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938 Program Highlights »
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Break
Mon Dec 4th 07:00 -- 08:00 AM @
coffee, no breakfast served
Tutorial
Mon Dec 4th 08:00 -- 10:15 AM @ Grand Ballroom
A Primer on Optimal Transport
Marco Cuturi · Justin M Solomon
Tutorial
Mon Dec 4th 08:00 -- 10:15 AM @ Hall C
Reinforcement Learning with People
Emma Brunskill
Tutorial
Mon Dec 4th 08:00 -- 10:15 AM @ Hall A
Deep Learning: Practice and Trends
Nando de Freitas · Scott Reed · Oriol Vinyals
Break
Mon Dec 4th 10:15 -- 10:45 AM @
Coffee Break
Tutorial
Mon Dec 4th 10:45 AM -- 01:00 PM @ Grand Ballroom
Fairness in Machine Learning
Solon Barocas · Moritz Hardt
Tutorial
Mon Dec 4th 10:45 AM -- 01:00 PM @ Hall C
Statistical Relational Artificial Intelligence: Logic, Probability and Computation
Luc De Raedt · David Poole · Kristian Kersting · Sriraam Natarajan
Tutorial
Mon Dec 4th 10:45 AM -- 01:00 PM @ Hall A
Deep Probabilistic Modelling with Gaussian Processes
Neil D Lawrence
Tutorial
Mon Dec 4th 02:30 -- 04:45 PM @ Grand Ballroom
Differentially Private Machine Learning: Theory, Algorithms and Applications
Kamalika Chaudhuri · Anand D Sarwate
Tutorial
Mon Dec 4th 02:30 -- 04:45 PM @ Hall C
Engineering and Reverse-Engineering Intelligence Using Probabilistic Programs, Program Induction, and Deep Learning
Josh Tenenbaum · Vikash K Mansinghka
Tutorial
Mon Dec 4th 02:30 -- 04:45 PM @ Hall A
Geometric Deep Learning on Graphs and Manifolds
Michael Bronstein · Joan Bruna · arthur szlam · Xavier Bresson · Yann LeCun
Invited Talk (Posner Lecture)
Mon Dec 4th 05:30 -- 06:20 PM @ Hall A
Energy Strategies to Decrease CO2 Emissions
John Platt
Break
Mon Dec 4th 06:30 -- 08:30 PM @
Opening Reception
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #1
Learning Active Learning from Data
Ksenia Konyushkova · Raphael Sznitman · Pascal Fua
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #2
Scalable Variational Inference for Dynamical Systems
Stefan Bauer · Nico S Gorbach · Joachim M Buhmann
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #3
Active Learning from Peers
Keerthiram Murugesan · Jaime Carbonell
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #4
Gradient Episodic Memory for Continuum Learning
David Lopez-Paz · Marc'Aurelio Ranzato
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #5
Consistent Multitask Learning with Nonlinear Output Relations
Carlo Ciliberto · Alessandro Rudi · Lorenzo Rosasco · Massimiliano Pontil
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #6
Joint distribution optimal transportation for domain adaptation
Nicolas Courty · Rémi Flamary · Amaury Habrard · Alain Rakotomamonjy
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #7
Learning Multiple Tasks with Deep Relationship Networks
Mingsheng Long · Jianmin Wang · Philip S Yu
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #8
Label Efficient Learning of Transferable Representations acrosss Domains and Tasks
Zelun Luo · Yuliang Zou · Judy Hoffman · Li Fei-Fei
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #9
Matching neural paths: transfer from recognition to correspondence search
Nikolay Savinov · Lubor Ladicky · Marc Pollefeys
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #10
Do Deep Neural Networks Suffer from Crowding?
Anna Volokitin · Gemma Roig · Tomaso A Poggio
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #11
SVCCA: Singular Vector Canonical Correlation Analysis for Deep Understanding and Improvement
Maithra Raghu · Justin Gilmer · Jason Yosinski · Jascha Sohl-Dickstein
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #12
Neural Expectation Maximization
Klaus Greff · Sjoerd van Steenkiste · Jürgen Schmidhuber
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #13
PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space
Charles Ruizhongtai Qi · Li Yi · Hao Su · Leonidas J Guibas
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #14
Preserving Proximity and Global Ranking for Node Embedding
Yi-An Lai · Chin-Chi Hsu · Wen Hao Chen · Mi-Yen Yeh · Shou-De Lin
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #15
Unsupervised Transformation Learning via Convex Relaxations
Tatsunori B Hashimoto · Percy Liang · John C Duchi
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #16
Hunt For The Unique, Stable, Sparse And Fast Feature Learning On Graphs
Saurabh Verma · Zhi-Li Zhang
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #17
Deep Subspace Clustering Network
Pan Ji · Tong Zhang · Hongdong Li · Mathieu Salzmann · Ian Reid
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #18
Learning Graph Embeddings with Embedding Propagation
Alberto Garcia Duran · Mathias Niepert
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #19
Unsupervised Sequence Classification using Sequential Output Statistics
Yu Liu · Jianshu Chen · Li Deng
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #20
Context Selection for Embedding Models
Liping Liu · Francisco Ruiz · David Blei
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #21
Probabilistic Rule Realization and Selection
Haizi Yu · Tianxi Li · Lav Varshney
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #22
Trimmed Density Ratio Estimation
Song Liu · Akiko Takeda · Taiji Suzuki · Kenji Fukumizu
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #23
A Minimax Optimal Algorithm for Crowdsourcing
Richard Combes · Thomas Bonald
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #24
Introspective Classification with Convolutional Nets
Long Jin · Justin Lazarow · Zhuowen Tu
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #25
Adaptive Classification for Prediction Under a Budget
Feng Nan · Venkatesh Saligrama
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #26
Learning with Feature Evolvable Streams
Bo-Jian Hou · Lijun Zhang · Zhi-Hua Zhou
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #27
Aggressive Sampling for Multi-class to Binary Reduction with Applications to Text Classification
Bikash Joshi · Massih-Reza Amini · Ioannis Partalas · Franck Iutzeler · Yury Maximov
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #28
Adversarial Surrogate Losses for Ordinal Regression
Rizal Fathony · Mohammad Ali Bashiri · Brian Ziebart
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #29
Formal Guarantees on the Robustness of a Classifier against Adversarial Manipulation
Matthias Hein · Maksym Andriushchenko
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #30
Cost efficient gradient boosting
Sven Peter · Ferran Diego · Fred Hamprecht · Boaz Nadler
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #31
A Highly Efficient Gradient Boosting Decision Tree
Guolin Ke · Qi Meng · Taifeng Wang · Wei Chen · Weidong Ma · Tie-Yan Liu
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #32
Estimating Accuracy from Unlabeled Data: A Probabilistic Logic Approach
Emmanouil Platanios · Hoifung Poon · Tom M Mitchell · Eric J Horvitz
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #33
Inferring Generative Model Structure with Static Analysis
Paroma Varma · Bryan He · Payal Bajaj · Nishith Khandwala · Christopher Ré
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #34
Scalable Model Selection for Belief Networks
Zhao Song · Yusuke Muraoka · Ryohei Fujimaki · Lawrence Carin
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #35
Time-dependent spatially varying graphical models, with application to brain fMRI data analysis
Kristjan Greenewald · Seyoung Park · Shuheng Zhou · Alexander Giessing
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #36
A Bayesian Data Augmentation Approach for Learning Deep Models
Toan Tran · Trung Pham · Gustavo Carneiro · Lyle Palmer · Ian Reid
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #37
Union of Intersections (UoI) for Interpretable Data Driven Discovery and Prediction
Kristofer Bouchard · Alejandro Bujan · Farbod Roosta-Khorasani · Shashanka Ubaru · Mr. Prabhat · Antoine Snijders · Jian-Hua Mao · Edward Chang · Michael W Mahoney · Sharmodeep Bhattacharya
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #38
Deep Learning with Topological Signatures
Christoph Hofer · Roland Kwitt · Marc Niethammer · Andreas Uhl
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #39
Practical Hash Functions for Similarity Estimation and Dimensionality Reduction
Søren Dahlgaard · Mathias Knudsen · Mikkel Thorup
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #40
Maxing and Ranking with Few Assumptions
Venkatadheeraj Pichapati · Alon Orlitsky · Vaishakh Ravindrakumar · Moein Falahatgar · Yi Hao
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #41
Kernel functions based on triplet comparisons
Matthäus Kleindessner · Ulrike von Luxburg
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #42
Learning A Structured Optimal Bipartite Graph for Co-Clustering
Feiping Nie · Xiaoqian Wang · Heng Huang
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #43
Multi-way Interacting Regression via Factorization Machines
Mikhail Yurochkin · XuanLong Nguyen · nikolaos Vasiloglou
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #44
Maximum Margin Interval Trees
Alexandre Drouin · Toby Hocking · Francois Laviolette
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #45
Kernel Feature Selection via Conditional Covariance Minimization
Jianbo Chen · Mitchell Stern · Martin J Wainwright · Michael Jordan
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #46
Improved Graph Laplacian via Geometric Self-Consistency
Dominique Joncas · Marina Meila · James McQueen
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #47
Mixture-Rank Matrix Approximation for Collaborative Filtering
Dongsheng Li · Chao Chen · Wei Liu · Tun Lu · Ning Gu · Stephen Chu
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #48
Predictive State Recurrent Neural Networks
Carlton Downey · Ahmed Hefny · Byron Boots · Geoffrey Gordon · Boyue Li
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #49
Hierarchical Methods of Moments
Matteo Ruffini · Guillaume Rabusseau · Borja Balle
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #50
Multitask Spectral Learning of Weighted Automata
Guillaume Rabusseau · Borja Balle · Joelle Pineau
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #51
Generative Local Metric Learning for Kernel Regression
Yung-Kyun Noh · Masashi Sugiyama · Kee-Eung Kim · Frank Park · Daniel Lee
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #52
Principles of Riemannian Geometry in Neural Networks
Michael Hauser · Asok Ray
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #53
Subset Selection for Sequential Data
Ehsan Elhamifar
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #54
On Quadratic Convergence of DC Proximal Newton Algorithm in Nonconvex Sparse Learning
Xingguo Li · Lin Yang · Jason Ge · Jarvis Haupt · Tong Zhang · Tuo Zhao
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #55
Fast, Sample-Efficient Algorithms for Structured Phase Retrieval
Gauri Jagatap · Chinmay Hegde
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #56
k-Support and Ordered Weighted Sparsity for Overlapping Groups: Hardness and Algorithms
Cong Han Lim · Stephen Wright
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #57
Parametric Simplex Method for Sparse Learning
Haotian Pang · Tuo Zhao · Han Liu · Robert J Vanderbei
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #58
Learned D-AMP: Principled Neural-network-based Compressive Image Recovery
Chris Metzler · Ali Mousavi · Richard Baraniuk
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #59
FALKON: An Optimal Large Scale Kernel Method
Alessandro Rudi · Luigi Carratino · Lorenzo Rosasco
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #60
Recursive Sampling for the Nystrom Method
Cameron Musco · Christopher Musco
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #61
Efficient Approximation Algorithms for Strings Kernel Based Sequence Classification
Muhammad Farhan · Juvaria Tariq · Arif Zaman · Mudassir Shabbir · Imdad Ullah Khan
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #62
Robust Hypothesis Test for Functional Effect with Gaussian Processes
Jeremiah Liu · Brent Coull
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #63
Invariance and Stability of Deep Convolutional Representations
Alberto Bietti · Julien Mairal
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #64
Testing and Learning on Distributions with Symmetric Noise Invariance
Law Ho Chung · Christopher Yau · Dino Sejdinovic
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #65
An Empirical Study on The Properties of Random Bases for Kernel Methods
Maximilian Alber · Pieter-Jan Kindermans · Kristof Schütt · Klaus-Robert Müller · Fei Sha
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #66
Max-Margin Invariant Features from Transformed Unlabelled Data
Dipan Pal · Ashwin Kannan · Gautam Arakalgud · Marios Savvides
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #67
SafetyNets: Verifiable Execution of Deep Neural Networks on an Untrusted Cloud
Zahra Ghodsi · Tianyu Gu · Siddharth Garg
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #68
Multi-output Polynomial Networks and Factorization Machines
Mathieu Blondel · Vlad Niculae · Takuma Otsuka · Naonori Ueda
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #69
The Neural Hawkes Process: A Neurally Self-Modulating Multivariate Point Process
Hongyuan Mei · Jason Eisner
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #70
Maximizing the Spread of Influence from Training Data
Eric Balkanski · Nicole Immorlica · Yaron Singer
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #71
Inductive Representation Learning on Large Graphs
Will Hamilton · Zhitao Ying · Jure Leskovec
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #72
A Meta-Learning Perspective on Cold-Start Recommendations for Items
Manasi Vartak · Hugo Larochelle · Arvind Thiagarajan
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #73
DropoutNet: Addressing Cold Start in Recommender Systems
Maksims Volkovs · Guangwei Yu · Tomi Poutanen
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #74
Federated Multi-Task Learning
Virginia Smith · Maziar Sanjabi · Chao-Kai Chiang · Ameet S Talwalkar
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #75
Flexpoint: An Adaptive Numerical Format for Efficient Training of Deep Neural Networks
Arjun K Bansal · William Constable · Oguz Elibol · Stewart Hall · Luke Hornof · Amir Khosrowshahi · Carey Kloss · Urs Köster · Marcel Nassar · Naveen Rao · Xin Wang · Tristan Webb
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #76
Bayesian Inference of Individualized Treatment Effects using Multi-task Gaussian Processes
Ahmed M. Alaa · Mihaela van der Schaar
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #77
Tomography of the London Underground: a Scalable Model for Origin-Destination Data
Nicolò Colombo · Ricardo Silva · Soong Moon Kang
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #78
Matching on Balanced Nonlinear Representations for Treatment Effects Estimation
Sheng Li · Yun Fu
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #79
MolecuLeNet: A continuous-filter convolutional neural network for modeling quantum interactions
Kristof Schütt · Pieter-Jan Kindermans · Huziel Enoc Sauceda Felix · Stefan Chmiela · Alexandre Tkatchenko · Klaus-Robert Müller
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #80
Hiding Images in Plain Sight: Deep Steganography
Shumeet Baluja
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #81
Universal Style Transfer via Feature Transforms
Yijun Li · Chen Fang · Jimei Yang · Zhaowen Wang · Xin Lu · Ming-Hsuan Yang
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #82
Attend and Predict: Understanding Gene Regulation by Selective Attention on Chromatin
Ritambhara Singh · Jack Lanchantin · Yanjun Qi
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #83
Unbounded cache model for online language modeling with open vocabulary
Edouard Grave · Moustapha Cisse · Armand Joulin
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #84
Deconvolutional Paragraph Representation Learning
Yizhe Zhang · Dinghan Shen · Guoyin Wang · Zhe Gan · Ricardo Henao · Lawrence Carin
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #85
Analyzing Hidden Representations in End-to-End Automatic Speech Recognition Systems
Yonatan Belinkov · James Glass
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #86
Best of Both Worlds: Transferring Knowledge from Discriminative Learning to a Generative Visual Dialog Model
Jiasen Lu · Anitha Kannan · Jianwei Yang · Dhruv Batra · Devi Parikh
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #87
Teaching Machines to Describe Images with Natural Language Feedback
huan ling · Sanja Fidler
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #88
High-Order Attention Models for Visual Question Answering
Idan Schwartz · Alexander Schwing · Tamir Hazan
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #89
Visual Reference Resolution using Attention Memory for Visual Dialog
Paul Hongsuck Seo · Andreas Lehrmann · Bohyung Han · Leonid Sigal
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #90
Semi-Supervised Learning for Optical Flow with Generative Adversarial Networks
Wei-Sheng Lai · Jia-Bin Huang · Ming-Hsuan Yang
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #91
Associative Embedding: End-to-End Learning for Joint Detection and Grouping
Alejandro Newell · Zhiao Huang · Jia Deng
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #92
Learning Deep Structured Multi-Scale Features using Attention-Gated CRFs for Contour Prediction
Dan Xu · Wanli Ouyang · Xavier Alameda-Pineda · Elisa Ricci · Xiaogang Wang · Nicu Sebe
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #93
Incorporating Side Information by Adaptive Convolution
Di Kang · Debarun Dhar · Antoni Chan
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #94
Learning a Multi-View Stereo Machine
Abhishek Kar · Jitendra Malik · Christian Häne
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #95
Pose Guided Person Image Generation
Liqian Ma · Xu Jia · Qianru Sun · Bernt Schiele · Tinne Tuytelaars · Luc Van Gool
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #96
Working hard to know your neighbor's margins: Local descriptor learning loss
Anastasiia Mishchuk · Dmytro Mishkin · Filip Radenovic · Jiri Matas
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #97
Multimodal Image-to-Image Translation by Enforcing Bi-Cycle Consistency
Jun-Yan Zhu · Richard Zhang · Deepak Pathak · Trevor Darrell · Oliver Wang · Eli Shechtman · Alexei Efros
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #98
Deep supervised discrete hashing
Qi Li · Zhenan Sun · Ran He · Tieniu Tan
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #99
SVD-Softmax: Fast Softmax Approximation on Large Vocabulary Neural Networks
Kyuhong Shim · Minjae Lee · Iksoo Choi · Yoonho Boo · Wonyong Sung
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #100
Hash Embeddings for Efficient Word Representations
Dan Tito Svenstrup · Jonas Hansen · Ole Winther
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #101
A Regularized Framework for Sparse and Structured Neural Attention
Vlad Niculae · Mathieu Blondel
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #102
Attentional Pooling for Action Recognition
Rohit Girdhar · Deva Ramanan
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #103
Plan, Attend, Generate: Planning for Sequence-to-Sequence Models
Caglar Gulcehre · Francis Dutil · Adam Trischler · Yoshua Bengio
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #104
Dilated Recurrent Neural Networks
Shiyu Chang · Yang Zhang · Wei Han · Mo Yu · Xiaoxiao Guo · Wei Tan · Xiaodong Cui · Michael Witbrock · Mark A Hasegawa-Johnson · Thomas Huang
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #105
Thalamus Gated Recurrent Modules
Danijar Hafner · Alexander Irpan · James Davidson · Nicolas Heess
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #106
Wasserstein Learning of Deep Generative Point Process Models
SHUAI XIAO · Mehrdad Farajtabar · Xiaojing Ye · Junchi Yan · Le Song · Hongyuan Zha
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #107
Stabilizing Training of Generative Adversarial Networks through Regularization
Kevin Roth · Aurelien Lucchi · Sebastian Nowozin · Thomas Hofmann
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #108
Neural Variational Inference and Learning in Undirected Graphical Models
Volodymyr Kuleshov · Stefano Ermon
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #109
Adversarial Symmetric Variational Autoencoder
Yuchen Pu · Weiyao Wang · Ricardo Henao · Liqun Chen · Zhe Gan · Chunyuan Li · Lawrence Carin
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #110
Diverse and Accurate Image Description Using a Variational Auto-Encoder with an Additive Gaussian Encoding Space
Liwei Wang · Alexander Schwing · Svetlana Lazebnik
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #111
Z-Forcing: Training Stochastic Recurrent Networks
Anirudh Goyal ALIAS PARTH GOYAL · Alessandro Sordoni · Marc-Alexandre Côté · Nan Ke · Yoshua Bengio
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #112
One-Shot Imitation Learning
Yan Duan · Marcin Andrychowicz · Bradly Stadie · OpenAI Jonathan Ho · Jonas Schneider · Ilya Sutskever · Pieter Abbeel · Wojciech Zaremba
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #113
Reconstruct & Crush Network
Erinc Merdivan · Mohammad Reza Loghmani · Matthieu Geist
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #114
Fader Networks: Generating Image Variations by Sliding Attribute Values
Guillaume Lample · Neil Zeghidour · Nicolas Usunier · Antoine Bordes · Ludovic DENOYER · Marc'Aurelio Ranzato
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #115
PredRNN: Recurrent Neural Networks for Video Prediction using Spatiotemporal LSTMs
Yunbo Wang · Mingsheng Long · Jianmin Wang · Philip S Yu
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #116
Multi-agent Predictive Modeling with Attentional CommNets
Yedid Hoshen
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #117
Real Time Image Saliency for Black Box Classifiers
Piotr Dabkowski · Yarin Gal
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #118
Prototypical Networks for Few-shot Learning
Jake Snell · Kevin Swersky · Richard Zemel
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #119
Few-Shot Learning Through an Information Retrieval Lens
Eleni Triantafillou · Richard Zemel · Raquel Urtasun
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #120
The Reversible Residual Network: Backpropagation Without Storing Activations
Aidan N Gomez · Mengye Ren · Raquel Urtasun · Roger Grosse
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #121
Gated Recurrent Convolution Neural Network for OCR
Jianfeng Wang · Xiaolin Hu
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #122
Learning Efficient Object Detection Models with Knowledge Distillation
Guobin Chen · Wongun Choi · Xiang Yu · Tony Han · Manmohan Chandraker
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #123
Active Bias: Training a More Accurate Neural Network by Emphasizing High Variance Samples
Haw-Shiuan Chang · Andrew McCallum · Erik Learned-Miller
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #124
Decoupling "when to update" from "how to update"
Eran Malach · Shai Shalev-Shwartz
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #125
Langevin Dynamics with Continuous Tempering for Training Deep Neural Networks
Nanyang Ye · Zhanxing Zhu · Rafal Mantiuk
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #126
Differentiable Learning of Logical Rules for Knowledge Base Reasoning
Fan Yang · Zhilin Yang · William W Cohen
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #127
Deliberation Networks: Sequence Generation Beyond One-Pass Decoding
Yingce Xia · Lijun Wu · Jianxin Lin · Fei Tian · Tao Qin · Tie-Yan Liu
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #128
Neural Program Meta-Induction
Jacob Devlin · Rudy R Bunel · Rishabh Singh · Matthew Hausknecht · Pushmeet Kohli
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #129
Saliency-based Sequential Image Attention with Multiset Prediction
Sean Welleck · Kyunghyun Cho · Zheng Zhang
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #130
Protein Interface Prediction using Graph Convolutional Networks
Alex Fout · Basir Shariat · Jonathon Byrd · Asa Ben-Hur
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #131
Dual-Agent GANs for Photorealistic and Identity Preserving Profile Face Synthesis
Jian Zhao · Lin Xiong · Panasonic Karlekar Jayashree · Jianshu Li · Fang Zhao · Zhecan Wang · Panasonic Sugiri Pranata · Panasonic Shengmei Shen · Jiashi Feng
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #132
Toward Robustness against Label Noise in Training Deep Discriminative Neural Networks
Arash Vahdat
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #133
Soft-to-Hard Vector Quantization for End-to-End Learning Compressible Representations
Eirikur Agustsson · Fabian Mentzer · Michael Tschannen · Lukas Cavigelli · Radu Timofte · Luca Benini · Luc V Gool
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #134
Selective Classification for Deep Neural Networks
Yonatan Geifman · Ran El-Yaniv
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #135
Deep Lattice Networks and Partial Monotonic Functions
Seungil You · David Ding · Kevin Canini · Jan Pfeifer · Maya Gupta
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #136
Learning to Prune Deep Neural Networks via Layer-wise Optimal Brain Surgeon
Xin Dong · Shangyu Chen · Sinno Pan
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #137
Bayesian Compression for Deep Learning
Christos Louizos · Karen Ullrich · Max Welling
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #138
Lower bounds on the robustness to adversarial perturbations
Jonathan Peck · Yvan Saeys · Bart Goossens · Joris Roels
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #139
Sobolev Training for Neural Networks
Wojciech M. Czarnecki · Simon Osindero · Max Jaderberg · Grzegorz Swirszcz · Razvan Pascanu
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #140
Structured Bayesian Pruning via Log-Normal Multiplicative Noise
Kirill Neklyudov · Dmitry Molchanov · Arsenii Ashukha · Dmitry Vetrov
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #141
Population Matching Discrepancy and Applications in Deep Learning
Jianfei Chen · Chongxuan LI · Yizhong Ru · Jun Zhu
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #142
Investigating the learning dynamics of deep neural networks using random matrix theory
Jeffrey Pennington · Samuel Schoenholz · Surya Ganguli
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #143
Robust Imitation of Diverse Behaviors
Ziyu Wang · Josh Merel · Scott Reed · Nando de Freitas · Gregory Wayne · Nicolas Heess
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #144
Question Asking as Program Generation
Anselm Rothe · Brenden Lake · Todd Gureckis
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #145
Variational Laws of Visual Attention for Dynamic Scenes
Dario Zanca · Marco Gori
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #146
Flexible statistical inference for mechanistic models of neural dynamics
Jan-Matthis Lueckmann · Pedro J Goncalves · Giacomo Bassetto · Kaan Oecal · Marcel Nonnenmacher · Jakob H Macke
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #147
Training recurrent networks to generate hypotheses about how the brain solves hard navigation problems
Ingmar Kanitscheider · Ila Fiete
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #148
YASS: Yet Another Spike Sorter
Jin Hyung Lee · David E Carlson · Hooshmand Shokri Razaghi · Weichi Yao · Georges A Goetz · E.J. Chichilnisky · Espen Hagen · Gaute T. Einevoll · Liam Paninski
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #149
Neural system identification for large populations separating "what" and "where"
David Klindt · Alexander Ecker · Thomas Euler · Matthias Bethge
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #150
A simple model of recognition and recall memory
Nisheeth Srivastava · Edward Vul
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #151
Gaussian process based nonlinear latent structure discovery in multivariate spike train data
Anqi Wu · Nicholas Roy · Stephen Keeley · Jonathan W Pillow
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #152
Deep adversarial neural decoding
Yağmur Güçlütürk · Umut Güçlü · Katja Seeliger · Sander Bosch · Rob van Lier · Marcel A. J. van Gerven
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #153
Cross-Spectral Factor Analysis
Neil Gallagher · Kyle Ulrich · Austin Talbot · Kafui Dzirasa · David E Carlson · Lawrence Carin
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #154
Cognitive Impairment Prediction in Alzheimer’s Disease with Regularized Modal Regression
Xiaoqian Wang · Hong Chen · Dinggang Shen · Heng Huang
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #155
Stochastic Submodular Maximization: The Case of Coverage Functions
Mohammad Karimi · Mario Lucic · Hamed Hassani · Andreas Krause
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #156
Gradient Methods for Submodular Maximization
Hamed Hassani · Mahdi Soltanolkotabi · Amin Karbasi
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #157
Non-convex Finite-Sum Optimization Via SCSG Methods
Lihua Lei · Cheng Ju · Jianbo Chen · Michael Jordan
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #158
Influence Maximization with $\varepsilon$-Almost Submodular Threshold Function
Qiang Li · Wei Chen · Institute of Computing Xiaoming Sun · Institute of Computing Jialin Zhang
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #159
Subset Selection under Noise
Chao Qian · Jing-Cheng Shi · Yang Yu · Ke Tang · Zhi-Hua Zhou
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #160
Polynomial time algorithms for dual volume sampling
Chengtao Li · Stefanie Jegelka · Suvrit Sra
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #161
Lookahead Bayesian Optimization with Inequality Constraints
Remi Lam · Karen Willcox
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #162
Non-monotone Continuous DR-submodular Maximization: Structure and Algorithms
An Bian · Joachim M Buhmann · Andreas Krause · Kfir Levy
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #163
Solving (Almost) all Systems of Random Quadratic Equations
Gang Wang · Georgios Giannakis · Yousef Saad · Jie Chen
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #164
Learning ReLUs via Gradient Descent
Mahdi Soltanolkotabi
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #165
Stochastic Mirror Descent for Non-Convex Optimization
Zhengyuan Zhou · Panayotis Mertikopoulos · Nicholas Bambos · Stephen Boyd · Peter W Glynn
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #166
Accelerated First-order Methods for Geodesically Convex Optimization on Riemannian Manifolds
Yuanyuan Liu · Fanhua Shang · James Cheng · Hong Cheng · Licheng Jiao
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #167
On the Fine-Grained Complexity of Empirical Risk Minimization: Kernel Methods and Neural Networks
Arturs Backurs · Piotr Indyk · Ludwig Schmidt
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #168
Large-Scale Quadratically Constrained Quadratic Program via Low-Discrepancy Sequences
Kinjal Basu · Ankan Saha · Shaunak Chatterjee
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #169
A New Alternating Direction Method for Linear Programming
Sinong Wang · Ness Shroff
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #170
Dykstra's Algorithm, ADMM, and Coordinate Descent: Connections, Insights, and Extensions
Ryan Tibshirani
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #171
Smooth Primal-Dual Coordinate Descent Algorithms for Nonsmooth Convex Optimization
Ahmet Alacaoglu · Quoc Tran Dinh · Olivier Fercoq · Volkan Cevher
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #172
First-Order Adaptive Sample Size Methods to Reduce Complexity of Empirical Risk Minimization
Aryan Mokhtari · Alejandro Ribeiro
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #173
Accelerated consensus via Min-Sum Splitting
Patrick Rebeschini · Sekhar C Tatikonda
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #174
Integration Methods and Optimization Algorithms
Damien Scieur · Vincent Roulet · Francis Bach · Alexandre d'Aspremont
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #175
Efficient Use of Limited-Memory Resources to Accelerate Linear Learning
Celestine Dünner · Thomas Parnell · Martin Jaggi
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #176
A Screening Rule for l1-Regularized Ising Model Estimation
Zhaobin Kuang · Sinong Geng · David Page
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #177
Uprooting and Rerooting Higher-order Graphical Models
Adrian Weller · Mark Rowland
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #178
Concentration of Multilinear Functions of the Ising Model with Applications to Network Data
Constantinos Daskalakis · Nishanth Dikkala · Gautam Kamath
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #179
Inference in Graphical Models via Semidefinite Programming Hierarchies
Murat A. Erdogdu · Yash Deshpande · Andrea Montanari
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #180
Beyond normality: Learning sparse probabilistic graphical models in the non-Gaussian setting
Rebecca Morrison · Ricardo Baptista · Youssef Marzouk
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #181
Dynamic Importance Sampling for Anytime Bounds of the Partition Function
Qi Lou · Rina Dechter · Alexander Ihler
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #182
Nonbacktracking Bounds on the Influence in Independent Cascade Models
Emmanuel Abbe · Sanjeev Kulkarni · Eun Jee Lee
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #183
Rigorous Dynamics and Consistent Estimation in Arbitrarily Conditioned Linear Systems
Alyson Fletcher · Sundeep Rangan · Mojtaba Sahraee-Ardakan · Philip Schniter
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #184
Learning Disentangled Representations with Semi-Supervised Deep Generative Models
Siddharth Narayanaswamy · T. Brooks Paige · Jan-Willem van de Meent · Alban Desmaison · Frank Wood · Noah Goodman · Pushmeet Kohli · Philip Torr
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #185
Gauging Variational Inference
Sung-Soo Ahn · Michael Chertkov · Jinwoo Shin
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #186
Variational Inference via $\chi$ Upper Bound Minimization
Adji Bousso Dieng · Dustin Tran · Rajesh Ranganath · John Paisley · David Blei
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #187
Collapsed variational Bayes for Markov jump processes
Boqian Zhang · Jiangwei Pan · Vinayak A Rao
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #188
Bayesian Dyadic Trees and Histograms for Regression
Stéphanie van der Pas · Veronika Rockova
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #189
Differentially private Bayesian learning on distributed data
Mikko Heikkilä · Eemil Lagerspetz · Samuel Kaski · Kana Shimizu · Sasu Tarkoma · Antti Honkela
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #190
Model-Powered Conditional Independence Test
Rajat Sen · Ananda Theertha Suresh · Karthikeyan Shanmugam · Alexandros Dimakis · Sanjay Shakkottai
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #191
When Worlds Collide: Integrating Different Counterfactual Assumptions in Fairness
Chris Russell · Ricardo Silva · Matt Kusner · Joshua Loftus
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #192
Q-LDA: Uncovering Latent Patterns in Text-based Sequential Decision Processes
Jianshu Chen · Chong Wang · Lin Xiao · Ji He · Lihong Li · Li Deng
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #193
Probabilistic Models for Integration Error in the Assessment of Functional Cardiac Models
Chris Oates · Steven Niederer · Angela Lee · François-Xavier Briol · Mark Girolami
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #194
Expectation Propagation for t-Exponential Family Using Q-Algebra
Futoshi Futami · Issei Sato · Masashi Sugiyama
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #195
A Probabilistic Framework for Nonlinearities in Stochastic Neural Networks
Qinliang Su · xuejun Liao · Lawrence Carin
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #196
Clone MCMC: Parallel High-Dimensional Gaussian Gibbs Sampling
Andrei-Cristian Barbos · Francois Caron · Jean-François Giovannelli · Arnaud Doucet
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #197
Learning spatiotemporal piecewise-geodesic trajectories from longitudinal manifold-valued data
Stéphanie ALLASSONNIERE · Juliette Chevallier
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #198
Scalable Levy Process Priors for Spectral Kernel Learning
Phillip A Jang · Andrew Loeb · Matthew Davidow · Andrew Wilson
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #199
Inferring The Latent Structure of Human Decision-Making from Raw Visual Inputs
Yunzhu Li · Jiaming Song · Stefano Ermon
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #200
Hybrid Reward Architecture for Reinforcement Learning
Harm Van Seijen · Romain Laroche · Mehdi Fatemi · Joshua Romoff
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #201
Shallow Updates for Deep Reinforcement Learning
Nir Levine · Tom Zahavy · Daniel J Mankowitz · Aviv Tamar · Shie Mannor
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #202
Towards Generalization and Simplicity in Continuous Control
Aravind Rajeswaran · Kendall Lowrey · Emanuel Todorov · Sham Kakade
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #203
Interpolated Policy Gradient: Merging On-Policy and Off-Policy Gradient Estimation for Deep Reinforcement Learning
Shixiang Gu · Tim Lillicrap · Richard E Turner · Zoubin Ghahramani · Bernhard Schölkopf · Sergey Levine
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #204
Scalable Planning with Tensorflow for Hybrid Nonlinear Domains
Ga Wu · Buser Say · Scott Sanner
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #205
Task-based End-to-end Model Learning in Stochastic Optimization
Priya Donti · J. Zico Kolter · Brandon Amos
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #206
Value Prediction Network
Junhyuk Oh · Satinder Singh · Honglak Lee
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #207
Variable Importance Using Decision Trees
Arash Amini · Seyed Jalil Kazemitabar · Adam Bloniarz · Ameet S Talwalkar
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #208
The Expressive Power of Neural Networks: A View from the Width
Zhou Lu · Hongming Pu · Feicheng Wang · Zhiqiang Hu · Liwei Wang
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #209
SGD Learns the Conjugate Kernel Class of the Network
Amit Daniely
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #210
Radon Machines: Effective Parallelisation for Machine Learning
Michael Kamp · Mario Boley · Olana Missura · Thomas Gärtner
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #211
Noise-Tolerant Interactive Learning Using Pairwise Comparisons
Yichong Xu · Hongyang Zhang · Aarti Singh · Artur Dubrawski · Kyle Miller
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #212
A PAC-Bayesian Analysis of Randomized Learning with Application to Stochastic Gradient Descent
Ben London
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #213
Revisiting Perceptron: Efficient and Label-Optimal Learning of Halfspaces
Songbai Yan · Chicheng Zhang
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #214
Sample and Computationally Efficient Learning Algorithms under S-Concave Distributions
Maria-Florina Balcan · Hongyang Zhang
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #215
Nearest-Neighbor Sample Compression: Efficiency, Consistency, Infinite Dimensions
Aryeh Kontorovich · Sivan Sabato · Roi Weiss
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #216
Learning Identifiable Gaussian Bayesian Networks in Polynomial Time and Sample Complexity
Asish Ghoshal · Jean Honorio
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #217
From which world is your graph
Cheng Li · Varun Kanade · Felix MF Wong · Zhenming Liu
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #218
Mean Field Residual Networks: On the Edge of Chaos
Ge Yang
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #219
Learning from uncertain curves: The 2-Wasserstein metric for Gaussian processes
Anton Mallasto · Aasa Feragen
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #220
On clustering network-valued data
Soumendu Sundar Mukherjee · Purnamrita Sarkar · Lizhen Lin
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #221
On the Power of Truncated SVD for General High-rank Matrix Estimation Problems
Simon Du · Yining Wang · Aarti Singh
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #222
AdaGAN: Boosting Generative Models
Ilya Tolstikhin · Sylvain Gelly · Olivier Bousquet · Carl-Johann SIMON-GABRIEL · Bernhard Schölkopf
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #223
Discovering Potential Influence via Information Bottleneck
Weihao Gao · Sreeram Kannan · Hyeji Kim · Sewoong Oh · Pramod Viswanath
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #224
Phase Transitions in the Pooled Data Problem
Jonathan Scarlett · Volkan Cevher
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #225
Coded Distributed Computing for Inverse Problems
Yaoqing Yang · Pulkit Grover · Soummya Kar
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #226
Query Complexity of Clustering with Side Information
Arya Mazumdar · Barna Saha
Poster
Mon Dec 4th 06:30 -- 10:30 PM @ Pacific Ballroom #227
Revisit Fuzzy Neural Network: Demystifying Batch Normalization and ReLU with Generalized Hamming Network
Lixin Fan
Break
Tue Dec 5th 07:30 -- 09:00 AM @
coffee, no breakfast served
Invited Talk
Tue Dec 5th 09:00 -- 09:50 AM @ Hall A
Why AI Will Make it Possible to Reprogram the Human Genome
Brendan J Frey
Break
Tue Dec 5th 10:10 -- 10:40 AM @
Coffee Break
Oral
Tue Dec 5th 10:40 -- 10:55 AM @ Hall A
Diffusion Approximations for Online Principal Component Estimation and Global Convergence
Chris Junchi Li · Mengdi Wang · Tong Zhang
Oral
Tue Dec 5th 10:40 -- 10:55 AM @ Hall C
On the Optimization Landscape of Tensor Decompositions
Rong Ge · Tengyu Ma
Oral
Tue Dec 5th 10:55 -- 11:10 AM @ Hall A
Positive-Unlabeled Learning with Non-Negative Risk Estimator
Ryuichi Kiryo · Gang Niu · Marthinus C du Plessis · Masashi Sugiyama
Oral
Tue Dec 5th 10:55 -- 11:10 AM @ Hall C
Robust Optimization for Non-Convex Objectives
Yaron Singer · Robert S Chen · Vasilis Syrgkanis · Brendan Lucier
Oral
Tue Dec 5th 11:10 -- 11:25 AM @ Hall A
An Applied Algorithmic Foundation for Hierarchical Clustering
Joshua Wang · Benjamin Moseley
Oral
Tue Dec 5th 11:10 -- 11:25 AM @ Hall C
Bayesian Optimization with Gradients
Jian Wu · Matthias Poloczek · Andrew Wilson · Peter Frazier
Spotlight
Tue Dec 5th 11:25 -- 11:30 AM @ Hall A
Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results
Antti Tarvainen · Harri Valpola
Spotlight
Tue Dec 5th 11:25 -- 11:30 AM @ Hall C
Gradient Descent Can Take Exponential Time to Escape Saddle Points
Simon Du · Chi Jin · Jason D Lee · Michael Jordan · Aarti Singh · Barnabas Poczos
Spotlight
Tue Dec 5th 11:30 -- 11:35 AM @ Hall A
Communication-Efficient Stochastic Gradient Descent, with Applications to Neural Networks
Dan Alistarh · Demjan Grubic · Jerry Li · Ryota Tomioka · Milan Vojnovic
Spotlight
Tue Dec 5th 11:30 -- 11:35 AM @ Hall C
Near-linear time approximation algorithms for optimal transport via Sinkhorn iteration
Jason Altschuler · Jonathan Weed · Philippe Rigollet
Spotlight
Tue Dec 5th 11:35 -- 11:40 AM @ Hall A
Inhomogoenous Hypergraph Clustering with Applications
Pan Li · Olgica Milenkovic
Spotlight
Tue Dec 5th 11:35 -- 11:40 AM @ Hall C
Limitations on Variance-Reduction and Acceleration Schemes for Finite Sums Optimization
Yossi Arjevani
Spotlight
Tue Dec 5th 11:40 -- 11:45 AM @ Hall A
K-Medoids For K-Means Seeding
James Newling · François Fleuret
Spotlight
Tue Dec 5th 11:40 -- 11:45 AM @ Hall C
Implicit Regularization in Matrix Factorization
Suriya Gunasekar · Blake Woodworth · Srinadh Bhojanapalli · Behnam Neyshabur · Nati Srebro
Spotlight
Tue Dec 5th 11:45 -- 11:50 AM @ Hall A
Online Learning with Transductive Regret
Scott Yang · Mehryar Mohri
Spotlight
Tue Dec 5th 11:45 -- 11:50 AM @ Hall C
Linear Convergence of a Frank-Wolfe Type Algorithm over Trace-Norm Balls
Zeyuan Allen-Zhu · Elad Hazan · Wei Hu · Yuanzhi Li
Spotlight
Tue Dec 5th 11:50 -- 11:55 AM @ Hall A
Matrix Norm Estimation from a Few Entries
Sewoong Oh · Ashish Khetan
Spotlight
Tue Dec 5th 11:50 -- 11:55 AM @ Hall C
Acceleration and Averaging in Stochastic Descent Dynamics
Walid Krichene
Spotlight
Tue Dec 5th 11:55 AM -- 12:00 PM @ Hall A
Semisupervised Clustering, AND-Queries and Locally Encodable Source Coding
Arya Mazumdar · Soumyabrata Pal
Spotlight
Tue Dec 5th 11:55 AM -- 12:00 PM @ Hall C
When Cyclic Coordinate Descent Beats Randomized Coordinate Descent
Mert Gurbuzbalaban · Nuri Vanli · Asuman Ozdaglar
Invited Talk
Tue Dec 5th 01:50 -- 02:40 PM @ Hall A
The Trouble with Bias
Kate Crawford
Oral
Tue Dec 5th 02:50 -- 03:05 PM @ Hall A
Streaming Weak Submodularity: Interpreting Neural Networks on the Fly
Ethan Elenberg · Alexandros Dimakis · Moran Feldman · Amin Karbasi
Oral
Tue Dec 5th 02:50 -- 03:05 PM @ Hall C
Safe and Nested Subgame Solving for Imperfect-Information Games
Noam Brown · Tuomas Sandholm
Oral
Tue Dec 5th 03:05 -- 03:20 PM @ Hall A
A unified approach to interpreting model predictions
Scott M Lundberg · Su-In Lee
Oral
Tue Dec 5th 03:05 -- 03:20 PM @ Hall C
A graph-theoretic approach to multitasking
Noga Alon · Daniel Reichman · Igor Shinkar · Tal Wagner · Sebastian Musslick · Tom Griffiths · Jonathan D Cohen · Biswadip dey · Kayhan Ozcimder
Spotlight
Tue Dec 5th 03:20 -- 03:25 PM @ Hall A
Differentiable Learning of Submodular Functions
Josip Djolonga · Andreas Krause
Spotlight
Tue Dec 5th 03:20 -- 03:25 PM @ Hall C
Information-theoretic analysis of generalization capability of learning algorithms
Maxim Raginsky · Aolin Xu
Spotlight
Tue Dec 5th 03:25 -- 03:30 PM @ Hall A
Generalized Linear Model Regression under Distance-to-set Penalties
Jason Xu · Eric Chi · Kenneth Lange
Spotlight
Tue Dec 5th 03:25 -- 03:30 PM @ Hall C
Net-Trim: Convex Pruning of Deep Neural Networks with Performance Guarantee
Alireza Aghasi · Nam Nguyen · Justin Romberg
Spotlight
Tue Dec 5th 03:30 -- 03:35 PM @ Hall A
Decomposable Submodular Function Minimization: Discrete and Continuous
Alina Ene · Huy Nguyen · Laszlo Vegh
Spotlight
Tue Dec 5th 03:30 -- 03:35 PM @ Hall C
Clustering Billions of Reads for DNA Data Storage
Cyrus Rashtchian · Konstantin Makarychev · Luis Ceze · Karin Strauss · Sergey Yekhanin · Djordje Jevdjic · Miklos Racz · Siena Ang
Spotlight
Tue Dec 5th 03:35 -- 03:40 PM @ Hall A
Unbiased estimates for linear regression via volume sampling
Michal Derezinski · Manfred Warmuth
Spotlight
Tue Dec 5th 03:35 -- 03:40 PM @ Hall C
On the Complexity of Learning Neural Networks
Le Song · Santosh Vempala · John Wilmes · Bo Xie
Spotlight
Tue Dec 5th 03:40 -- 03:45 PM @ Hall A
On Frank-Wolfe and Equilibrium Computation
Jacob D Abernethy · Jun-Kun Wang
Spotlight
Tue Dec 5th 03:40 -- 03:45 PM @ Hall C
Multiplicative Weights Update with Constant Step-Size in Congestion Games: Convergence, Limit Cycles and Chaos
Gerasimos Palaiopanos · Ioannis Panageas · Georgios Piliouras
Spotlight
Tue Dec 5th 03:45 -- 03:50 PM @ Hall A
On Separability of Loss Functions, and Revisiting Discriminative Vs Generative Models
Adarsh Prasad · Pradeep Ravikumar
Spotlight
Tue Dec 5th 03:45 -- 03:50 PM @ Hall C
Estimating Mutual Information for Discrete-Continuous Mixtures
Weihao Gao · Sreeram Kannan · Sewoong Oh · Pramod Viswanath
Break
Tue Dec 5th 03:50 -- 04:20 PM @
Coffee Break
Oral
Tue Dec 5th 04:20 -- 04:35 PM @ Hall A
Unsupervised object learning from dense equivariant image labelling
James Thewlis · Andrea Vedaldi · Hakan Bilen
Oral
Tue Dec 5th 04:20 -- 04:35 PM @ Hall C
A Linear-Time Kernel Goodness-of-Fit Test
Wittawat Jitkrittum · Wenkai Xu · Zoltan Szabo · Kenji Fukumizu · Arthur Gretton
Oral
Tue Dec 5th 04:35 -- 04:50 PM @ Hall A
Interpretable and Globally Optimal Prediction for Textual Grounding using Image Concepts
Raymond Yeh · Jinjun Xiong · Wen-Mei Hwu · Minh Do · Alexander Schwing
Oral
Tue Dec 5th 04:35 -- 04:50 PM @ Hall C
Generalization Properties of Learning with Random Features
Alessandro Rudi · Lorenzo Rosasco
Oral
Tue Dec 5th 04:50 -- 05:05 PM @ Hall A
Eigen-Distortions of Hierarchical Representations
Alexander Berardino · Valero Laparra · Johannes Ballé · Eero Simoncelli
Oral
Tue Dec 5th 04:50 -- 05:05 PM @ Hall C
Communication-Efficient Distributed Learning of Discrete Distributions
Ilias Diakonikolas · Elena Grigorescu · Jerry Li · Abhiram Natarajan · Krzysztof Onak · Ludwig Schmidt
Spotlight
Tue Dec 5th 05:05 -- 05:10 PM @ Hall A
Towards Accurate Binary Convolutional Neural Network
Wei Pan · Xiaofan Lin · Cong Zhao
Spotlight
Tue Dec 5th 05:05 -- 05:10 PM @ Hall C
Posterior sampling for reinforcement learning: worst-case regret bounds
Shipra Agrawal · Randy Jia
Spotlight
Tue Dec 5th 05:10 -- 05:15 PM @ Hall A
Deep Learning for Precipitation Nowcasting: A Benchmark and A New Model
Xingjian Shi · Hao Wang · Zhihan Gao · Leonard Lausen · Dit-Yan Yeung · Wang-chun WOO · Wai-kin Wong
Spotlight
Tue Dec 5th 05:10 -- 05:15 PM @ Hall C
Regret Analysis for Continuous Dueling Bandit
Wataru Kumagai
Spotlight
Tue Dec 5th 05:15 -- 05:20 PM @ Hall A
Poincaré Embeddings for Learning Hierarchical Representations
Maximillian Nickel · Douwe Kiela
Spotlight
Tue Dec 5th 05:15 -- 05:20 PM @ Hall C
Minimal Exploration in Structured Stochastic Bandits
Stefan Magureanu · Richard Combes · Alexandre Proutiere
Spotlight
Tue Dec 5th 05:20 -- 05:25 PM @ Hall A
Deep Hyperspherical Learning
Weiyang Liu · Yan-Ming Zhang · Xingguo Li · Zhiding Yu · Bo Dai · Tuo Zhao · Le Song
Spotlight
Tue Dec 5th 05:20 -- 05:25 PM @ Hall C
Fast Rates for Bandit Optimization with Upper-Confidence Frank-Wolfe
Quentin Berthet · Vianney Perchet
Spotlight
Tue Dec 5th 05:25 -- 05:30 PM @ Hall A
What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision?
Alex Kendall · Yarin Gal
Spotlight
Tue Dec 5th 05:25 -- 05:30 PM @ Hall C
Diving into the shallows: a computational perspective on large-scale shallow learning
SIYUAN MA · Mikhail Belkin
Spotlight
Tue Dec 5th 05:30 -- 05:35 PM @ Hall A
One-Sided Unsupervised Domain Mapping
Sagie Benaim · Lior Wolf
Spotlight
Tue Dec 5th 05:30 -- 05:35 PM @ Hall C
Monte-Carlo Tree Search by Best Arm Identification
Emilie Kaufmann · Wouter Koolen
Spotlight
Tue Dec 5th 05:35 -- 05:40 PM @ Hall A
Deep Mean-Shift Priors for Image Restoration
Siavash Arjomand Bigdeli · Matthias Zwicker · Paolo Favaro · Meiguang Jin
Spotlight
Tue Dec 5th 05:35 -- 05:40 PM @ Hall C
A framework for Multi-A(rmed)/B(andit) Testing with Online FDR Control
Fanny Yang · Aaditya Ramdas · Kevin Jamieson · Martin Wainwright
Spotlight
Tue Dec 5th 05:40 -- 05:45 PM @ Hall A
Deep Voice 2: Multi-Speaker Neural Text-to-Speech
Andrew Gibiansky
Spotlight
Tue Dec 5th 05:40 -- 05:45 PM @ Hall C
Parameter-Free Online Learning via Model Selection
Dylan J Foster · Satyen Kale · Mehryar Mohri · Karthik Sridharan
Spotlight
Tue Dec 5th 05:45 -- 05:50 PM @ Hall A
Graph Matching via Multiplicative Update Algorithm
Bo Jiang · Jin Tang · Bin Luo
Spotlight
Tue Dec 5th 05:45 -- 05:50 PM @ Hall C
Bregman Divergence for Stochastic Variance Reduction: Saddle-Point and Adversarial Prediction
Zhan Shi · Xinhua Zhang · Yaoliang Yu
Spotlight
Tue Dec 5th 05:50 -- 05:55 PM @ Hall A
Dynamic Routing Between Capsules
Sara Sabour · Nicholas Frosst · Geoffrey E Hinton
Spotlight
Tue Dec 5th 05:50 -- 05:55 PM @ Hall C
Gaussian Quadrature for Kernel Features
Tri Dao · Christopher M De Sa · Christopher Ré
Spotlight
Tue Dec 5th 05:55 -- 06:00 PM @ Hall A
Modulating early visual processing by language
Harm de Vries · Florian Strub · Jeremie Mary · Hugo Larochelle · Olivier Pietquin · Aaron C Courville
Spotlight
Tue Dec 5th 05:55 -- 06:00 PM @ Hall C
Online Learning of Linear Dynamical Systems
Elad Hazan · Karan Singh · Cyril Zhang
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #1
Posterior sampling for reinforcement learning: worst-case regret bounds
Shipra Agrawal · Randy Jia
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #2
A framework for Multi-A(rmed)/B(andit) Testing with Online FDR Control
Fanny Yang · Aaditya Ramdas · Kevin Jamieson · Martin Wainwright
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #3
Monte-Carlo Tree Search by Best Arm Identification
Emilie Kaufmann · Wouter Koolen
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #4
Minimal Exploration in Structured Stochastic Bandits
Stefan Magureanu · Richard Combes · Alexandre Proutiere
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #5
Regret Analysis for Continuous Dueling Bandit
Wataru Kumagai
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #6
Elementary Symmetric Polynomials for Optimal Experimental Design
Zelda E. Mariet · Suvrit Sra
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #7
Online Learning of Linear Dynamical Systems
Elad Hazan · Karan Singh · Cyril Zhang
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #8
Efficient and Flexible Inference for Stochastic Systems
Stefan Bauer · Djordje Miladinovic · Nico S Gorbach · Joachim M Buhmann
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #9
Group Sparse Additive Machine
Hong Chen · Xiaoqian Wang · Heng Huang
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #10
Bregman Divergence for Stochastic Variance Reduction: Saddle-Point and Adversarial Prediction
Zhan Shi · Xinhua Zhang · Yaoliang Yu
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #11
Online multiclass boosting
Young Hun Jung · Jack Goetz · Ambuj Tewari
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #12
Universal consistency and minimax rates for online Mondrian Forest
Jaouad Mourtada · Stéphane Gaïffas · Erwan Scornet
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #13
Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results
Antti Tarvainen · Harri Valpola
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #14
Learning from Complementary Labels
Takashi Ishida · Gang Niu · Weihua Hu · Masashi Sugiyama
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #15
Positive-Unlabeled Learning with Non-Negative Risk Estimator
Ryuichi Kiryo · Gang Niu · Marthinus C du Plessis · Masashi Sugiyama
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #16
Semisupervised Clustering, AND-Queries and Locally Encodable Source Coding
Arya Mazumdar · Soumyabrata Pal
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #17
On Learning Errors of Structured Prediction with Approximate Inference
Yuanbin Wu
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #18
On Optimal Generalizability in Parametric Learning
Ahmad Beirami · Meisam Razaviyayn · Shahin Shahrampour · Vahid Tarokh
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #19
Multi-Objective Non-parametric Sequential Prediction
Guy Uziel · Ran El-Yaniv
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #20
Fixed-Rank Approximation of a Positive-Semidefinite Matrix from Streaming Data
Joel A Tropp · Alp Yurtsever · Madeleine Udell · Volkan Cevher
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #21
Communication-Efficient Stochastic Gradient Descent, with Applications to Neural Networks
Dan Alistarh · Demjan Grubic · Jerry Li · Ryota Tomioka · Milan Vojnovic
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #22
Machine Learning with Adversaries: Byzantine Tolerant Gradient Descent
Peva Blanchard · El Mahdi El Mhamdi · Rachid Guerraoui · Julien Stainer
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #23
Ranking Data with Continuous Labels through Oriented Recursive Partitions
Stéphan Clémençon · Mastane Achab
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #24
Practical Data-Dependent Metric Compression with Provable Guarantees
Piotr Indyk · Ilya Razenshteyn · Tal Wagner
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #25
Simple strategies for recovering inner products from coarsely quantized random projections
Ping Li · Martin Slawski
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #26
Clustering Stable Instances of Euclidean k-means.
Aravindan Vijayaraghavan · Abhratanu Dutta · Alex Wang
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #27
On Distributed Hierarchical Clustering
Mahsa Derakhshan · Soheil Behnezhad · Mohammadhossein Bateni · Vahab Mirrokni · MohammadTaghi Hajiaghayi · Silvio Lattanzi · Raimondas Kiveris
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #28
Sparse k-Means Embedding
Weiwei Liu · Xiaobo Shen · Ivor Tsang
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #29
K-Medoids For K-Means Seeding
James Newling · François Fleuret
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #30
An Applied Algorithmic Foundation for Hierarchical Clustering
Joshua Wang · Benjamin Moseley
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #31
Inhomogoenous Hypergraph Clustering with Applications
Pan Li · Olgica Milenkovic
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #32
Subspace Clustering via Tangent Cones
Amin Jalali · Rebecca Willett
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #33
Tensor Biclustering
Soheil Feizi · Hamid Javadi · David Tse
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #34
A unified approach to interpreting model predictions
Scott M Lundberg · Su-In Lee
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #35
Efficient Sublinear-Regret Algorithms for Online Sparse Linear Regression
Shinji Ito · Akihiro Yabe · Ken-Ichi Kawarabayashi · Naonori Kakimura · Takuro Fukunaga · Daisuke Hatano · Hanna Sumita
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #36
Unbiased estimates for linear regression via volume sampling
Michal Derezinski · Manfred Warmuth
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #37
On Separability of Loss Functions, and Revisiting Discriminative Vs Generative Models
Adarsh Prasad · Pradeep Ravikumar
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #38
Generalized Linear Model Regression under Distance-to-set Penalties
Jason Xu · Eric Chi · Kenneth Lange
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #39
Group Additive Structure Identification for Kernel Nonparametric Regression
Chao Pan · Michael Zhu
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #40
Learning Overcomplete HMMs
Vatsal Sharan · Sham Kakade · Percy Liang · Gregory Valiant
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #41
Matrix Norm Estimation from a Few Entries
Sewoong Oh · Ashish Khetan
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #42
Optimal Shrinkage of Singular Values Under Random Data Contamination
Danny Barash · Matan Gavish
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #43
A New Theory for Nonconvex Matrix Completion
Guangcan Liu · Xiaotong Yuan · Qingshan Liu
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #44
Learning Low-Dimensional Metrics
Blake Mason · Lalit Jain · Robert Nowak
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #45
Fast Alternating Minimization Algorithms for Dictionary Learning
Niladri Chatterji · Peter Bartlett
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #46
Consistent Robust Regression
Kush Bhatia · Prateek Jain · Purushottam Kar
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #47
Partial Hard Thresholding: A Towards Unified Analysis of Support Recovery
Jie Shen · Ping Li
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #48
Minimax Estimation of Bandable Precision Matrices
Addison Hu · Sahand Negahban
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #49
Diffusion Approximations for Online Principal Component Estimation and Global Convergence
Chris Junchi Li · Mengdi Wang · Tong Zhang
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #50
Estimation of the covariance structure of heavy-tailed distributions
Xiaohan Wei · Stanislav Minsker
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #51
Learning Koopman Invariant Subspaces for Dynamic Mode Decomposition
Naoya Takeishi · Yoshinobu Kawahara · Takehisa Yairi
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #52
Stochastic Approximation for Canonical Correlation Analysis
Raman Arora · Teodor Vanislavov Marinov · Poorya Mianjy
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #53
Diving into the shallows: a computational perspective on large-scale shallow learning
SIYUAN MA · Mikhail Belkin
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #54
The Unreasonable Effectiveness of Structured Random Orthogonal Embeddings
Krzysztof M Choromanski · Mark Rowland · Adrian Weller
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #55
Generalization Properties of Learning with Random Features
Alessandro Rudi · Lorenzo Rosasco
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #56
Gaussian Quadrature for Kernel Features
Tri Dao · Christopher M De Sa · Christopher Ré
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #57
A Linear-Time Kernel Goodness-of-Fit Test
Wittawat Jitkrittum · Wenkai Xu · Zoltan Szabo · Kenji Fukumizu · Arthur Gretton
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #58
Convergence rates of a partition based Bayesian multivariate density estimation method
Linxi Liu · Dangna Li · Wing Hung Wong
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #59
The power of absolute discounting: all-dimensional distribution estimation
Moein Falahatgar · Mesrob Ohannessian · Alon Orlitsky · Venkatadheeraj Pichapati
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #60
Optimally Learning Populations of Parameters
Kevin Tian · Weihao Kong · Gregory Valiant
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #61
Communication-Efficient Distributed Learning of Discrete Distributions
Ilias Diakonikolas · Elena Grigorescu · Jerry Li · Abhiram Natarajan · Krzysztof Onak · Ludwig Schmidt
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #62
Improved Dynamic Regret for Non-degeneracy Functions
Lijun Zhang · Tianbao Yang · Jinfeng Yi · Rong Jin · Zhi-Hua Zhou
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #63
Parameter-Free Online Learning via Model Selection
Dylan J Foster · Satyen Kale · Mehryar Mohri · Karthik Sridharan
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #64
Fast Rates for Bandit Optimization with Upper-Confidence Frank-Wolfe
Quentin Berthet · Vianney Perchet
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #65
Online Learning with Transductive Regret
Scott Yang · Mehryar Mohri
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #66
Multi-Armed Bandits with Metric Movement Costs
Tomer Koren · Roi Livni · Yishay Mansour
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #67
Differentially Private Empirical Risk Minimization Revisited: Faster and More General
Di Wang · Minwei Ye · Jinhui Xu
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #68
Certified Defenses for Data Poisoning Attacks
Jacob Steinhardt · Pang Wei W Koh · Percy Liang
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #69
Sparse Approximate Conic Hulls
Greg Van Buskirk · Ben Raichel · Nicholas Ruozzi
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #70
On Tensor Train Rank Minimization : Statistical Efficiency and Scalable Algorithm
Masaaki Imaizumi · Takanori Maehara · Kohei Hayashi
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #71
Sparse convolutional coding for neuronal assembly detection
Sven Peter · Elke Kirschbaum · Martin Both · Intramural Lee Campbell · Intramural Brandon Harvey · Intramural Conor Heins · Daniel Durstewitz · Ferran Diego · Fred Hamprecht
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #72
Estimating High-dimensional Non-Gaussian Multiple Index Models via Stein’s Lemma
Zhuoran Yang · krishnakumar balasubramanian · Princeton Zhaoran Wang · Han Liu
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #73
Solid Harmonic Wavelet Scattering: Predicting Quantum Molecular Energy from Invariant Descriptors of 3D Electronic Densities
Michael Eickenberg · Georgios Exarchakis · Matthew Hirn · Stephane Mallat
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #74
Clustering Billions of Reads for DNA Data Storage
Cyrus Rashtchian · Konstantin Makarychev · Luis Ceze · Karin Strauss · Sergey Yekhanin · Djordje Jevdjic · Miklos Racz · Siena Ang
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #75
Deep Recurrent Neural Network-Based Identification of Precursor microRNAs
Seunghyun Park · Seonwoo Min · Hyun-Soo Choi · Sungroh Yoon
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #76
Decoding with Value Networks for Neural Machine Translation
Di He · Hanqing Lu · Yingce Xia · Tao Qin · Liwei Wang · Tieyan Liu
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #77
Towards the ImageNet-CNN of NLP: Pretraining Sentence Encoders with Machine Translation
Bryan McCann · James Bradbury · Caiming Xiong · Richard Socher
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #78
Deep Voice 2: Multi-Speaker Neural Text-to-Speech
Andrew Gibiansky
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #79
Modulating early visual processing by language
Harm de Vries · Florian Strub · Jeremie Mary · Hugo Larochelle · Olivier Pietquin · Aaron C Courville
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #80
Multimodal Learning and Reasoning for Visual Question Answering
Ilija Ilievski · Jiashi Feng
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #81
Learning to Model the Tail
Yu-Xiong Wang · Deva Ramanan · Martial Hebert
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #82
Interpretable and Globally Optimal Prediction for Textual Grounding using Image Concepts
Raymond Yeh · Jinjun Xiong · Wen-Mei Hwu · Minh Do · Alexander Schwing
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #83
Multiscale Quantization for Fast Similarity Search
Xiang Wu · Ruiqi Guo · Ananda Theertha Suresh · Daniel Holtmann-Rice · David Simcha · Felix Yu · Sanjiv Kumar
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #84
MaskRNN: Instance Level Video Object Segmentation
Yuan-Ting Hu · Jia-Bin Huang · Alexander Schwing
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #85
Flat2Sphere: Learning Spherical Convolution for Fast Features from 360° Imagery
Yu-Chuan Su · Kristen Grauman
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #86
Deep Mean-Shift Priors for Image Restoration
Siavash Arjomand Bigdeli · Matthias Zwicker · Paolo Favaro · Meiguang Jin
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #87
Pixels to Graphs by Associative Embedding
Alejandro Newell · Jia Deng
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #88
3D Shape Reconstruction by Modeling 2.5D Sketch
Jiajun Wu · Yifan Wang · Tianfan Xue · Xingyuan Sun · Bill Freeman · Josh Tenenbaum
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #89
Temporal Coherency based Criteria for Predicting Video Frames using Deep Multi-stage Generative Adversarial Networks
Prateep Bhattacharjee · Sukhendu Das
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #90
Learning to Generalize Intrinsic Images with a Structured Disentangling Autoencoder
Michael Janner · Jiajun Wu · Tejas Kulkarni · Ilker Yildirim · Josh Tenenbaum
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #91
Unsupervised object learning from dense equivariant image labelling
James Thewlis · Andrea Vedaldi · Hakan Bilen
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #92
One-Sided Unsupervised Domain Mapping
Sagie Benaim · Lior Wolf
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #93
Contrastive Learning for Image Captioning
Bo Dai · Dahua Lin
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #94
Dynamic Routing Between Capsules
Sara Sabour · Nicholas Frosst · Geoffrey E Hinton
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #95
What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision?
Alex Kendall · Yarin Gal
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #96
Efficient Optimization for Linear Dynamical Systems with Applications to Clustering and Sparse Coding
Wenbing Huang · Fuchun Sun · Tong Zhang · Junzhou Huang · Mehrtash Harandi
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #97
Label Distribution Learning Forests
Wei Shen · KAI ZHAO · Yilu Guo · Alan Yuille
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #98
Graph Matching via Multiplicative Update Algorithm
Bo Jiang · Jin Tang · Bin Luo
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #99
Training Quantized Nets: A Deeper Understanding
Hao Li · Soham De · Zheng Xu · Christoph Studer · Hanan Samet · Tom Goldstein
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #100
Inner-loop free ADMM using Auxiliary Deep Neural Networks
Kai Fan · Qi Wei · Katherine A Heller
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #101
Towards Accurate Binary Convolutional Neural Network
Wei Pan · Xiaofan Lin · Cong Zhao
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #102
Runtime Neural Pruning
Ji Lin · Yongming Rao · Jiwen Lu
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #103
Structured Embedding Models for Grouped Data
Maja Rudolph · Francisco Ruiz · David Blei
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #104
Poincaré Embeddings for Learning Hierarchical Representations
Maximillian Nickel · Douwe Kiela
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #105
Language modeling with recurrent highway hypernetworks
Joseph Suarez
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #106
Preventing Gradient Explosions in Gated Recurrent Units
Sekitoshi Kanai · Yasuhiro Fujiwara · Sotetsu Iwamura
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #107
Wider and Deeper, Cheaper and Faster: Tensorized LSTMs for Sequence Learning
Zhen He · Shaobing Gao · Liang Xiao · David Barber
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #108
Fast-Slow Recurrent Neural Networks
Asier Mujika · Florian Meier · Angelika Steger
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #109
Cold-Start Reinforcement Learning with Softmax Policy Gradients
Nan Ding · Radu Soricut
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #110
Deep Learning for Precipitation Nowcasting: A Benchmark and A New Model
Xingjian Shi · Hao Wang · Zhihan Gao · Leonard Lausen · Dit-Yan Yeung · Wang-chun WOO · Wai-kin Wong
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #111
Recurrent Ladder Networks
Isabeau Prémont-Schwarz · Alexander Ilin · Tele Hao · Antti Rasmus · Rinu Boney · Harri Valpola
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #112
Predictive-State Decoders: Encoding the Future into Recurrent Networks
Arun Venkatraman · Nicholas Rhinehart · Wen Sun · Lerrel Pinto · Martial Hebert · Byron Boots · Kris Kitani · J. Bagnell
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #113
QMDP-Net: Deep Learning for Planning under Partial Observability
Peter Karkus · David Hsu · Wee Sun Lee
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #114
Filtering Variational Objectives
Chris Maddison · John Lawson · George Tucker · Mohammad Norouzi · Nicolas Heess · Andriy Mnih · Yee Teh · Arnaud Doucet
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #115
Unsupervised Learning of Disentangled Latent Representations from Sequential Data
Wei-Ning Hsu · Yu Zhang · James Glass
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #116
Neural Discrete Representation Learning
Aaron van den Oord · Oriol Vinyals · koray kavukcuoglu
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #117
Variational Memory Addressing in Generative Models
Jörg Bornschein · Andriy Mnih · Daniel Zoran · Danilo Jimenez Rezende
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #118
Cortical microcircuits as gated-recurrent neural networks
Rui Costa · Ioannis Alexandros Assael · Brendan Shillingford · Nando de Freitas · TIm Vogels
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #119
Continual Learning with Deep Generative Replay
Hanul Shin · Jung Kwon Lee · Jaehong Kim · Jiwon Kim
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #120
Hierarchical Attentive Recurrent Tracking
Adam Kosiorek · Alex Bewley · Ingmar Posner
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #121
VAE Learning via Stein Variational Gradient Descent
Yuchen Pu · Zhe Gan · Ricardo Henao · Chunyuan Li · Shaobo Han · Lawrence Carin
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #122
Learning to Inpaint for Image Compression
Mohammad Haris Baig · Vladlen Koltun · Lorenzo Torresani
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #123
Visual Interaction Networks
Nicholas Watters · Daniel Zoran · Theophane Weber · Peter Battaglia · Razvan Pascanu · Andrea Tacchetti
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #124
NeuralFDR: Learning Discovery Thresholds from Hypothesis Features
Martin J Zhang · Fei Xia · James Zou · David Tse
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #125
Eigen-Distortions of Hierarchical Representations
Alexander Berardino · Valero Laparra · Johannes Ballé · Eero Simoncelli
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #126
On-the-fly Operation Batching in Dynamic Computation Graphs
Graham Neubig · Yoav Goldberg · Chris Dyer
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #127
Learning Affinity via Spatial Propagation Networks
Sifei Liu · Guangyu Zhong · Ming-Hsuan Yang · Shalini De Mello · Jan Kautz · Jinwei Gu
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #128
Supervised Adversarial Domain Adaptation
Saeid Motiian · Quinn Jones · Gianfranco Doretto
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #129
Deep Hyperspherical Learning
Weiyang Liu · Yan-Ming Zhang · Xingguo Li · Zhiding Yu · Bo Dai · Tuo Zhao · Le Song
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #130
Riemannian approach to batch normalization
Minhyung Cho · Jaehyung Lee
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #131
Backprop without Learning Rates Through Coin Betting
Francesco Orabona · Tatiana Tommasi
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #132
On the Convergence of Block Coordinate Descent in Training DNNs with Tikhonov Regularization
Ziming Zhang · Matthew Brand
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #133
Collaborative Deep Learning in Fixed Topology Networks
Zhanhong Jiang · Aditya Balu · Chinmay Hegde · Soumik Sarkar
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #134
How regularization affects the critical points in linear networks
Amirhossein Taghvaei · Jin W Kim · Prashant Mehta
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #135
Predicting Organic Reaction Outcomes with Weisfeiler-Lehman Network
Wengong Jin · Connor Coley · Regina Barzilay · Tommi Jaakkola
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #136
Predicting Scene Parsing and Motion Dynamics in the Future
Xiaojie Jin · Jiashi Feng · Huaxin Xiao · Yunpeng Chen · Shuicheng Yan · Xiaohui Shen · Jimei Yang · Zequn Jie · Li Ping
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #137
Houdini: Democratizing Adversarial Examples
Moustapha Cisse · Yossi Adi · Natalia Neverova · Joseph Keshet
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #138
Geometric Matrix Completion with Recurrent Multi-Graph Neural Networks
Federico Monti · Michael Bronstein · Xavier Bresson
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #139
Compression-aware Training of Deep Neural Networks
Jose Alvarez · Mathieu Salzmann
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #140
Non-parametric Neural Networks
Andreas Lehrmann · Leonid Sigal
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #141
GibbsNet: Iterative Adversarial Inference for Deep Graphical Models
Alex Lamb · Devon Hjelm · Yaroslav Ganin · Joseph Paul Cohen · Aaron C Courville · Yoshua Bengio
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #142
Exploring Generalization in Deep Learning
Behnam Neyshabur · Srinadh Bhojanapalli · Nati Srebro
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #143
Regularizing Deep Neural Networks by Noise: Its Interpretation and Optimization
Hyeonwoo Noh · Tackgeun You · Jonghwan Mun · Bohyung Han
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #144
Extracting low-dimensional dynamics from multiple large-scale neural population recordings by learning to predict correlations
Marcel Nonnenmacher · Srinivas C Turaga · Jakob H Macke
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #145
Adaptive sampling for a population of neurons
Benjamin Cowley · Ryan Williamson · Katerina Clemens · Matthew Smith · Byron M Yu
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #146
OnACID: Online Analysis of Calcium Imaging Data in Real Time
Andrea Giovannucci · Johannes Friedrich · Matt Kaufman · Anne Churchland · Dmitri Chklovskii · Liam Paninski · Eftychios Pnevmatikakis
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #147
Detrended Partial Cross Correlation for Brain Connectivity Analysis
Jaime Ide · Fábio Cappabianco · Fabio Faria · Chiang-shan R Li
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #148
Practical Bayesian Optimization for Model Fitting with Bayesian Adaptive Direct Search
Luigi Acerbi · Wei Ji
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #149
An Error Detection and Correction Framework for Connectomics
Jonathan Zung · Ignacio Tartavull
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #150
GP CaKe: Effective brain connectivity with causal kernels
Luca Ambrogioni · Max Hinne · Marcel Van Gerven · Eric Maris
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #151
Learning Neural Representations of Human Cognition across Many fMRI Studies
Arthur Mensch · Julien Mairal · Danilo Bzdok · Bertrand Thirion · Gael Varoquaux
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #152
Mapping distinct timescales of functional interactions among brain networks
Mali Sundaresan · Arshed Nabeel · Devarajan Sridharan
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #153
Robust Estimation of Neural Signals in Calcium Imaging
Hakan Inan · Murat A. Erdogdu · Mark Schnitzer
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #154
Learning the Morphology of Brain Signals Using Alpha-Stable Convolutional Sparse Coding
Mainak Jas · Tom Dupré la Tour · Umut Simsekli · Alexandre Gramfort
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #155
Streaming Weak Submodularity: Interpreting Neural Networks on the Fly
Ethan Elenberg · Alexandros Dimakis · Moran Feldman · Amin Karbasi
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #156
Decomposable Submodular Function Minimization: Discrete and Continuous
Alina Ene · Huy Nguyen · Laszlo Vegh
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #157
Differentiable Learning of Submodular Functions
Josip Djolonga · Andreas Krause
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #158
Robust Optimization for Non-Convex Objectives
Yaron Singer · Robert S Chen · Vasilis Syrgkanis · Brendan Lucier
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #159
On the Optimization Landscape of Tensor Decompositions
Rong Ge · Tengyu Ma
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #160
Gradient Descent Can Take Exponential Time to Escape Saddle Points
Simon Du · Chi Jin · Jason D Lee · Michael Jordan · Aarti Singh · Barnabas Poczos
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #161
Convolutional Phase Retrieval
Qing Qu · Yuqian Zhang · Yonina Eldar · John Wright
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #162
Implicit Regularization in Matrix Factorization
Suriya Gunasekar · Blake Woodworth · Srinadh Bhojanapalli · Behnam Neyshabur · Nati Srebro
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #163
Near-linear time approximation algorithms for optimal transport via Sinkhorn iteration
Jason Altschuler · Jonathan Weed · Philippe Rigollet
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #164
On Frank-Wolfe and Equilibrium Computation
Jacob D Abernethy · Jun-Kun Wang
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #165
Greedy Algorithms for Cone Constrained Optimization with Convergence Guarantees
Francesco Locatello · Michael Tschannen · Gunnar Raetsch · Martin Jaggi
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #166
When Cyclic Coordinate Descent Beats Randomized Coordinate Descent
Mert Gurbuzbalaban · Nuri Vanli · Asuman Ozdaglar
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #167
Linear Convergence of a Frank-Wolfe Type Algorithm over Trace-Norm Balls
Zeyuan Allen-Zhu · Elad Hazan · Wei Hu · Yuanzhi Li
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #168
Adaptive Accelerated Gradient Converging Method under H\"{o}lderian Error Bound Condition
Mingrui Liu · Tianbao Yang
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #169
Searching in the Dark: Practical SVRG Methods under Error Bound Conditions with Guarantee
Yi Xu · Qihang Lin · Tianbao Yang
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #170
Geometric Descent Method for Convex Composite Minimization
Shixiang Chen · Shiqian Ma · Wei Liu
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #171
Faster and Non-ergodic O(1/K) Stochastic Alternating Direction Method of Multipliers
Cong Fang · Feng Cheng · Zhouchen Lin
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #172
Doubly Accelerated Stochastic Variance Reduced Dual Averaging Method for Regularized Empirical Risk Minimization
Tomoya Murata · Taiji Suzuki
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #173
Limitations on Variance-Reduction and Acceleration Schemes for Finite Sums Optimization
Yossi Arjevani
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #174
Nonlinear Acceleration of Stochastic Algorithms
Damien Scieur · Francis Bach · Alexandre d'Aspremont
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #175
Acceleration and Averaging in Stochastic Descent Dynamics
Walid Krichene
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #176
Multiscale Semi-Markov Dynamics for Intracortical Brain-Computer Interfaces
Daniel Milstein · Jason Pacheco · Leigh Hochberg · John D Simeral · Beata Jarosiewicz · Erik Sudderth
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #177
EEG-GRAPH: A Factor Graph Based Model for Capturing Spatial, Temporal, and Observational Relationships in Electroencephalograms
Yogatheesan Varatharajah · Min Jin Chong · Krishnakant Saboo · Brent Berry · Benjamin Brinkmann · Gregory Worrell · Ravishankar Iyer
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #178
Asynchronous Parallel Coordinate Minimization for MAP Inference
Ofer Meshi · Alexander Schwing
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #179
Speeding Up Latent Variable Gaussian Graphical Model Estimation via Nonconvex Optimization
Pan Xu · Jian Ma · Quanquan Gu
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #180
The Expxorcist: Nonparametric Graphical Models Via Conditional Exponential Densities
Arun Suggala · Mladen Kolar · Pradeep Ravikumar
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #181
Reducing Reparameterization Gradient Variance
Andrew Miller · Nick Foti · Alexander D'Amour · Ryan Adams
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #182
Robust Conditional Probabilities
Yoav Wald · Amir Globerson
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #183
Stein Variational Gradient Descent as Gradient Flow
Qiang Liu
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #184
Parallel Streaming Wasserstein Barycenters
Matthew Staib · Sebastian Claici · Justin M Solomon · Stefanie Jegelka
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #185
AIDE: An algorithm for measuring the accuracy of probabilistic inference algorithms
Marco Cusumano-Towner · Vikash K Mansinghka
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #186
Deep Dynamic Poisson Factorization Model
Chengyue Gong · win-bin huang
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #187
On the Model Shrinkage Effect of Gamma Process Edge Partition Models
Iku Ohama · Issei Sato · Takuya Kida · Hiroki Arimura
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #188
Model evidence from nonequilibrium simulations
Michael Habeck
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #189
A-NICE-MC: Adversarial Training for MCMC
Jiaming Song · Shengjia Zhao · Stefano Ermon
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #190
Identification of Gaussian Process State Space Models
Stefanos Eleftheriadis · Tom Nicholson · Marc Deisenroth · James Hensman
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #191
Streaming Sparse Gaussian Process Approximations
Thang D Bui · Cuong Nguyen · Richard E Turner
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #192
Bayesian Optimization with Gradients
Jian Wu · Matthias Poloczek · Andrew Wilson · Peter Frazier
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #193
Variational Inference for Gaussian Process Models with Linear Complexity
Ching-An Cheng · Byron Boots
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #194
Efficient Modeling of Latent Information in Supervised Learning using Gaussian Processes
Zhenwen Dai · Mauricio A. Álvarez · Neil Lawrence
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #195
Non-Stationary Spectral Kernels
Sami Remes · Markus Heinonen · Samuel Kaski
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #196
Scalable Log Determinants for Gaussian Process Kernel Learning
David Eriksson · Kun Dong · David Bindel · Andrew Wilson · Hannes Nickisch
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #197
Spectral Mixture Kernels for Multi-Output Gaussian Processes
Gabriel Parra · Felipe Tobar
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #198
Linearly constrained Gaussian processes
Carl Jidling · Niklas Wahlström · Adrian Wills · Thomas B Schön
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #199
Hindsight Experience Replay
Marcin Andrychowicz · Filip Wolski · Alex Ray · Jonas Schneider · Rachel Fong · Peter Welinder · Bob McGrew · Josh Tobin · OpenAI Pieter Abbeel · Wojciech Zaremba
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #200
Log-normality and Skewness of Estimated State/Action Values in Reinforcement Learning
Liangpeng Zhang · Ke Tang · Xin Yao
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #201
Finite sample analysis of the GTD Policy Evaluation Algorithms in Markov Setting
Yue Wang
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #202
Inverse Filtering for Hidden Markov Models
Robert Mattila · Cristian Rojas · Vikram Krishnamurthy · Bo Wahlberg
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #203
Safe Model-based Reinforcement Learning with Stability Guarantees
Felix Berkenkamp · Matteo Turchetta · Angela Schoellig · Andreas Krause
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #204
Data-Efficient Reinforcement Learning in Continuous State-Action Gaussian-POMDPs
Rowan McAllister · Carl Edward Rasmussen
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #205
Linear regression without correspondence
Daniel Hsu · Kevin Shi · Xiaorui Sun
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #206
On the Complexity of Learning Neural Networks
Le Song · Santosh Vempala · John Wilmes · Bo Xie
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #207
Near Optimal Sketching of Low-Rank Tensor Regression
Jarvis Haupt · Xingguo Li · David Woodruff
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #208
Is Input Sparsity Time Possible for Kernel Low-Rank Approximation?
Cameron Musco · David Woodruff
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #209
Higher-Order Total Variation Classes on Grids: Minimax Theory and Trend Filtering Methods
Veeranjaneyulu Sadhanala · Yu-Xiang Wang · James Sharpnack · Ryan Tibshirani
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #210
Alternating Estimation for Structured High-Dimensional Multi-Response Models
Sheng Chen · Arindam Banerjee
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #211
Adaptive Clustering through Semidefinite Programming
Martin Royer
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #212
Compressing the Gram Matrix for Learning Neural Networks in Polynomial Time
Surbhi Goel · Adam Klivans
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #213
Learning with Average Top-k Loss
Yanbo Fan · Siwei Lyu · Yiming Ying · Baogang Hu
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #214
Hierarchical Clustering Beyond the Worst-Case
Vincent Cohen-Addad · Varun Kanade · Frederik Mallmann-Trenn
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #215
Net-Trim: Convex Pruning of Deep Neural Networks with Performance Guarantee
Alireza Aghasi · Nam Nguyen · Justin Romberg
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #216
A graph-theoretic approach to multitasking
Noga Alon · Daniel Reichman · Igor Shinkar · Tal Wagner · Sebastian Musslick · Tom Griffiths · Jonathan D Cohen · Biswadip dey · Kayhan Ozcimder
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #217
Information-theoretic analysis of generalization capability of learning algorithms
Maxim Raginsky · Aolin Xu
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #218
Independence clustering (without a matrix)
Daniil Ryabko
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #219
Polynomial Codes: an Optimal Design for High-Dimensional Coded Matrix Multiplication
Qian Yu · Mohammad Maddah-Ali · Salman Avestimehr
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #220
Estimating Mutual Information for Discrete-Continuous Mixtures
Weihao Gao · Sreeram Kannan · Sewoong Oh · Pramod Viswanath
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #221
Best Response Regression
Omer Ben Porat · Moshe Tennenholtz
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #222
Statistical Cost Sharing
Eric Balkanski · Umar Syed · Sergei Vassilvitskii
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #223
A Sample Complexity Measure with Applications to Learning Optimal Auctions
Vasilis Syrgkanis
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #224
Multiplicative Weights Update with Constant Step-Size in Congestion Games: Convergence, Limit Cycles and Chaos
Gerasimos Palaiopanos · Ioannis Panageas · Georgios Piliouras
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #225
Efficiency Guarantees from Data
Darrell Hoy · Denis Nekipelov · Vasilis Syrgkanis
Poster
Tue Dec 5th 06:30 -- 10:30 PM @ Pacific Ballroom #226
Safe and Nested Subgame Solving for Imperfect-Information Games
Noam Brown · Tuomas Sandholm
Demonstration
Tue Dec 5th 07:00 -- 10:30 PM @ Pacific Ballroom Concourse # D1
A Deep Reinforcement Learning Chatbot
Iulian Vlad Serban · Chinnadhurai Sankar · Mathieu Germain · Saizheng Zhang · Zhouhan Lin · Sandeep Subramanian · Taesup Kim · Michael J Pieper · Sarath Chandar · Nan Ke · Sai Rajeswar Mudumba · Alexandre de Brébisson · Jose Sotelo · Dendi A Suhubdy · Vincent Michalski · Joelle Pineau · Yoshua Bengio
Demonstration
Tue Dec 5th 07:00 -- 10:30 PM @ Pacific Ballroom Concourse #D2
CTRL-Labs: Non-invasive Neural Interface
Patrick Kaifosh · Tudor Giurgica-Tiron · Alan Du · Adam Al-natsheh · Jeffrey Seely · Steven Demers
Demonstration
Tue Dec 5th 07:00 -- 10:30 PM @ Pacific Ballroom Concourse #D3
TincyYolo: Smaller still, faster, and more efficient
Michaela Blott · Nicholas Fraser
Demonstration
Tue Dec 5th 07:00 -- 10:30 PM @ Pacific Ballroom Concourse, #D4
A cortical neural network simulator for kids
Michiro Negishi
Demonstration
Tue Dec 5th 07:00 -- 10:30 PM @ Pacific Ballroom Concourse #D5
Libratus: Beating Top Humans in No-Limit Poker
Noam Brown · Tuomas Sandholm
Demonstration
Tue Dec 5th 07:00 -- 10:30 PM @ Pacific Ballroom Concourse #D6
Deep Robotic Learning using Visual Imagination and Meta-Learning
Chelsea Finn · Frederik Ebert · Tianhe Yu · Annie Xie · Sudeep Dasari · Pieter Abbeel · Sergey Levine
Demonstration
Tue Dec 5th 07:00 -- 10:30 PM @ Pacific Ballroom Concourse #D7
Conversational Speech Search on Massive Audio Datasets
Anthony Scodary · Wonkyum Lee · Nico Benitez · Samuel Kim
Demonstration
Tue Dec 5th 07:00 -- 10:30 PM @ Pacific Ballroom Concourse #D8
Symbol Grounding and Program Induction using Multi-modal instructions, Visual Cues and Eye Tracking.
Yordan Hristov · Emmanuel Kahembwe · Subramanian Ramamoorthy
Demonstration
Tue Dec 5th 07:00 -- 10:30 PM @ Pacific Ballroom Concourse #D9
Sensomind: Democratizing deep learning for the food industry
Michael Sass Hansen · Sebastian Brandes Kraaijenzank
Demonstration
Tue Dec 5th 07:00 -- 10:30 PM @ Pacific Ballroom Concourse #D10
Deep Neural Net implementations with FPGAs
Thomas Boser · Paolo Calafiura · Ian Johnson
Break
Wed Dec 6th 07:30 -- 09:00 AM @
coffee, no breakfast served
Invited Talk
Wed Dec 6th 09:00 -- 09:50 AM @ Hall A
The Unreasonable Effectiveness of Structure
Lise Getoor
Break
Wed Dec 6th 09:50 -- 10:20 AM @
Coffee Break
Oral
Wed Dec 6th 10:20 -- 10:35 AM @ Hall A
On Structured Prediction Theory with Calibrated Convex Surrogate Losses
Anton Osokin · Francis Bach · Simon Lacoste-Julien
Oral
Wed Dec 6th 10:20 -- 10:35 AM @ Hall C
TernGrad: Ternary Gradients to Reduce Communication in Distributed Deep Learning
Wei Wen · Cong Xu · Feng Yan · Chunpeng Wu · Yandan Wang · Yiran Chen · Hai Li
Oral
Wed Dec 6th 10:35 -- 10:50 AM @ Hall A
REBAR: Low-variance, unbiased gradient estimates for discrete latent variable models
George Tucker · Andriy Mnih · Chris J Maddison · John Lawson · Jascha Sohl-Dickstein
Oral
Wed Dec 6th 10:35 -- 10:50 AM @ Hall C
Train longer, generalize better: closing the generalization gap in large batch training of neural networks
Elad Hoffer · Itay Hubara · Daniel Soudry
Oral
Wed Dec 6th 10:50 -- 11:05 AM @ Hall A
Variance-based Regularization with Convex Objectives
Hongseok Namkoong · John C Duchi
Oral
Wed Dec 6th 10:50 -- 11:05 AM @ Hall C
End-to-end Differentiable Proving
Tim Rocktäschel · Sebastian Riedel
Oral
Wed Dec 6th 11:05 -- 11:20 AM @ Hall A
Online control of the false discovery rate with decaying memory
Aaditya Ramdas · Fanny Yang · Martin Wainwright · Michael Jordan
Oral
Wed Dec 6th 11:05 -- 11:20 AM @ Hall C
Gradient descent GAN optimization is locally stable
Vaishnavh Nagarajan · J. Zico Kolter
Spotlight
Wed Dec 6th 11:20 -- 11:25 AM @ Hall A
Submultiplicative Glivenko-Cantelli and Uniform Convergence of Revenues
Noga Alon · Moshe Babaioff · Yannai A. Gonczarowski · Yishay Mansour · Shay Moran · Amir Yehudayoff
Spotlight
Wed Dec 6th 11:20 -- 11:25 AM @ Hall C
f-GANs in an Information Geometric Nutshell
Richard Nock · Zac Cranko · Aditya K Menon · Lizhen Qu · Robert C Williamson
Spotlight
Wed Dec 6th 11:25 -- 11:30 AM @ Hall A
Fast Black-box Variational Inference through Stochastic Trust-Region Optimization
Jeffrey Regier · Michael Jordan · Jon McAuliffe
Spotlight
Wed Dec 6th 11:25 -- 11:30 AM @ Hall C
Unsupervised Image-to-Image Translation Networks
Ming-Yu Liu · Thomas Breuel · Jan Kautz
Spotlight
Wed Dec 6th 11:30 -- 11:35 AM @ Hall A
A Universal Analysis of Large-Scale Regularized Least Squares Solutions
Ashkan Panahi · Babak Hassibi
Spotlight
Wed Dec 6th 11:30 -- 11:35 AM @ Hall C
The Numerics of GANs
Lars Mescheder · Sebastian Nowozin · Andreas Geiger
Spotlight
Wed Dec 6th 11:35 -- 11:40 AM @ Hall A
A Disentangled Recognition and Nonlinear Dynamics Model for Unsupervised Learning
Marco Fraccaro · Simon Kamronn · Ulrich Paquet · Ole Winther
Spotlight
Wed Dec 6th 11:35 -- 11:40 AM @ Hall C
Dual Discriminator Generative Adversarial Nets
Tu Nguyen · Trung Le · Hung Vu · Dinh Phung
Spotlight
Wed Dec 6th 11:40 -- 11:45 AM @ Hall A
Accelerated Stochastic Greedy Coordinate Descent by Soft Thresholding Projection onto Simplex
Chaobing Song · Shaobo Cui · Shu-Tao Xia · Yong Jiang
Spotlight
Wed Dec 6th 11:40 -- 11:45 AM @ Hall C
Bayesian GANs
Yunus Saatci · Andrew Wilson
Spotlight
Wed Dec 6th 11:45 -- 11:50 AM @ Hall A
Early stopping for kernel boosting algorithms: A general analysis with localized complexities
Yuting Wei · Fanny Yang · Martin Wainwright
Spotlight
Wed Dec 6th 11:45 -- 11:50 AM @ Hall C
Approximation and Convergence Properties of Generative Adversarial Learning
Shuang Liu · Olivier Bousquet · Kamalika Chaudhuri
Spotlight
Wed Dec 6th 11:50 -- 11:55 AM @ Hall A
Spectrally-normalized margin bounds for neural networks
Matus Telgarsky · Peter Bartlett · Dylan J Foster
Spotlight
Wed Dec 6th 11:50 -- 11:55 AM @ Hall C
Dualing GANs
Yujia Li · Alexander Schwing · Kuan-Chieh Wang · Richard Zemel
Spotlight
Wed Dec 6th 11:55 AM -- 12:00 PM @ Hall A
The Scaling Limit of High-Dimensional Online Independent Component Analysis
Chuang Wang · Yue Lu
Spotlight
Wed Dec 6th 11:55 AM -- 12:00 PM @ Hall C
Generalizing GANs: A Turing Perspective
Roderich Gross · Yue Gu · Wei Li · Melvin Gauci
Invited Talk
Wed Dec 6th 01:50 -- 02:40 PM @ Hall A
Deep Learning for Robotics
Pieter Abbeel
Oral
Wed Dec 6th 02:50 -- 03:05 PM @ Hall A
ELF: An Extensive, Lightweight and Flexible Research Platform for Real-time Strategy Games
Yuandong Tian · Qucheng Gong · Wenling Shang · Yuxin Wu · C. Lawrence Zitnick
Oral
Wed Dec 6th 02:50 -- 03:05 PM @ Hall C
The Marginal Value of Adaptive Gradient Methods in Machine Learning
Ashia C Wilson · Rebecca Roelofs · Mitchell Stern · Nati Srebro · Benjamin Recht
Oral
Wed Dec 6th 03:05 -- 03:20 PM @ Hall A
Imagination-Augmented Agents for Deep Reinforcement Learning
Sébastien Racanière · David Reichert · Theophane Weber · Oriol Vinyals · Daan Wierstra · Lars Buesing · Peter Battaglia · Razvan Pascanu · Yujia Li · Nicolas Heess · Arthur Guez · Danilo Jimenez Rezende · Adrià Puigdomènech Badia · David Silver
Oral
Wed Dec 6th 03:05 -- 03:20 PM @ Hall C
Can Decentralized Algorithms Outperform Centralized Algorithms? A Case Study for Decentralized Parallel Stochastic Gradient Descent
Xiangru Lian · Ce Zhang · Huan Zhang · Cho-Jui Hsieh · Wei Zhang · Ji Liu
Spotlight
Wed Dec 6th 03:20 -- 03:25 PM @ Hall A
Dual Path Networks
Yunpeng Chen · Jianan Li · Huaxin Xiao · Xiaojie Jin · Shuicheng Yan · Jiashi Feng
Spotlight
Wed Dec 6th 03:20 -- 03:25 PM @ Hall C
Breaking the Nonsmooth Barrier: A Scalable Parallel Method for Composite Optimization
Fabian Pedregosa · Rémi Leblond · Simon Lacoste-Julien
Spotlight
Wed Dec 6th 03:25 -- 03:30 PM @ Hall A
A simple neural network module for relational reasoning
Adam Santoro · David Raposo · David Barrett · Mateusz Malinowski · Razvan Pascanu · Peter Battaglia · Tim Lillicrap
Spotlight
Wed Dec 6th 03:25 -- 03:30 PM @ Hall C
Stochastic Optimization with Variance Reduction for Infinite Datasets with Finite Sum Structure
Alberto Bietti · Julien Mairal
Spotlight
Wed Dec 6th 03:30 -- 03:35 PM @ Hall A
Second-order Optimization in Deep Reinforcement Learning using Kronecker-factored Approximation
Yuhuai Wu · Elman Mansimov · Roger Grosse · Shun Liao · Jimmy Ba
Spotlight
Wed Dec 6th 03:30 -- 03:35 PM @ Hall C
Process-constrained batch Bayesian optimisation
Pratibha Vellanki · Santu Rana · Sunil Gupta · David Rubin · Alessandra Sutti · Thomas Dorin · Murray Height · Paul Sanders · Svetha Venkatesh
Spotlight
Wed Dec 6th 03:35 -- 03:40 PM @ Hall A
Attention is All you Need
Ashish Vaswani · Noam Shazeer · Niki Parmar · Llion Jones · Jakob Uszkoreit · Aidan N Gomez · Łukasz Kaiser
Spotlight
Wed Dec 6th 03:35 -- 03:40 PM @ Hall C
Safe Adaptive Importance Sampling
Sebastian Stich · Anant Raj · Martin Jaggi
Spotlight
Wed Dec 6th 03:40 -- 03:45 PM @ Hall A
Learning Combinatorial Optimization Algorithms over Graphs
Elias Khalil · Hanjun Dai · Yuyu Zhang · Bistra Dilkina · Le Song
Spotlight
Wed Dec 6th 03:40 -- 03:45 PM @ Hall C
Beyond Worst-case: A Probabilistic Analysis of Affine Policies in Dynamic Optimization
Omar El Housni · Vineet Goyal
Spotlight
Wed Dec 6th 03:45 -- 03:50 PM @ Hall A
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles
Balaji Lakshminarayanan · Alexander Pritzel · Charles Blundell
Spotlight
Wed Dec 6th 03:45 -- 03:50 PM @ Hall C
Straggler Mitigation in Distributed Optimization Through Data Encoding
Can Karakus · Yifan Sun · Suhas Diggavi · Wotao Yin
Break
Wed Dec 6th 03:50 -- 04:20 PM @
Coffee Break
Oral
Wed Dec 6th 04:20 -- 04:35 PM @ Hall A
Off-policy evaluation for slate recommendation
Adith Swaminathan · Akshay Krishnamurthy · Alekh Agarwal · Miro Dudik · John Langford · Damien Jose · Imed Zitouni
Oral
Wed Dec 6th 04:20 -- 04:35 PM @ Hall C
What-If Reasoning using Counterfactual Gaussian Processes
Peter Schulam · Suchi Saria
Oral
Wed Dec 6th 04:35 -- 04:50 PM @ Hall A
Robust and Efficient Transfer Learning with Hidden Parameter Markov Decision Processes
Samuel Daulton · Taylor Killian · Finale Doshi-Velez · George Konidaris
Oral
Wed Dec 6th 04:35 -- 04:50 PM @ Hall C
Convolutional Gaussian Processes
Mark van der Wilk · Carl Edward Rasmussen · James Hensman
Oral
Wed Dec 6th 04:50 -- 05:05 PM @ Hall A
Inverse Reward Design
Dylan Hadfield-Menell · Smitha Milli · Stuart J Russell · Pieter Abbeel · Anca Dragan
Oral
Wed Dec 6th 04:50 -- 05:05 PM @ Hall C
Counterfactual Fairness
Matt Kusner · Joshua Loftus · Chris Russell · Ricardo Silva
Spotlight
Wed Dec 6th 05:05 -- 05:10 PM @ Hall A
Dynamic Safe Interruptibility for Decentralized Multi-Agent Reinforcement Learning
El Mahdi El Mhamdi · Rachid Guerraoui · Hadrien Hendrikx · Alexandre Maurer
Spotlight
Wed Dec 6th 05:05 -- 05:10 PM @ Hall C
An Empirical Bayes Approach to Optimizing Machine Learning Algorithms
James McInerney
Spotlight
Wed Dec 6th 05:10 -- 05:15 PM @ Hall A
Unifying PAC and Regret: Uniform PAC Bounds for Episodic Reinforcement Learning
Christoph Dann · Tor Lattimore · Emma Brunskill
Spotlight
Wed Dec 6th 05:10 -- 05:15 PM @ Hall C
PASS-GLM: polynomial approximate sufficient statistics for scalable Bayesian GLM inference
Jonathan Huggins · Ryan Adams · Tamara Broderick
Spotlight
Wed Dec 6th 05:15 -- 05:20 PM @ Hall A
Repeated Inverse Reinforcement Learning
Kareem Amin · Nan Jiang · Satinder Singh
Spotlight
Wed Dec 6th 05:15 -- 05:20 PM @ Hall C
Multiresolution Kernel Approximation for Gaussian Process Regression
Yi Ding · Risi Kondor · Jonathan Eskreis-Winkler
Spotlight
Wed Dec 6th 05:20 -- 05:25 PM @ Hall A
Learning multiple visual domains with residual adapters
Sylvestre-Alvise Rebuffi · Hakan Bilen · Andrea Vedaldi
Spotlight
Wed Dec 6th 05:20 -- 05:25 PM @ Hall C
Multi-Information Source Optimization
Matthias Poloczek · Jialei Wang · Peter Frazier
Spotlight
Wed Dec 6th 05:25 -- 05:30 PM @ Hall A
Natural value approximators: learning when to trust past estimates
Tom Schaul · Zhongwen Xu · Joseph Modayil · Hado van Hasselt · Andre Barreto · David Silver
Spotlight
Wed Dec 6th 05:25 -- 05:30 PM @ Hall C
Doubly Stochastic Variational Inference for Deep Gaussian Processes
Hugh Salimbeni · Marc Deisenroth
Spotlight
Wed Dec 6th 05:30 -- 05:35 PM @ Hall A
EX2: Exploration with Exemplar Models for Deep Reinforcement Learning
Justin Fu · John Co-Reyes · Sergey Levine
Spotlight
Wed Dec 6th 05:30 -- 05:35 PM @ Hall C
Permutation-based Causal Inference Algorithms with Interventions
Yuhao Wang · Liam Solus · Karren Yang · Caroline Uhler
Spotlight
Wed Dec 6th 05:35 -- 05:40 PM @ Hall A
Regret Minimization in MDPs with Options without Prior Knowledge
Ronan Fruit · Matteo Pirotta · Alessandro Lazaric · Emma Brunskill
Spotlight
Wed Dec 6th 05:35 -- 05:40 PM @ Hall C
Gradients of Generative Models for Improved Discriminative Analysis of Tandem Mass Spectra
John T Halloran · David M Rocke
Spotlight
Wed Dec 6th 05:40 -- 05:45 PM @ Hall A
Successor Features for Transfer in Reinforcement Learning
Andre Barreto · Will Dabney · Remi Munos · Jonathan Hunt · Tom Schaul · David Silver · Hado van Hasselt
Spotlight
Wed Dec 6th 05:40 -- 05:45 PM @ Hall C
Style Transfer from Non-parallel Text by Cross-Alignment
Tianxiao Shen · Tao Lei · Regina Barzilay · Tommi Jaakkola
Spotlight
Wed Dec 6th 05:45 -- 05:50 PM @ Hall A
Overcoming Catastrophic Forgetting by Incremental Moment Matching
Sang-Woo Lee · Jin-Hwa Kim · Jaehyun Jun · Jung-Woo Ha · Byoung-Tak Zhang
Spotlight
Wed Dec 6th 05:45 -- 05:50 PM @ Hall C
Premise Selection for Theorem Proving by Deep Graph Embedding
Mingzhe Wang · Yihe Tang · Jian Wang · Jia Deng
Spotlight
Wed Dec 6th 05:50 -- 05:55 PM @ Hall A
Fair Clustering Through Fairlets
Flavio Chierichetti · Ravi Kumar · Silvio Lattanzi · Sergei Vassilvitskii
Spotlight
Wed Dec 6th 05:50 -- 05:55 PM @ Hall C
Deep Multi-task Gaussian Processes for Survival Analysis with Competing Risks
Ahmed M. Alaa · Mihaela van der Schaar
Spotlight
Wed Dec 6th 05:55 -- 06:00 PM @ Hall A
Fitting Low-Rank Tensors in Constant Time
Kohei Hayashi · Yuichi Yoshida
Spotlight
Wed Dec 6th 05:55 -- 06:00 PM @ Hall C
Unsupervised Learning of Disentangled Representations from Video
Emily Denton · vighnesh Birodkar
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #1
Deep Reinforcement Learning from Human Preferences
Paul F Christiano · Jan Leike · Tom Brown · Miljan Martic · Shane Legg · Dario Amodei
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #2
Multi-Modal Imitation Learning from Unstructured Demonstrations using Generative Adversarial Nets
Karol Hausman · Yevgen Chebotar · Stefan Schaal · Gaurav Sukhatme · Joseph J Lim
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #3
EX2: Exploration with Exemplar Models for Deep Reinforcement Learning
Justin Fu · John Co-Reyes · Sergey Levine
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #4
#Exploration: A Study of Count-Based Exploration for Deep Reinforcement Learning
Haoran Tang · Pieter Abbeel · Davis Foote · Yan Duan · OpenAI Xi Chen · Rein Houthooft · Adam Stooke · Filip DeTurck
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #5
Thinking Fast and Slow with Deep Learning and Tree Search
Thomas Anthony · Zheng Tian · David Barber
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #6
Natural value approximators: learning when to trust past estimates
Tom Schaul · Zhongwen Xu · Joseph Modayil · Hado van Hasselt · Andre Barreto · David Silver
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #7
Active Exploration for Learning Symbolic Representations
Garrett Andersen · George Konidaris
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #8
State Aware Imitation Learning
Yannick Schroecker · Charles L Isbell
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #9
Successor Features for Transfer in Reinforcement Learning
Andre Barreto · Will Dabney · Remi Munos · Jonathan Hunt · Tom Schaul · David Silver · Hado van Hasselt
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #10
Bridging the Gap Between Value and Policy Based Reinforcement Learning
Ofir Nachum · Mohammad Norouzi · Kelvin Xu · Dale Schuurmans
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #11
Using Options and Covariance Testing for Long Horizon Off-Policy Policy Evaluation
Zhaohan Guo · Philip S. Thomas · Emma Brunskill
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #12
Compatible Reward Inverse Reinforcement Learning
Alberto Maria Metelli · Matteo Pirotta · Marcello Restelli
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #13
Adaptive Batch Size for Safe Policy Gradients
Matteo Papini · Matteo Pirotta · Marcello Restelli
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #14
Regret Minimization in MDPs with Options without Prior Knowledge
Ronan Fruit · Matteo Pirotta · Alessandro Lazaric · Emma Brunskill
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #15
Is the Bellman residual a bad proxy?
Matthieu Geist · Bilal Piot · Olivier Pietquin
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #16
Learning Unknown Markov Decision Processes: A Thompson Sampling Approach
Yi Ouyang · Mukul Gagrani · Ashutosh Nayyar · Rahul Jain
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #17
Online Reinforcement Learning in Stochastic Games
Chen-Yu Wei · Yi-Te Hong · Chi-Jen Lu
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #18
Reinforcement Learning under Model Mismatch
Aurko Roy · Huan Xu · Sebastian Pokutta
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #19
Zap Q-Learning
Adithya M Devraj · Sean Meyn
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #20
Ensemble Sampling
Xiuyuan Lu · Benjamin Van Roy
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #21
Action Centered Contextual Bandits
Kristjan Greenewald · Ambuj Tewari · Susan Murphy · Predag Klasnja
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #22
Conservative Contextual Linear Bandits
Abbas Kazerouni · Mohammad Ghavamzadeh · Yasin Abbasi · Benjamin Van Roy
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #23
Rotting Bandits
Nir Levine · Koby Crammer · Shie Mannor
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #24
Identifying Outlier Arms in Multi-Armed Bandit
Honglei Zhuang · Chi Wang · Yifan Wang
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #25
Multi-Task Learning for Contextual Bandits
Aniket Anand Deshmukh · Urun Dogan · Clay Scott
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #26
Boltzmann Exploration Done Right
Nicolò Cesa-Bianchi · Claudio Gentile · Gergely Neu · Gabor Lugosi
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #27
Improving the Expected Improvement Algorithm
Chao Qin · Diego Klabjan · Daniel Russo
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #28
A KL-LUCB algorithm for Large-Scale Crowdsourcing
Ervin Tanczos · Robert Nowak · Bob Mankoff
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #29
Scalable Generalized Linear Bandits: Online Computation and Hashing
Kwang-Sung Jun · Aniruddha Bhargava · Robert Nowak · Rebecca Willett
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #30
Bandits Dueling on Partially Ordered Sets
Julien Audiffren · Liva Ralaivola
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #31
Position-based Multiple-play Multi-armed Bandit Problem with Unknown Position Bias
Junpei Komiyama · Junya Honda · Akiko Takeda
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #32
Online Influence Maximization under Independent Cascade Model with Semi-Bandit Feedback
Zheng Wen · Branislav Kveton · Michal Valko · Sharan Vaswani
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #33
A Scale Free Algorithm for Stochastic Bandits with Bounded Kurtosis
Tor Lattimore
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #34
Adaptive Active Hypothesis Testing under Limited Information
Fabio Cecchi · Nidhi Hegde
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #35
Near-Optimal Edge Evaluation in Explicit Generalized Binomial Graphs
Sanjiban Choudhury · Shervin Javdani · Siddhartha Srinivasa · Sebastian Scherer
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #36
Robust and Efficient Transfer Learning with Hidden Parameter Markov Decision Processes
Samuel Daulton · Taylor Killian · Finale Doshi-Velez · George Konidaris
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #37
Overcoming Catastrophic Forgetting by Incremental Moment Matching
Sang-Woo Lee · Jin-Hwa Kim · Jaehyun Jun · Jung-Woo Ha · Byoung-Tak Zhang
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #38
Hypothesis Transfer Learning via Transformation Functions
Simon Du · Jayanth Koushik · Aarti Singh · Barnabas Poczos
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #39
Learning multiple visual domains with residual adapters
Sylvestre-Alvise Rebuffi · Hakan Bilen · Andrea Vedaldi
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #40
Self-supervised Learning of Motion Capture
Hsiao-Yu Tung · Hsiao-Wei Tung · Ersin Yumer · Katerina Fragkiadaki
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #41
Information Theoretic Properties of Markov Random Fields, and their Algorithmic Applications
Linus Hamilton · Frederic Koehler · Ankur Moitra
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #42
Maximizing Subset Accuracy with Recurrent Neural Networks in Multi-label Classification
Jinseok Nam · Eneldo Loza Mencía · Hyunwoo J Kim · Johannes Fürnkranz
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #43
Local Aggregative Games
Vikas Garg · Tommi Jaakkola
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #44
An Empirical Bayes Approach to Optimizing Machine Learning Algorithms
James McInerney
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #45
Learning Chordal Markov Networks via Branch and Bound
Kari Rantanen · Antti Hyttinen · Matti Järvisalo
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #46
Optimal Sample Complexity of M-wise Data for Top-K Ranking
Minje Jang · Sunghyun Kim · Changho Suh · Sewoong Oh
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #47
Translation Synchronization via Truncated Least Squares
Xiangru Huang · Zhenxiao Liang · Chandrajit Bajaj · Qixing Huang
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #48
From Bayesian Sparsity to Gated Recurrent Nets
Hao He · Bo Xin · David Wipf
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #49
Online Learning for Multivariate Hawkes Processes
Yingxiang Yang · Jalal Etesami · Niao He · Negar Kiyavash
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #50
Efficient Second-Order Online Kernel Learning with Adaptive Embedding
Daniele Calandriello · Michal Valko · Alessandro Lazaric
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #51
Online to Offline Conversions and Adaptive Minibatch Sizes
Kfir Levy
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #52
Nonparametric Online Regression while Learning the Metric
Ilja Kuzborskij · Nicolò Cesa-Bianchi
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #53
Stochastic and Adversarial Online Learning without Hyperparameters
Ashok Cutkosky · Kwabena A Boahen
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #54
Affine-Invariant Online Optimization
Tomer Koren · Roi Livni
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #55
Online Convex Optimization with Stochastic Constraints
Hao Yu · Michael Neely · Xiaohan Wei
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #56
Online Learning with a Hint
Ofer Dekel · arthur flajolet · Nika Haghtalab · Patrick Jaillet
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #57
Efficient Online Linear Optimization with Approximation Algorithms
Dan Garber
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #58
Random Permutation Online Isotonic Regression
Wojciech Kotlowski · Wouter Koolen · Alan Malek
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #59
Minimax Optimal Players for the Finite-Time 3-Expert Prediction Problem
Yasin Abbasi · Peter Bartlett · Victor Gabillon
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #60
Online Learning of Optimal Bidding Strategy in Repeated Multi-Commodity Auctions
M. Sevi Baltaoglu · Lang Tong · Qing Zhao
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #61
Online Prediction with Selfish Experts
Tim Roughgarden · Okke Schrijvers
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #62
Real-Time Bidding with Side Information
arthur flajolet · Patrick Jaillet
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #63
Improving Regret Bounds for Combinatorial Semi-Bandits with Probabilistically Triggered Arms and Its Applications
Qinshi Wang · Wei Chen
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #64
A General Framework for Robust Interactive Learning
Ehsan Emamjomeh-Zadeh · David Kempe
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #65
Practical Locally Private Heavy Hitters
kobbi nissim · Raef Bassily · Uri Stemmer · Abhradeep Guha Thakurta
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #66
Deanonymization in the Bitcoin P2P Network
Giulia Fanti · Pramod Viswanath
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #67
Accuracy First: Selecting a Differential Privacy Level for Accuracy Constrained ERM
Steven Wu · Bo Waggoner · Seth Neel · Aaron Roth · Katrina Ligett
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #68
Renyi Differential Privacy Mechanisms for Posterior Sampling
Joseph Geumlek · Shuang Song · Kamalika Chaudhuri
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #69
Collecting Telemetry Data Privately
Bolin Ding · Janardhan Kulkarni · Sergey Yekhanin
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #70
Generating steganographic images via adversarial training
Jamie Hayes · George Danezis
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #71
Fitting Low-Rank Tensors in Constant Time
Kohei Hayashi · Yuichi Yoshida
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #72
Thy Friend is My Friend: Iterative Collaborative Filtering for Sparse Matrix Estimation
Christian Borgs · Jennifer Chayes · Christina Lee · Devavrat Shah
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #73
Fair Clustering Through Fairlets
Flavio Chierichetti · Ravi Kumar · Silvio Lattanzi · Sergei Vassilvitskii
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #74
On Fairness and Calibration
Geoff Pleiss · Manish Raghavan · Felix Wu · Jon Kleinberg · Kilian Weinberger
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #75
Avoiding Discrimination through Causal Reasoning
Niki Kilbertus · Mateo Rojas Carulla · Giambattista Parascandolo · Moritz Hardt · Dominik Janzing · Bernhard Schölkopf
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #76
Optimized Pre-Processing for Discrimination Prevention
Flavio Calmon · Dennis Wei · Karthikeyan Natesan Ramamurthy · Bhanukiran Vinzamuri · Kush R Varshney
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #77
Recycling for Fairness: Learning with Conditional Distribution Matching Constraints
Novi Quadrianto · Viktoriia Sharmanska
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #78
From Parity to Preference: Learning with Cost-effective Notions of Fairness
Muhammad Bilal Zafar · Isabel Valera · Manuel Rodriguez · Krishna Gummadi · Adrian Weller
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #79
Beyond Parity: Fairness Objectives for Collaborative Filtering
Sirui Yao · Bert Huang
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #80
Multi-view Matrix Factorization for Linear Dynamical System Estimation
Mahdi Karami · Martha White · Dale Schuurmans · Csaba Szepesvari
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #81
Random Projection Filter Bank for Time Series Data
Amir-massoud Farahmand · Sepideh Pourazarm · Daniel Nikovski
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #82
A Dirichlet Mixture Model of Hawkes Processes for Event Sequence Clustering
Hongteng Xu · Hongyuan Zha
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #83
Predicting User Activity Level In Point Process Models With Mass Transport Equation
Yichen Wang · Xiaojing Ye · Hongyuan Zha · Le Song
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #84
Off-policy evaluation for slate recommendation
Adith Swaminathan · Akshay Krishnamurthy · Alekh Agarwal · Miro Dudik · John Langford · Damien Jose · Imed Zitouni
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #85
Expectation Propagation with Stochastic Kinetic Model in Complex Interaction Systems
Wen Dong · Le Fang · Fan Yang · Tong Guan · Chunming Qiao
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #86
A multi-agent reinforcement learning model of common-pool resource appropriation
Julien Pérolat · Joel Leibo · Vinicius Zambaldi · Charles Beattie · Karl Tuyls · Thore Graepel
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #87
Balancing information exposure in social networks
Kiran Garimella · Aristides Gionis · Nikos Parotsidis · Nikolaj Tatti
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #88
Scalable Demand-Aware Recommendation
Jinfeng Yi · Cho-Jui Hsieh · Kush R Varshney · Lijun Zhang · Yao Li
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #89
A Greedy Approach for Budgeted Maximum Inner Product Search
Hsiang-Fu Yu · Cho-Jui Hsieh · Qi Lei · Inderjit S Dhillon
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #90
DPSCREEN: Dynamic Personalized Screening
Kartik Ahuja · William Zame · Mihaela van der Schaar
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #91
Deep Multi-task Gaussian Processes for Survival Analysis with Competing Risks
Ahmed M. Alaa · Mihaela van der Schaar
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #92
Premise Selection for Theorem Proving by Deep Graph Embedding
Mingzhe Wang · Yihe Tang · Jian Wang · Jia Deng
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #93
Gradients of Generative Models for Improved Discriminative Analysis of Tandem Mass Spectra
John T Halloran · David M Rocke
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #94
Style Transfer from Non-parallel Text by Cross-Alignment
Tianxiao Shen · Tao Lei · Regina Barzilay · Tommi Jaakkola
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #95
Emergence of Language with Multi-agent Games: Learning to Communicate with Sequences of Symbols
Serhii Havrylov · Ivan Titov
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #96
ELF: An Extensive, Lightweight and Flexible Research Platform for Real-time Strategy Games
Yuandong Tian · Qucheng Gong · Wenling Shang · Yuxin Wu · C. Lawrence Zitnick
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #97
ExtremeWeather: A large-scale climate dataset for semi-supervised detection, localization, and understanding of extreme weather events
Evan Racah · Christopher Beckham · Tegan Maharaj · Mr. Prabhat · Chris Pal
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #98
Approximation and Convergence Properties of Generative Adversarial Learning
Shuang Liu · Olivier Bousquet · Kamalika Chaudhuri
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #99
Gradient descent GAN optimization is locally stable
Vaishnavh Nagarajan · J. Zico Kolter
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #100
f-GANs in an Information Geometric Nutshell
Richard Nock · Zac Cranko · Aditya K Menon · Lizhen Qu · Robert C Williamson
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #101
The Numerics of GANs
Lars Mescheder · Sebastian Nowozin · Andreas Geiger
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #102
Generalizing GANs: A Turing Perspective
Roderich Gross · Yue Gu · Wei Li · Melvin Gauci
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #103
Dualing GANs
Yujia Li · Alexander Schwing · Kuan-Chieh Wang · Richard Zemel
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #104
Fisher GAN
Youssef Mroueh · Tom Sercu
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #105
Learning to Pivot with Adversarial Networks
Gilles Louppe · Michael Kagan · Kyle Cranmer
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #106
Improved Training of Wasserstein GANs
Ishaan Gulrajani · Faruk Ahmed · Martin Arjovsky · Vincent Dumoulin · Aaron C Courville
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #107
MMD GAN: Towards Deeper Understanding of Moment Matching Network
Chun-Liang Li · Wei-Cheng Chang · Yu Cheng · Yiming Yang · Barnabas Poczos
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #108
Two Time-Scale Update Rule for Generative Adversarial Nets
Hubert Ramsauer · Martin Heusel · Sepp Hochreiter · Bernhard Nessler · Thomas Unterthiner
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #109
VEEGAN: Reducing Mode Collapse in GANs using Implicit Variational Learning
Akash Srivastava · Lazar Valkoz · Chris Russell · Michael U. Gutmann · Charles Sutton
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #110
Improved Semi-supervised Learning with GANs using Manifold Invariances
Abhishek Kumar · Prasanna Sattigeri · Tom Fletcher
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #111
Good Semi-supervised Learning That Requires a Bad GAN
Zihang Dai · Zhilin Yang · Fan Yang · William W Cohen · Ruslan Salakhutdinov
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #112
Bayesian GANs
Yunus Saatci · Andrew Wilson
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #113
Dual Discriminator Generative Adversarial Nets
Tu Nguyen · Trung Le · Hung Vu · Dinh Phung
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #114
Towards Understanding Adversarial Learning for Joint Distribution Matching
Chunyuan Li · Hao Liu · Ricardo Henao · Liqun Chen · Yuchen Pu · Changyou Chen · Lawrence Carin
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #115
Triple Generative Adversarial Nets
Chongxuan LI · Kun Xu · Jun Zhu · Bo Zhang
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #116
Triangle Generative Adversarial Networks
Zhe Gan · Liqun Chen · Weiyao Wang · Yuchen Pu · Yizhe Zhang · Lawrence Carin
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #117
Structured Generative Adversarial Networks
Hao Zhang · Zhijie Deng · Xiaodan Liang · Jun Zhu · Eric P Xing
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #118
PixelGAN Autoencoders
Alireza Makhzani · Brendan J Frey
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #119
Learning to Compose Domain-Specific Transformations for Data Augmentation
Alexander Ratner · Henry Ehrenberg · Zeshan Hussain · Jared Dunnmon · Christopher Ré
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #120
Unsupervised Image-to-Image Translation Networks
Ming-Yu Liu · Thomas Breuel · Jan Kautz
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #121
Adversarial Invariant Feature Learning
Qizhe Xie · Zihang Dai · Yulun Du · Eduard Hovy · Graham Neubig
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #122
Adversarial Ranking for Language Generation
Dianqi Li · Kevin Lin · Xiaodong He · Ming-ting Sun · Zhengyou Zhang
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #123
Efficient Computation of Moments in Sum-Product Networks
Han Zhao · Geoffrey Gordon
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #124
Attention is All you Need
Ashish Vaswani · Noam Shazeer · Niki Parmar · Llion Jones · Jakob Uszkoreit · Aidan N Gomez · Łukasz Kaiser
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #125
Masked Autoregressive Flow for Density Estimation
George Papamakarios · Iain Murray · Theo Pavlakou
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #126
Variational Walkback: Learning a Transition Operator as a Stochastic Recurrent Net
Anirudh Goyal ALIAS PARTH GOYAL · Nan Ke · Surya Ganguli · Yoshua Bengio
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #127
TernGrad: Ternary Gradients to Reduce Communication in Distributed Deep Learning
Wei Wen · Cong Xu · Feng Yan · Chunpeng Wu · Yandan Wang · Yiran Chen · Hai Li
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #128
End-to-end Differentiable Proving
Tim Rocktäschel · Sebastian Riedel
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #129
A simple neural network module for relational reasoning
Adam Santoro · David Raposo · David Barrett · Mateusz Malinowski · Razvan Pascanu · Peter Battaglia · Tim Lillicrap
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #130
Dual Path Networks
Yunpeng Chen · Jianan Li · Huaxin Xiao · Xiaojie Jin · Shuicheng Yan · Jiashi Feng
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #131
Spherical convolutions and their application in molecular modelling
Wouter Boomsma · Jes Frellsen
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #132
Deep Sets
Manzil Zaheer · Satwik Kottur · Siamak Ravanbakhsh · Barnabas Poczos · Ruslan Salakhutdinov · Alexander Smola
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #133
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles
Balaji Lakshminarayanan · Alexander Pritzel · Charles Blundell
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #134
Self-Normalizing Neural Networks
Günter Klambauer · Thomas Unterthiner · Andreas Mayr · Sepp Hochreiter
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #135
Batch Renormalization: Towards Reducing Minibatch Dependence in Batch-Normalized Models
Sergey Ioffe
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #136
Train longer, generalize better: closing the generalization gap in large batch training of neural networks
Elad Hoffer · Itay Hubara · Daniel Soudry
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #137
Nonlinear random matrix theory for deep learning
Jeffrey Pennington · Pratik Worah
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #138
DisTraL: Robust multitask reinforcement learning
Yee Teh · Victor Bapst · Razvan Pascanu · Nicolas Heess · John Quan · James Kirkpatrick · Wojciech M. Czarnecki · Raia Hadsell
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #139
Imagination-Augmented Agents for Deep Reinforcement Learning
Sébastien Racanière · David Reichert · Theophane Weber · Oriol Vinyals · Daan Wierstra · Lars Buesing · Peter Battaglia · Razvan Pascanu · Yujia Li · Nicolas Heess · Arthur Guez · Danilo Jimenez Rezende · Adrià Puigdomènech Badia · David Silver
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #140
Second-order Optimization in Deep Reinforcement Learning using Kronecker-factored Approximation
Yuhuai Wu · Elman Mansimov · Roger Grosse · Shun Liao · Jimmy Ba
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #141
Learning Combinatorial Optimization Algorithms over Graphs
Elias Khalil · Hanjun Dai · Yuyu Zhang · Bistra Dilkina · Le Song
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #142
Targeting EEG/LFP Synchrony with Neural Nets
Yitong Li · David E Carlson · Lawrence Carin
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #143
Toward Goal-Driven Neural Network Models for the Rodent Whisker-Trigeminal System
Chengxu Zhuang · Jonas Kubilius · Mitra JZ Hartmann · Daniel Yamins
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #144
Fast amortized inference of neural activity from calcium imaging data with variational autoencoders
Artur Speiser · Jinyao Yan · Evan Archer · Lars Buesing · Srinivas C Turaga · Jakob H Macke
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #145
Scene Physics Acquisition via Visual De-animation
Jiajun Wu · Erika Lu · Pushmeet Kohli · Bill Freeman · Josh Tenenbaum
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #146
Shape and Material from Sound
zhoutong zhang · Qiujia Li · Zhengjia Huang · Jiajun Wu · Josh Tenenbaum · Bill Freeman
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #147
Deep Networks for Decoding Natural Images from Retinal Signals
Nikhil Parthasarathy · Eleanor Batty · William Falcon · Thomas Rutten · Mohit Rajpal · E.J. Chichilnisky · Liam Paninski
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #148
Quantifying how much sensory information in a neural code is relevant for behavior
Giuseppe Pica · Eugenio Piasini · Houman Safaai · Caroline Runyan · Christopher Harvey · Mathew Diamond · Christoph Kayser · Tommaso Fellin · Stefano Panzeri
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #149
Model-based Bayesian inference of neural activity and connectivity from all-optical interrogation of a neural circuit
Laurence Aitchison · Lloyd Russell · Adam Packer · Jinyao Yan · Philippe Castonguay · Michael Hausser · Srinivas C Turaga
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #150
Deep Hyperalignment
Muhammad Yousefnezhad · Daoqiang Zhang
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #151
Tensor encoding and decomposition of brain connectomes with application to tractography evaluation
Cesar F Caiafa · Olaf Sporns · Andrew Saykin · Franco Pestilli
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #152
Online Dynamic Programming
Holakou Rahmanian · Manfred Warmuth
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #153
Unsupervised Learning of Disentangled Representations from Video
Emily Denton · vighnesh Birodkar
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #154
Interactive Submodular Bandit
Lin Chen · Andreas Krause · Amin Karbasi
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #155
Streaming Robust Submodular Maximization:A Partitioned Thresholding Approach
Slobodan Mitrovic · Ilija Bogunovic · Ashkan Norouzi-Fard · Jakub M Tarnawski · Volkan Cevher
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #156
Minimizing a Submodular Function from Samples
Eric Balkanski · Yaron Singer
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #157
Process-constrained batch Bayesian optimisation
Pratibha Vellanki · Santu Rana · Sunil Gupta · David Rubin · Alessandra Sutti · Thomas Dorin · Murray Height · Paul Sanders · Svetha Venkatesh
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #158
The Marginal Value of Adaptive Gradient Methods in Machine Learning
Ashia C Wilson · Rebecca Roelofs · Mitchell Stern · Nati Srebro · Benjamin Recht
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #159
Breaking the Nonsmooth Barrier: A Scalable Parallel Method for Composite Optimization
Fabian Pedregosa · Rémi Leblond · Simon Lacoste-Julien
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #160
Beyond Worst-case: A Probabilistic Analysis of Affine Policies in Dynamic Optimization
Omar El Housni · Vineet Goyal
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #161
Approximate Supermodularity Bounds for Experimental Design
Luiz Chamon · Alejandro Ribeiro
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #162
On Blackbox Backpropagation and Jacobian Sensing
Krzysztof M Choromanski · Vikas Sindhwani
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #163
Asynchronous Coordinate Descent under More Realistic Assumptions
Tao Sun · Robert Hannah · Wotao Yin
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #164
Clustering with Noisy Queries
Arya Mazumdar · Barna Saha
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #165
Approximation Algorithms for $\ell_0$-Low Rank Approximation
Karl Bringmann · Pavel Kolev · David Woodruff
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #166
Convergence Analysis of Two-layer Neural Networks with ReLU Activation
Yuanzhi Li · Yang Yuan
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #167
Can Decentralized Algorithms Outperform Centralized Algorithms? A Case Study for Decentralized Parallel Stochastic Gradient Descent
Xiangru Lian · Ce Zhang · Huan Zhang · Cho-Jui Hsieh · Wei Zhang · Ji Liu
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #168
Decomposition-Invariant Conditional Gradient for General Polytopes with Line Search
Mohammad Ali Bashiri · Xinhua Zhang
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #169
Straggler Mitigation in Distributed Optimization Through Data Encoding
Can Karakus · Yifan Sun · Suhas Diggavi · Wotao Yin
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #170
No More Fixed Penalty Parameter in ADMM: Faster Convergence with New Adaptive Penalization
Yi Xu · Mingrui Liu · Tianbao Yang · Qihang Lin
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #171
Accelerated Stochastic Greedy Coordinate Descent by Soft Thresholding Projection onto Simplex
Chaobing Song · Shaobo Cui · Shu-Tao Xia · Yong Jiang
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #172
Safe Adaptive Importance Sampling
Sebastian Stich · Anant Raj · Martin Jaggi
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #173
Sharpness, Restart and Acceleration
Vincent Roulet · Alexandre d'Aspremont
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #174
Stochastic Optimization with Variance Reduction for Infinite Datasets with Finite Sum Structure
Alberto Bietti · Julien Mairal
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #175
Min-Max Propagation
Christopher Srinivasa · Inmar Givoni · Siamak Ravanbakhsh · Brendan J Frey
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #176
A Disentangled Recognition and Nonlinear Dynamics Model for Unsupervised Learning
Marco Fraccaro · Simon Kamronn · Ulrich Paquet · Ole Winther
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #177
Concrete Dropout
Yarin Gal · Jiri Hron · Alex Kendall
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #178
REBAR: Low-variance, unbiased gradient estimates for discrete latent variable models
George Tucker · Andriy Mnih · Chris J Maddison · John Lawson · Jascha Sohl-Dickstein
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #179
Hierarchical Implicit Models and Likelihood-Free Variational Inference
Dustin Tran · Rajesh Ranganath · David Blei
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #180
Sticking the Landing: Simple, Lower-Variance Gradient Estimators for Variational Inference
Geoffrey Roeder · Yuhuai Wu · David Duvenaud
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #181
Perturbative Black Box Variational Inference
Cheng Zhang · Robert Bamler · Manfred Opper · Stephan Mandt
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #182
Fast Black-box Variational Inference through Stochastic Trust-Region Optimization
Jeffrey Regier · Michael Jordan · Jon McAuliffe
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #183
Excess Risk Bounds for the Bayes Risk using Variational Inference in Latent Gaussian Models
Rishit Sheth · Roni Khardon
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #184
Learning Causal Graphs with Latent Variables
Murat Kocaoglu · Karthikeyan Shanmugam · Elias Bareinboim
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #185
Permutation-based Causal Inference Algorithms with Interventions
Yuhao Wang · Liam Solus · Karren Yang · Caroline Uhler
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #186
Learning Causal Structures Using Regression Invariance
AmirEmad Ghassami · Saber Salehkaleybar · Negar Kiyavash · Kun Zhang
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #187
Counterfactual Fairness
Matt Kusner · Joshua Loftus · Chris Russell · Ricardo Silva
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #188
Causal Effect Inference with Deep Latent Variable Models
Christos Louizos · Uri Shalit · Joris M Mooij · David Sontag · Richard Zemel · Max Welling
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #189
Conic Scan Coverage algorithm for nonparametric topic modeling
Mikhail Yurochkin · Aritra Guha · XuanLong Nguyen
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #190
Tractability in Structured Probability Spaces
Arthur Choi · Yujia Shen · Adnan Darwiche
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #191
PASS-GLM: polynomial approximate sufficient statistics for scalable Bayesian GLM inference
Jonathan Huggins · Ryan Adams · Tamara Broderick
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #192
Adaptive Bayesian Sampling with Monte Carlo EM
Anirban Roychowdhury · Srinivasan Parthasarathy
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #193
What-If Reasoning using Counterfactual Gaussian Processes
Peter Schulam · Suchi Saria
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #194
Multi-Information Source Optimization
Matthias Poloczek · Jialei Wang · Peter Frazier
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #195
Doubly Stochastic Variational Inference for Deep Gaussian Processes
Hugh Salimbeni · Marc Deisenroth
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #196
Convolutional Gaussian Processes
Mark van der Wilk · Carl Edward Rasmussen · James Hensman
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #197
Multiresolution Kernel Approximation for Gaussian Process Regression
Yi Ding · Risi Kondor · Jonathan Eskreis-Winkler
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #198
Unifying PAC and Regret: Uniform PAC Bounds for Episodic Reinforcement Learning
Christoph Dann · Tor Lattimore · Emma Brunskill
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #199
Repeated Inverse Reinforcement Learning
Kareem Amin · Nan Jiang · Satinder Singh
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #200
Inverse Reward Design
Dylan Hadfield-Menell · Smitha Milli · Stuart J Russell · Pieter Abbeel · Anca Dragan
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #201
Utile Context Tree Weighting
Joao V Messias · Shimon Whiteson
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #202
Policy Gradient With Value Function Approximation For Collective Multiagent Planning
Duc Thien Nguyen · Akshat Kumar · Hoong Chuin Lau
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #203
A Unified Game-Theoretic Approach to Multiagent Reinforcement Learning
Marc Lanctot · Vinicius Zambaldi · Audrunas Gruslys · Angeliki Lazaridou · karl Tuyls · Julien Perolat · David Silver · Thore Graepel
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #204
Dynamic Safe Interruptibility for Decentralized Multi-Agent Reinforcement Learning
El Mahdi El Mhamdi · Rachid Guerraoui · Hadrien Hendrikx · Alexandre Maurer
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #205
Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments
Ryan Lowe · YI WU · Aviv Tamar · Jean Harb · OpenAI Pieter Abbeel · Igor Mordatch
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #206
Spectrally-normalized margin bounds for neural networks
Matus Telgarsky · Peter Bartlett · Dylan J Foster
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #207
On Structured Prediction Theory with Calibrated Convex Surrogate Losses
Anton Osokin · Francis Bach · Simon Lacoste-Julien
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #208
Collaborative PAC Learning
Avrim Blum · Nika Haghtalab · Ariel D Procaccia · IIIS Mingda Qiao
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #209
Submultiplicative Glivenko-Cantelli and Uniform Convergence of Revenues
Noga Alon · Moshe Babaioff · Yannai A. Gonczarowski · Yishay Mansour · Shay Moran · Amir Yehudayoff
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #210
Discriminative State Space Models
Vitaly Kuznetsov · Mehryar Mohri
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #211
Delayed Mirror Descent in Continuous Games
Zhengyuan Zhou · Panayotis Mertikopoulos · Nicholas Bambos · Peter W Glynn · Claire Tomlin
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #212
Variance-based Regularization with Convex Objectives
Hongseok Namkoong · John C Duchi
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #213
Learning Mixture of Gaussians with Streaming Data
Aditi Raghunathan · Prateek Jain · Ravishankar Krishnawamy
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #214
On the Consistency of Quick Shift
Heinrich Jiang
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #215
Early stopping for kernel boosting algorithms: A general analysis with localized complexities
Yuting Wei · Fanny Yang · Martin Wainwright
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #216
A Sharp Error Analysis for the Fused Lasso, with Implications to Broader Settings and Approximate Screening
Kevin Lin · James Sharpnack · Alessandro Rinaldo · Ryan Tibshirani
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #217
The Scaling Limit of High-Dimensional Online Independent Component Analysis
Chuang Wang · Yue Lu
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #218
A Universal Analysis of Large-Scale Regularized Least Squares Solutions
Ashkan Panahi · Babak Hassibi
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #219
Statistical Convergence Analysis of Gradient EM on General Gaussian Mixture Models
Bowei Yan · Mingzhang Yin · Purnamrita Sarkar
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #220
Online control of the false discovery rate with decaying memory
Aaditya Ramdas · Fanny Yang · Martin Wainwright · Michael Jordan
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #221
Learning with Bandit Feedback in Potential Games
Amélie Heliou · Johanne Cohen · Panayotis Mertikopoulos
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #222
Fully Decentralized Policies for Multi-Agent Systems: An Information Theoretic Approach
Roel Dobbe · David Fridovich-Keil · Claire Tomlin
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #223
Revenue Optimization with Approximate Bid Predictions
Andres Munoz · Sergei Vassilvitskii
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #224
A Decomposition of Forecast Error in Prediction Markets
Miro Dudik · Sebastien Lahaie · Ryan M Rogers · Jennifer Wortman Vaughan
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #225
Dynamic Revenue Sharing
Santiago Balseiro · Max Lin · Vahab Mirrokni · Renato Leme · IIIS Song Zuo
Poster
Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #226
Multi-View Decision Processes
Christos Dimitrakakis · David Parkes · Goran Radanovic · Paul Tylkin
Demonstration
Wed Dec 6th 07:00 -- 10:30 PM @ Pacific Ballroom Concourse #D1
Humans attributes extraction and search with a deep learning based real-time video analysis system
Matthieu Ospici · benoit pelletier · Antoine CECCHI
Demonstration
Wed Dec 6th 07:00 -- 10:30 PM @ Pacific Ballroom Concourse #D2
MAgent: A Many-Agent Reinforcement Learning Research Platform for Artificial Collective Intelligence
Lianmin Zheng · Jiacheng Yang · Han Cai · Weinan Zhang · Jun Wang · Yong Yu
Demonstration
Wed Dec 6th 07:00 -- 10:30 PM @ Pacific Ballroom Concourse #D3
Electronic Screen Protector with Efficient and Robust Mobile Vision
HEE JUNG RYU · Florian Schroff
Demonstration
Wed Dec 6th 07:00 -- 10:30 PM @ Pacific Ballroom Concourse #D4
3D Surface-to-Structure Translation with Deep Convolutional Networks
Takumi Moriya · Kazuyuki Saito
Demonstration
Wed Dec 6th 07:00 -- 10:30 PM @ Pacific Ballroom Concourse #D5
Sharkzor: Interactive Deep Learning for Image Triage, Sort and Summary
Nathan Hodas · Nathan Hilliard · Artem Yankov · Megan Pirrung · Courtney Corley
Demonstration
Wed Dec 6th 07:00 -- 10:30 PM @ Pacific Ballroom Concourse #D6
Magenta and deeplearn.js: Real-time Control of DeepGenerative Music Models in the Browser
Curtis Hawthorne · Ian Simon · Adam Roberts · Jesse Engel · Daniel Smilkov · Nikhil Thorat · Douglas Eck
Demonstration
Wed Dec 6th 07:00 -- 10:30 PM @ Pacific Ballroom Concourse #D7
Matrix Calculus -- The Power of Symbolic Differentiation
Soeren Laue · Matthias Mitterreiter · Joachim Giesen
Demonstration
Wed Dec 6th 07:00 -- 10:30 PM @ Pacific Ballroom Concourse #D8
Babble Labble: Learning from Natural Language Explanations
Braden Hancock · Paroma Varma · Percy Liang · Christopher Ré · Stephanie Wang
Demonstration
Wed Dec 6th 07:00 -- 10:30 PM @ Pacific Ballroom Concourse #D9
Interactive-Length Multi-Task Video Captioning with Cooperative Feedback
Han Guo · Ramakanth Pasunuru · Mohit Bansal
Demonstration
Wed Dec 6th 07:00 -- 10:30 PM @ Pacific Ballroom Concourse #D10
Fast-speed Intelligent Video Analytics using Deep Learning Algorithms on Low-power FPGA
Yi Shan · Song Yao · Song Han · Yu Wang
Break
Thu Dec 7th 07:30 -- 09:00 AM @
coffee, no breakfast served
Invited Talk
Thu Dec 7th 09:00 -- 09:50 AM @ Hall A
Learning State Representations
Yael Niv
Invited Talk (Breiman Lecture)
Thu Dec 7th 09:50 -- 10:40 AM @ Hall A
On Bayesian Deep Learning and Deep Bayesian Learning
Yee Whye Teh
Break
Thu Dec 7th 10:40 -- 11:10 AM @
Coffee Break
Oral
Thu Dec 7th 11:10 -- 11:25 AM @ Hall A
Toward Goal-Driven Neural Network Models for the Rodent Whisker-Trigeminal System
Chengxu Zhuang · Jonas Kubilius · Mitra JZ Hartmann · Daniel Yamins
Oral
Thu Dec 7th 11:10 -- 11:25 AM @ Hall C
Masked Autoregressive Flow for Density Estimation
George Papamakarios · Iain Murray · Theo Pavlakou
Oral
Thu Dec 7th 11:25 -- 11:40 AM @ Hall A
Model-based Bayesian inference of neural activity and connectivity from all-optical interrogation of a neural circuit
Laurence Aitchison · Lloyd Russell · Adam Packer · Jinyao Yan · Philippe Castonguay · Michael Hausser · Srinivas C Turaga
Oral
Thu Dec 7th 11:25 -- 11:40 AM @ Hall C
Deep Sets
Manzil Zaheer · Satwik Kottur · Siamak Ravanbakhsh · Barnabas Poczos · Ruslan Salakhutdinov · Alexander Smola
Oral
Thu Dec 7th 11:40 -- 11:55 AM @ Hall A
Quantifying how much sensory information in a neural code is relevant for behavior
Giuseppe Pica · Eugenio Piasini · Houman Safaai · Caroline Runyan · Christopher Harvey · Mathew Diamond · Christoph Kayser · Tommaso Fellin · Stefano Panzeri
Oral
Thu Dec 7th 11:40 -- 11:55 AM @ Hall C
From Bayesian Sparsity to Gated Recurrent Nets
Hao He · Bo Xin · David Wipf
Spotlight
Thu Dec 7th 11:55 AM -- 12:00 PM @ Hall A
Scene Physics Acquisition via Visual De-animation
Jiajun Wu · Erika Lu · Pushmeet Kohli · Bill Freeman · Josh Tenenbaum
Spotlight
Thu Dec 7th 11:55 AM -- 12:00 PM @ Hall C
Self-Normalizing Neural Networks
Günter Klambauer · Thomas Unterthiner · Andreas Mayr · Sepp Hochreiter
Spotlight
Thu Dec 7th 12:00 -- 12:05 PM @ Hall A
Shape and Material from Sound
zhoutong zhang · Qiujia Li · Zhengjia Huang · Jiajun Wu · Josh Tenenbaum · Bill Freeman
Spotlight
Thu Dec 7th 12:00 -- 12:05 PM @ Hall C
Batch Renormalization: Towards Reducing Minibatch Dependence in Batch-Normalized Models
Sergey Ioffe
Spotlight
Thu Dec 7th 12:05 -- 12:10 PM @ Hall A
Deep Hyperalignment
Muhammad Yousefnezhad · Daoqiang Zhang
Spotlight
Thu Dec 7th 12:05 -- 12:10 PM @ Hall C
Nonlinear random matrix theory for deep learning
Jeffrey Pennington · Pratik Worah
Spotlight
Thu Dec 7th 12:10 -- 12:15 PM @ Hall A
Fast amortized inference of neural activity from calcium imaging data with variational autoencoders
Artur Speiser · Jinyao Yan · Evan Archer · Lars Buesing · Srinivas C Turaga · Jakob H Macke
Spotlight
Thu Dec 7th 12:10 -- 12:15 PM @ Hall C
Spherical convolutions and their application in molecular modelling
Wouter Boomsma · Jes Frellsen
Spotlight
Thu Dec 7th 12:15 -- 12:20 PM @ Hall A
Tensor encoding and decomposition of brain connectomes with application to tractography evaluation
Cesar F Caiafa · Olaf Sporns · Andrew Saykin · Franco Pestilli
Spotlight
Thu Dec 7th 12:15 -- 12:20 PM @ Hall C
Translation Synchronization via Truncated Least Squares
Xiangru Huang · Zhenxiao Liang · Chandrajit Bajaj · Qixing Huang
Spotlight
Thu Dec 7th 12:20 -- 12:25 PM @ Hall A
Targeting EEG/LFP Synchrony with Neural Nets
Yitong Li · David E Carlson · Lawrence Carin
Spotlight
Thu Dec 7th 12:20 -- 12:25 PM @ Hall C
Self-supervised Learning of Motion Capture
Hsiao-Yu Tung · Hsiao-Wei Tung · Ersin Yumer · Katerina Fragkiadaki
Spotlight
Thu Dec 7th 12:25 -- 12:30 PM @ Hall A
Deep Networks for Decoding Natural Images from Retinal Signals
Nikhil Parthasarathy · Eleanor Batty · William Falcon · Thomas Rutten · Mohit Rajpal · E.J. Chichilnisky · Liam Paninski
Spotlight
Thu Dec 7th 12:25 -- 12:30 PM @ Hall C
Maximizing Subset Accuracy with Recurrent Neural Networks in Multi-label Classification
Jinseok Nam · Eneldo Loza Mencía · Hyunwoo J Kim · Johannes Fürnkranz
Symposium
Thu Dec 7th 02:00 -- 09:30 PM @ Grand Ballroom
Metalearning
Risto Miikkulainen · Quoc V Le · Kenneth Stanley · Chrisantha Fernando
Symposium
Thu Dec 7th 02:00 -- 09:30 PM @ Hall C
Interpretable Machine Learning
Andrew G Wilson · Jason Yosinski · Patrice Simard · Rich Caruana · William Herlands
Symposium
Thu Dec 7th 02:00 -- 09:30 PM @ Beverly Theater
Kinds of intelligence: types, tests and meeting the needs of society
José Hernández-Orallo · Zoubin Ghahramani · Tomaso A Poggio · Adrian Weller · Matthew Crosby
Symposium
Thu Dec 7th 02:00 -- 09:30 PM @ Hall A
Deep Reinforcement Learning
Pieter Abbeel · Yan Duan · David Silver · Satinder Singh · Junhyuk Oh · Rein Houthooft
Break
Thu Dec 7th 04:00 -- 04:30 PM @
Coffee Break
Break
Thu Dec 7th 06:30 -- 07:30 PM @
Light Dinner
Break
Fri Dec 8th 07:00 -- 08:30 AM @
Coffee Break
Workshop
Fri Dec 8th 08:00 AM -- 06:30 PM @ Hyatt Shoreline
Nearest Neighbors for Modern Applications with Massive Data: An Age-old Solution with New Challenges
George H Chen · Devavrat Shah · Christina Lee
Workshop
Fri Dec 8th 08:00 AM -- 06:30 PM @ Room 104-B
Machine Learning for Health (ML4H) - What Parts of Healthcare are Ripe for Disruption by Machine Learning Right Now?
Andrew Beam · Madalina Fiterau · Peter Schulam · Jason Fries · Michael Hughes · Alex Wiltschko · Jasper Snoek · Natalia Antropova · Rajesh Ranganath · Bruno Jedynak · Tristan Naumann · Adrian Dalca · Adrian Dalca · Tim Althoff · SHUBHI ASTHANA · Prateek Tandon · Jaz Kandola · Alexander Ratner · David Kale · Uri Shalit · Marzyeh Ghassemi · Isaac S Kohane
Workshop
Fri Dec 8th 08:00 AM -- 06:30 PM @ Room 201-B
Machine Learning for Audio Signal Processing (ML4Audio)
Hendrik Purwins · Bob L. Sturm · Mark Plumbley
Workshop
Fri Dec 8th 08:00 AM -- 06:30 PM @ Grand Ballroom B
NIPS 2017 Time Series Workshop
Vitaly Kuznetsov · Oren Anava · Scott Yang · Azadeh Khaleghi
Workshop
Fri Dec 8th 08:00 AM -- 06:30 PM @ Room S-5
Synergies in Geometric Data Analysis
Marina Meila · Frederic Chazal
Workshop
Fri Dec 8th 08:00 AM -- 06:30 PM @ Room 201-A
Transparent and interpretable Machine Learning in Safety Critical Environments
Alessandra Tosi · Alfredo Vellido · Mauricio A. Álvarez
Workshop
Fri Dec 8th 08:00 AM -- 06:30 PM @ Room 102-C
Machine Learning for Molecules and Materials
Stefan Chmiela · José Miguel Hernández-Lobato · Kristof T. Schütt · Alan Aspuru-Guzik · Alexandre Tkatchenko · Bharath Ramsundar · Anatole von Lilienfeld · Matt Kusner · Koji Tsuda · Brooks Paige · Klaus-Robert Müller
Workshop
Fri Dec 8th 08:00 AM -- 06:30 PM @ Room S-3
Workshop on Worm's Neural Information Processing (WNIP)
Ramin Hasani · Manuel Zimmer · Stephen Larson · Radu Grosu
Workshop
Fri Dec 8th 08:00 AM -- 06:30 PM @ Room 101-A
Visually grounded interaction and language
Florian Strub · Harm de Vries · Abhishek Das · Satwik Kottur · Stefan Lee · Mateusz Malinowski · Olivier Pietquin · Devi Parikh · Dhruv Batra · Aaron C Courville · Jeremie Mary
Workshop
Fri Dec 8th 08:00 AM -- 06:30 PM @ Grand Ballroom A
OPT 2017: Optimization for Machine Learning
Suvrit Sra · Sashank J. Reddi · Alekh Agarwal · Benjamin Recht
Workshop
Fri Dec 8th 08:00 AM -- 06:30 PM @ Room 104-A
Advances in Approximate Bayesian Inference
Francisco Ruiz · Stephan Mandt · Cheng Zhang · James McInerney · Dustin Tran · Tamara Broderick · Michalis Titsias · David Blei · Max Welling
Workshop
Fri Dec 8th 08:00 AM -- 06:30 PM @ Hyatt Beacon Ballroom D+E+F+H
Extreme Classification: Multi-class & Multi-label Learning in Extremely Large Label Spaces
Manik Varma · Marius Kloft · Krzysztof Dembczynski
Workshop
Fri Dec 8th 08:00 AM -- 06:30 PM @ Room 203
Machine Deception
Ian Goodfellow · Tim Hwang · Bryce Goodman · Mikel Rodriguez
Workshop
Fri Dec 8th 08:00 AM -- 06:30 PM @ Hyatt Seaview Ballroom
Discrete Structures in Machine Learning
Yaron Singer · Jeff A Bilmes · Andreas Krause · Stefanie Jegelka · Amin Karbasi
Workshop
Fri Dec 8th 08:00 AM -- 06:30 PM @ Seaside Ballroom
Learning on Distributions, Functions, Graphs and Groups
Florence d'Alché-Buc · Krikamol Muandet · Bharath Sriperumbudur · Zoltán Szabó
Workshop
Fri Dec 8th 08:00 AM -- 06:30 PM @ Room 202
Deep Learning for Physical Sciences
Atilim Gunes Baydin · Mr. Prabhat · Kyle Cranmer · Frank Wood
Workshop
Fri Dec 8th 08:00 AM -- 08:45 PM @ Room S-7
Competition track
Sergio Escalera · Markus Weimer
Workshop
Fri Dec 8th 08:00 AM -- 06:30 PM @ Room 103-C
6th Workshop on Automated Knowledge Base Construction (AKBC)
Jay Pujara · Danqi Chen · Bhavana Dalvi Mishra · Tim Rocktäschel
Workshop
Fri Dec 8th 08:00 AM -- 06:30 PM @ Room-204
ML Systems Workshop @ NIPS 2017
Aparna Lakshmiratan · Sarah Bird · Siddhartha Sen · Christopher Ré · Li Erran Li · Joseph Gonzalez · Daniel Crankshaw
Workshop
Fri Dec 8th 08:00 AM -- 06:30 PM @ Room 103 A+B
Advances in Modeling and Learning Interactions from Complex Data
Gautam Dasarathy · Mladen Kolar · Richard Baraniuk
Workshop
Fri Dec 8th 08:00 AM -- 06:30 PM @ Room 101-B
Learning in the Presence of Strategic Behavior
Nika Haghtalab · Yishay Mansour · Tim Roughgarden · Vasilis Syrgkanis · Jennifer Wortman Vaughan
Workshop
Fri Dec 8th 08:00 AM -- 06:30 PM @ Hyatt Regency Ballroom A+B+C
Conversational AI - today's practice and tomorrow's potential
Alborz Geramifard · Jason Williams · Larry Heck · James Glass · Antoine Bordes · Steve Young · Gerald Tesauro
Workshop
Fri Dec 8th 08:00 AM -- 06:30 PM @ Room S-1
Machine Learning for the Developing World
Maria De-Arteaga · William Herlands
Workshop
Fri Dec 8th 08:00 AM -- 06:30 PM @ Room 104-C
Acting and Interacting in the Real World: Challenges in Robot Learning
Ingmar Posner · Raia Hadsell · Martin Riedmiller · Markus Wulfmeier · Rohan Paul
Workshop
Fri Dec 8th 08:00 AM -- 06:30 PM @ Room 102 A+B
Machine Learning for Creativity and Design
Douglas Eck · David Ha · S. M. Ali Eslami · Sander Dieleman · Rebecca Fiebrink · Luba Elliott
Workshop
Fri Dec 8th 08:00 AM -- 06:30 PM @ S-4
Machine Learning and Computer Security
Jacob Steinhardt · Nicolas Papernot · Bo Li · Chang Liu · Percy Liang · Dawn Song
Workshop
Fri Dec 8th 08:30 AM -- 06:30 PM @ Hall C
From 'What If?' To 'What Next?' : Causal Inference and Machine Learning for Intelligent Decision Making
Alexander Volfovsky · Adith Swaminathan · Panagiotis Toulis · Nathan Kallus · Ricardo Silva · John S Shawe-Taylor · Thorsten Joachims · Lihong Li
Workshop
Sat Dec 9th 08:00 AM -- 06:30 PM @ 101-B
(Almost) 50 shades of Bayesian Learning: PAC-Bayesian trends and insights
Benjamin Guedj · Pascal Germain · Francis Bach
Workshop
Sat Dec 9th 08:00 AM -- 06:30 PM @ Hyatt Regency Ballroom A+B+C
Learning with Limited Labeled Data: Weak Supervision and Beyond
Isabelle Augenstein · Stephen Bach · Eugene Belilovsky · Matthew Blaschko · Christoph Lampert · Edouard Oyallon · Emmanouil Antonios Platanios · Alexander Ratner · Christopher Ré
Workshop
Sat Dec 9th 08:00 AM -- 06:30 PM @ Hyatt Shoreline
Aligned Artificial Intelligence
Dylan Hadfield-Menell · Jacob Steinhardt · David Duvenaud · David Krueger · Anca Dragan
Workshop
Sat Dec 9th 08:00 AM -- 06:30 PM @ S-4
Collaborate & Communicate: An exploration and practical skills workshop that builds on the experience of AIML experts who are both successful collaborators and great communicators.
Katherine Gorman
Workshop
Sat Dec 9th 08:00 AM -- 06:30 PM @ S-7
Medical Imaging meets NIPS
Ben Glocker · Ender Konukoglu · Hervé Lombaert · Kanwal Bhatia
Workshop
Sat Dec 9th 08:00 AM -- 06:30 PM @ 104-B
Cognitively Informed Artificial Intelligence: Insights From Natural Intelligence
Michael Mozer · Brenden Lake · Angela J Yu
Workshop
Sat Dec 9th 08:00 AM -- 06:30 PM @ Room S-5
Synergies in Geometric Data Analysis (2nd day)
Marina Meila · Frederic Chazal
Workshop
Sat Dec 9th 08:00 AM -- 06:30 PM @ 204
Machine Learning Challenges as a Research Tool
Isabelle Guyon · Evelyne Viegas · Sergio Escalera · Jacob D Abernethy
Workshop
Sat Dec 9th 08:00 AM -- 06:30 PM @ Hyatt Beacon Ballroom D+E+F+H
Interpreting, Explaining and Visualizing Deep Learning - Now what ?
Klaus-Robert Müller · Andrea Vedaldi · Lars K Hansen · Wojciech Samek · Grégoire Montavon
Workshop
Sat Dec 9th 08:00 AM -- 06:30 PM @ 102-C
Emergent Communication Workshop
Jakob Foerster · Igor Mordatch · Angeliki Lazaridou · Kyunghyun Cho · Douwe Kiela · Pieter Abbeel
Workshop
Sat Dec 9th 08:00 AM -- 06:30 PM @ Grand Ballroom A
Deep Learning: Bridging Theory and Practice
Sanjeev Arora · Maithra Raghu · Ruslan Salakhutdinov · Ludwig Schmidt · Oriol Vinyals
Workshop
Sat Dec 9th 08:00 AM -- 06:30 PM @ 201-B
2017 NIPS Workshop on Machine Learning for Intelligent Transportation Systems
Li Erran Li · Anca Dragan · Juan Carlos Niebles · Silvio Savarese
Workshop
Sat Dec 9th 08:00 AM -- 06:30 PM @ Hall C
Bayesian Deep Learning
Yarin Gal · José Miguel Hernández-Lobato · Christos Louizos · Andrew G Wilson · Diederik P. (Durk) Kingma · Zoubin Ghahramani · Kevin P Murphy · Max Welling
Workshop
Sat Dec 9th 08:00 AM -- 06:30 PM @ 102 A+B
Optimal Transport and Machine Learning
Olivier Bousquet · Marco Cuturi · Gabriel Peyré · Fei Sha · Justin Solomon
Workshop
Sat Dec 9th 08:00 AM -- 06:30 PM @ 203
NIPS Highlights (MLTrain), Learn How to code a paper with state of the art frameworks
Alexandros Dimakis · Nikolaos Vasiloglou · Guy Van den Broeck · Alexander Ihler · Assaf Araki
Workshop
Sat Dec 9th 08:00 AM -- 06:30 PM @ S-3
Workshop on Prioritising Online Content
John S Shawe-Taylor · Massimiliano Pontil · Nicolò Cesa-Bianchi · Emine Yilmaz · Chris Watkins · Sebastian Riedel · Marko Grobelnik
Workshop
Sat Dec 9th 08:00 AM -- 06:30 PM @ 202
The future of gradient-based machine learning software & techniques
Alex Wiltschko · Bart van Merriënboer · Pascal Lamblin
Workshop
Sat Dec 9th 08:00 AM -- 06:30 PM @ Hyatt Seaview Ballroom
Learning Disentangled Features: from Perception to Control
Emily Denton · Siddharth Narayanaswamy · Tejas Kulkarni · Honglak Lee · Diane Bouchacourt · Josh Tenenbaum · David Pfau
Workshop
Sat Dec 9th 08:00 AM -- 06:30 PM @ 104-A
Teaching Machines, Robots, and Humans
Maya Cakmak · Anna Rafferty · Adish Singla · Xiaojin Zhu · Sandra Zilles
Workshop
Sat Dec 9th 08:00 AM -- 06:30 PM @ Seaside Ballroom
Workshop on Meta-Learning
Roberto Calandra · Frank Hutter · Hugo Larochelle · Sergey Levine
Workshop
Sat Dec 9th 08:00 AM -- 06:30 PM @ Grand Ballroom B
Hierarchical Reinforcement Learning
Andrew G Barto · Doina Precup · Shie Mannor · Tom Schaul · Roy Fox · Carlos Florensa Campo
Workshop
Sat Dec 9th 08:00 AM -- 06:30 PM @ 103 A+B
Machine Learning on the Phone and other Consumer Devices
Hrishikesh Aradhye · Joaquin Quinonero Candela · Rohit Prasad
Workshop
Sat Dec 9th 08:00 AM -- 06:30 PM @ 104-C
Machine Learning in Computational Biology
James Zou · Anshul Kundaje · Gerald Quon · Nicolo Fusi · Sara Mostafavi
Workshop
Sat Dec 9th 08:00 AM -- 06:30 PM @ S-1
Bayesian optimization for science and engineering
Ruben Martinez-Cantin · José Miguel Hernández-Lobato · Javier Gonzalez
Workshop
Sat Dec 9th 08:00 AM -- 06:30 PM @ 101-A
Deep Learning at Supercomputer Scale
Erich Elsen · Danijar Hafner · Zak Stone · Brennan Saeta
Workshop
Sat Dec 9th 08:00 AM -- 06:30 PM @ 201-A
BigNeuro 2017: Analyzing brain data from nano to macroscale
Eva Dyer · Gregory Kiar · William Gray Roncal · · Konrad P Koerding · Joshua T Vogelstein