkin · Daniel Hsu · Partha Mitra
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #109
Smoothed Analysis of Discrete Tensor Decomposition and Assemblies of Neurons
Nima Anari · Constantinos Daskalakis · Wolfgang Maass · Christos Papadimitriou · Amin Saberi · Santosh Vempala
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #110
Entropy and mutual information in models of deep neural networks
Marylou Gabrié · Andre Manoel · Clément Luneau · jean barbier · Nicolas Macris · Florent Krzakala · Lenka Zdeborová
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #111
The committee machine: Computational to statistical gaps in learning a two-layers neural network
Benjamin Aubin · Antoine Maillard · jean barbier · Florent Krzakala · Nicolas Macris · Lenka Zdeborová
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #112
A Unified Framework for Extensive-Form Game Abstraction with Bounds
Christian Kroer · Tuomas Sandholm
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #113
Connecting Optimization and Regularization Paths
Arun Suggala · Adarsh Prasad · Pradeep Ravikumar
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #114
Overlapping Clustering Models, and One (class) SVM to Bind Them All
Xueyu Mao · Purnamrita Sarkar · Deepayan Chakrabarti
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #115
Learning latent variable structured prediction models with Gaussian perturbations
Kevin Bello · Jean Honorio
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #116
Self-Supervised Generation of Spatial Audio for 360° Video
Pedro Morgado · Nuno Nvasconcelos · Timothy Langlois · Oliver Wang
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #117
Symbolic Graph Reasoning Meets Convolutions
Xiaodan Liang · Zhiting Hu · Hao Zhang · Liang Lin · Eric Xing
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #118
Towards Deep Conversational Recommendations
Raymond Li · Samira Ebrahimi Kahou · Hannes Schulz · Vincent Michalski · Laurent Charlin · Chris Pal
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #119
Human-in-the-Loop Interpretability Prior
Isaac Lage · Andrew Ross · Samuel J Gershman · Been Kim · Finale Doshi-Velez
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #120
Why Is My Classifier Discriminatory?
Irene Chen · Fredrik Johansson · David Sontag
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #121
Link Prediction Based on Graph Neural Networks
Muhan Zhang · Yixin Chen
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #122
KONG: Kernels for ordered-neighborhood graphs
Moez Draief · Konstantin Kutzkov · Kevin Scaman · Milan Vojnovic
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #123
Efficient Stochastic Gradient Hard Thresholding
Pan Zhou · Xiaotong Yuan · Jiashi Feng
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #124
Measures of distortion for machine learning
Leena Chennuru Vankadara · Ulrike von Luxburg
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #125
Relating Leverage Scores and Density using Regularized Christoffel Functions
Edouard Pauwels · Francis Bach · Jean-Philippe Vert
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #126
Streaming Kernel PCA with $\tilde{O}(\sqrt{n})$ Random Features
Md Enayat Ullah · Poorya Mianjy · Teodor Vanislavov Marinov · Raman Arora
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #127
Learning with SGD and Random Features
Luigi Carratino · Alessandro Rudi · Lorenzo Rosasco
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #128
But How Does It Work in Theory? Linear SVM with Random Features
Yitong Sun · Anna Gilbert · Ambuj Tewari
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #129
Statistical and Computational Trade-Offs in Kernel K-Means
Daniele Calandriello · Lorenzo Rosasco
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #130
Quadrature-based features for kernel approximation
Marina Munkhoeva · Yermek Kapushev · Evgeny Burnaev · Ivan Oseledets
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #131
Processing of missing data by neural networks
Marek Śmieja · Łukasz Struski · Jacek Tabor · Bartosz Zieliński · Przemysław Spurek
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #132
Constructing Deep Neural Networks by Bayesian Network Structure Learning
Raanan Y. Rohekar · Shami Nisimov · Yaniv Gurwicz · Guy Koren · Gal Novik
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #133
Mallows Models for Top-k Lists
Flavio Chierichetti · Anirban Dasgupta · Shahrzad Haddadan · Ravi Kumar · Silvio Lattanzi
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #134
Cooperative neural networks (CoNN): Exploiting prior independence structure for improved classification
Harsh Shrivastava · Eugene Bart · Bob Price · Hanjun Dai · Bo Dai · Srinivas Aluru
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #135
Maximum-Entropy Fine Grained Classification
Abhimanyu Dubey · Otkrist Gupta · Ramesh Raskar · Nikhil Naik
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #136
Efficient Loss-Based Decoding on Graphs for Extreme Classification
Itay Evron · Edward Moroshko · Koby Crammer
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #137
A no-regret generalization of hierarchical softmax to extreme multi-label classification
Marek Wydmuch · Kalina Jasinska · Mikhail Kuznetsov · Róbert Busa-Fekete · Krzysztof Dembczynski
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #138
Efficient Gradient Computation for Structured Output Learning with Rational and Tropical Losses
Corinna Cortes · Vitaly Kuznetsov · Mehryar Mohri · Dmitry Storcheus · Scott Yang
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #139
Deep Structured Prediction with Nonlinear Output Transformations
Colin Graber · Ofer Meshi · Alexander Schwing
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #140
Mapping Images to Scene Graphs with Permutation-Invariant Structured Prediction
Roei Herzig · Moshiko Raboh · Gal Chechik · Jonathan Berant · Amir Globerson
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #141
Large Margin Deep Networks for Classification
Gamaleldin Elsayed · Dilip Krishnan · Hossein Mobahi · Kevin Regan · Samy Bengio
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #142
Semi-supervised Deep Kernel Learning: Regression with Unlabeled Data by Minimizing Predictive Variance
Neal Jean · Sang Michael Xie · Stefano Ermon
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #143
Multitask Boosting for Survival Analysis with Competing Risks
Alexis Bellot · Mihaela van der Schaar
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #144
Multi-Layered Gradient Boosting Decision Trees
Ji Feng · Yang Yu · Zhi-Hua Zhou
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #145
Unsupervised Adversarial Invariance
Ayush Jaiswal · Rex Yue Wu · Wael Abd-Almageed · Prem Natarajan
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #146
Learning Deep Disentangled Embeddings With the F-Statistic Loss
Karl Ridgeway · Michael Mozer
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #147
Learning Latent Subspaces in Variational Autoencoders
Jack Klys · Jake Snell · Richard Zemel
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #148
Dual Swap Disentangling
Zunlei Feng · Xinchao Wang · Chenglong Ke · An-Xiang Zeng · Dacheng Tao · Mingli Song
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #149
Joint Autoregressive and Hierarchical Priors for Learned Image Compression
David Minnen · Johannes Ballé · Johannes Ballé · George D Toderici
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #150
Group Equivariant Capsule Networks
Jan Eric Lenssen · Matthias Fey · Pascal Libuschewski
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #151
Learning Disentangled Joint Continuous and Discrete Representations
Emilien Dupont
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #152
Image-to-image translation for cross-domain disentanglement
Abel Gonzalez-Garcia · Joost van de Weijer · Yoshua Bengio
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #153
Cooperative Learning of Audio and Video Models from Self-Supervised Synchronization
Bruno Korbar · Du Tran · Lorenzo Torresani
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #154
Non-Adversarial Mapping with VAEs
Yedid Hoshen
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #155
Learning to Teach with Dynamic Loss Functions
Lijun Wu · Fei Tian · Yingce Xia · Yang Fan · Tao Qin · Lai Jian-Huang · Tie-Yan Liu
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #156
Maximizing acquisition functions for Bayesian optimization
James Wilson · Frank Hutter · Marc Deisenroth
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #157
MetaReg: Towards Domain Generalization using Meta-Regularization
Yogesh Balaji · Swami Sankaranarayanan · Rama Chellappa
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #158
Transfer Learning with Neural AutoML
Catherine Wong · Neil Houlsby · Yifeng Lu · Andrea Gesmundo
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #159
Hierarchical Reinforcement Learning for Zero-shot Generalization with Subtask Dependencies
Sungryull Sohn · Junhyuk Oh · Honglak Lee
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #160
Lifelong Inverse Reinforcement Learning
Jorge A Mendez · Shashank Shivkumar · Eric Eaton
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #161
Safe Active Learning for Time-Series Modeling with Gaussian Processes
Christoph Zimmer · Mona Meister · Duy Nguyen-Tuong
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #162
Online Structure Learning for Feed-Forward and Recurrent Sum-Product Networks
Agastya Kalra · Abdullah Rashwan · Wei-Shou Hsu · Pascal Poupart · Prashant Doshi · Georgios Trimponias
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #163
Preference Based Adaptation for Learning Objectives
Yao-Xiang Ding · Zhi-Hua Zhou
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #164
Byzantine Stochastic Gradient Descent
Dan Alistarh · Zeyuan Allen-Zhu · Jerry Li
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #165
Contextual bandits with surrogate losses: Margin bounds and efficient algorithms
Dylan Foster · Akshay Krishnamurthy
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #166
Online Learning of Quantum States
Scott Aaronson · Xinyi Chen · Elad Hazan · Satyen Kale · Ashwin Nayak
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #167
Horizon-Independent Minimax Linear Regression
Alan Malek · Peter Bartlett
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #168
Factored Bandits
Julian Zimmert · Yevgeny Seldin
Poster
Thu Dec 6th 10:45 AM -- 12:45 PM @ Room 210 & 230 AB #169
A Model for Learned Bloom Filters and Optimizing by Sandwiching
Michael Mitzenmacher
Invited Talk
Thu Dec 6th 02:15 -- 03:05 PM @ Rooms 220 CDE
Designing Computer Systems for Software 2.0
Kunle Olukotun
Break
Thu Dec 6th 03:05 -- 03:30 PM @
Coffee Break
Spotlight
Thu Dec 6th 03:30 -- 03:35 PM @ Room 220 CD
Robust Subspace Approximation in a Stream
Roie Levin · Anish Prasad Sevekari · David Woodruff
Spotlight
Thu Dec 6th 03:30 -- 03:35 PM @ Room 220 E
Hyperbolic Neural Networks
Octavian Ganea · Gary Becigneul · Thomas Hofmann
Spotlight
Thu Dec 6th 03:30 -- 03:35 PM @ Room 517 CD
A Simple Proximal Stochastic Gradient Method for Nonsmooth Nonconvex Optimization
Zhize Li · Jian Li
Spotlight
Thu Dec 6th 03:35 -- 03:40 PM @ Room 220 CD
Efficient nonmyopic batch active search
Shali Jiang · Gustavo Malkomes · Matthew Abbott · Benjamin Moseley · Roman Garnett
Spotlight
Thu Dec 6th 03:35 -- 03:40 PM @ Room 220 E
Norm matters: efficient and accurate normalization schemes in deep networks
Elad Hoffer · Ron Banner · Itay Golan · Daniel Soudry
Spotlight
Thu Dec 6th 03:35 -- 03:40 PM @ Room 517 CD
Stochastic Chebyshev Gradient Descent for Spectral Optimization
Insu Han · Haim Avron · Jinwoo Shin
Spotlight
Thu Dec 6th 03:40 -- 03:45 PM @ Room 220 CD
Interactive Structure Learning with Structural Query-by-Committee
Christopher Tosh · Sanjoy Dasgupta
Spotlight
Thu Dec 6th 03:40 -- 03:45 PM @ Room 220 E
Constructing Fast Network through Deconstruction of Convolution
Yunho Jeon · Junmo Kim
Spotlight
Thu Dec 6th 03:40 -- 03:45 PM @ Room 517 CD
LAG: Lazily Aggregated Gradient for Communication-Efficient Distributed Learning
Tianyi Chen · Georgios Giannakis · Tao Sun · Wotao Yin
Spotlight
Thu Dec 6th 03:45 -- 03:50 PM @ Room 220 CD
Contour location via entropy reduction leveraging multiple information sources
Alexandre Marques · Remi Lam · Karen Willcox
Spotlight
Thu Dec 6th 03:45 -- 03:50 PM @ Room 220 E
A Simple Unified Framework for Detecting Out-of-Distribution Samples and Adversarial Attacks
Kimin Lee · Kibok Lee · Honglak Lee · Jinwoo Shin
Spotlight
Thu Dec 6th 03:45 -- 03:50 PM @ Room 517 CD
Low-rank Interaction with Sparse Additive Effects Model for Large Data Frames
Geneviève Robin · Hoi-To Wai · Julie Josse · Olga Klopp · Eric Moulines
Oral
Thu Dec 6th 03:50 -- 04:05 PM @ Room 220 CD
Non-delusional Q-learning and value-iteration
Tyler Lu · Dale Schuurmans · Craig Boutilier
Oral
Thu Dec 6th 03:50 -- 04:05 PM @ Room 220 E
Discovery of Latent 3D Keypoints via End-to-end Geometric Reasoning
Supasorn Suwajanakorn · Noah Snavely · Jonathan Tompson · Mohammad Norouzi
Oral
Thu Dec 6th 03:50 -- 04:05 PM @ Room 517 CD
Optimal Algorithms for Non-Smooth Distributed Optimization in Networks
Kevin Scaman · Francis Bach · Sebastien Bubeck · Laurent Massoulié · Yin Tat Lee
Spotlight
Thu Dec 6th 04:05 -- 04:10 PM @ Room 220 CD
Policy-Conditioned Uncertainty Sets for Robust Markov Decision Processes
Andrea Tirinzoni · Marek Petrik · Xiangli Chen · Brian Ziebart
Spotlight
Thu Dec 6th 04:05 -- 04:10 PM @ Room 220 E
Learning Libraries of Subroutines for Neurally–Guided Bayesian Program Induction
Kevin Ellis · Lucas Morales · Mathias Sablé-Meyer · Armando Solar-Lezama · Josh Tenenbaum
Spotlight
Thu Dec 6th 04:05 -- 04:10 PM @ Room 517 CD
Direct Runge-Kutta Discretization Achieves Acceleration
Jingzhao Zhang · Aryan Mokhtari · Suvrit Sra · Ali Jadbabaie
Spotlight
Thu Dec 6th 04:10 -- 04:15 PM @ Room 220 CD
Learning convex bounds for linear quadratic control policy synthesis
Jack Umenberger · Thomas Schön
Spotlight
Thu Dec 6th 04:10 -- 04:15 PM @ Room 220 E
Learning Loop Invariants for Program Verification
Xujie Si · Hanjun Dai · Mukund Raghothaman · Mayur Naik · Le Song
Spotlight
Thu Dec 6th 04:10 -- 04:15 PM @ Room 517 CD
Limited Memory Kelley's Method Converges for Composite Convex and Submodular Objectives
In