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Invited Talk (Breiman Lecture)
Thu Dec 06 05:30 AM -- 06:20 AM (PST) @ Room 220 CD
Making Algorithms Trustworthy: What Can Statistical Science Contribute to Transparency, Explanation and Validation?
In Thu Invited Talk 1
David Spiegelhalter
Spotlight
Thu Dec 06 06:45 AM -- 06:50 AM (PST) @ Room 220 CD
Learning with SGD and Random Features
In Thu Track 1 -- Session 1
Luigi Carratino · Alessandro Rudi · Lorenzo Rosasco
Spotlight
Thu Dec 06 06:45 AM -- 06:50 AM (PST) @ Room 220 E
Graphical model inference: Sequential Monte Carlo meets deterministic approximations
In Thu Track 2 -- Session 1
Fredrik Lindsten · Jouni Helske · Matti Vihola
Spotlight
Thu Dec 06 06:45 AM -- 06:50 AM (PST) @ Room 517 CD
Boolean Decision Rules via Column Generation
In Thu Track 3 -- Session 1
Sanjeeb Dash · Oktay Gunluk · Dennis Wei
Spotlight
Thu Dec 06 06:50 AM -- 06:55 AM (PST) @ Room 220 CD
KONG: Kernels for ordered-neighborhood graphs
In Thu Track 1 -- Session 1
Moez Draief · Konstantin Kutzkov · Kevin Scaman · Milan Vojnovic
Spotlight
Thu Dec 06 06:50 AM -- 06:55 AM (PST) @ Room 220 E
Boosting Black Box Variational Inference
In Thu Track 2 -- Session 1
Francesco Locatello · Gideon Dresdner · Rajiv Khanna · Isabel Valera · Gunnar Ratsch
Spotlight
Thu Dec 06 06:50 AM -- 06:55 AM (PST) @ Room 517 CD
Fast greedy algorithms for dictionary selection with generalized sparsity constraints
In Thu Track 3 -- Session 1
Kaito Fujii · Tasuku Soma
Spotlight
Thu Dec 06 06:55 AM -- 07:00 AM (PST) @ Room 220 CD
Quadrature-based features for kernel approximation
In Thu Track 1 -- Session 1
Marina Munkhoeva · Yermek Kapushev · Evgeny Burnaev · Ivan Oseledets
Spotlight
Thu Dec 06 06:55 AM -- 07:00 AM (PST) @ Room 220 E
Discretely Relaxing Continuous Variables for tractable Variational Inference
In Thu Track 2 -- Session 1
Trefor Evans · Prasanth Nair
Spotlight
Thu Dec 06 06:55 AM -- 07:00 AM (PST) @ Room 517 CD
Distributed $k$-Clustering for Data with Heavy Noise
In Thu Track 3 -- Session 1
Shi Li · Xiangyu Guo
Spotlight
Thu Dec 06 07:00 AM -- 07:05 AM (PST) @ Room 220 CD
Statistical and Computational Trade-Offs in Kernel K-Means
In Thu Track 1 -- Session 1
Daniele Calandriello · Lorenzo Rosasco
Spotlight
Thu Dec 06 07:00 AM -- 07:05 AM (PST) @ Room 220 E
Implicit Reparameterization Gradients
In Thu Track 2 -- Session 1
Mikhail Figurnov · Shakir Mohamed · Andriy Mnih
Spotlight
Thu Dec 06 07:00 AM -- 07:05 AM (PST) @ Room 517 CD
Do Less, Get More: Streaming Submodular Maximization with Subsampling
In Thu Track 3 -- Session 1
Moran Feldman · Amin Karbasi · Ehsan Kazemi
Oral
Thu Dec 06 07:05 AM -- 07:20 AM (PST) @ Room 220 CD
Integrated accounts of behavioral and neuroimaging data using flexible recurrent neural network models
In Thu Track 1 -- Session 1
Amir Dezfouli · Richard Morris · Fabio Ramos · Peter Dayan · Bernard Balleine
[ Video] 
Oral
Thu Dec 06 07:05 AM -- 07:20 AM (PST) @ Room 220 E
Variational Inference with Tail-adaptive f-Divergence
In Thu Track 2 -- Session 1
Dilin Wang · Hao Liu · Qiang Liu
[ Video] 
Oral
Thu Dec 06 07:05 AM -- 07:20 AM (PST) @ Room 517 CD
Optimal Algorithms for Continuous Non-monotone Submodular and DR-Submodular Maximization
In Thu Track 3 -- Session 1
Rad Niazadeh · Tim Roughgarden · Joshua Wang
[ Video] 
Spotlight
Thu Dec 06 07:20 AM -- 07:25 AM (PST) @ Room 220 CD
Why Is My Classifier Discriminatory?
In Thu Track 1 -- Session 1
Irene Chen · Fredrik Johansson · David Sontag
Spotlight
Thu Dec 06 07:20 AM -- 07:25 AM (PST) @ Room 220 E
Mirrored Langevin Dynamics
In Thu Track 2 -- Session 1
Ya-Ping Hsieh · Ali Kavis · Paul Rolland · Volkan Cevher
Spotlight
Thu Dec 06 07:20 AM -- 07:25 AM (PST) @ Room 517 CD
Overlapping Clustering Models, and One (class) SVM to Bind Them All
In Thu Track 3 -- Session 1
Xueyu Mao · Purnamrita Sarkar · Deepayan Chakrabarti
Spotlight
Thu Dec 06 07:25 AM -- 07:30 AM (PST) @ Room 220 CD
Human-in-the-Loop Interpretability Prior
In Thu Track 1 -- Session 1
Isaac Lage · Andrew Ross · Samuel J Gershman · Been Kim · Finale Doshi-Velez
Spotlight
Thu Dec 06 07:25 AM -- 07:30 AM (PST) @ Room 220 E
Global Convergence of Langevin Dynamics Based Algorithms for Nonconvex Optimization
In Thu Track 2 -- Session 1
Pan Xu · Jinghui Chen · Difan Zou · Quanquan Gu
Spotlight
Thu Dec 06 07:25 AM -- 07:30 AM (PST) @ Room 517 CD
Removing the Feature Correlation Effect of Multiplicative Noise
In Thu Track 3 -- Session 1
Zijun Zhang · Yining Zhang · Zongpeng Li
Spotlight
Thu Dec 06 07:30 AM -- 07:35 AM (PST) @ Room 220 CD
Link Prediction Based on Graph Neural Networks
In Thu Track 1 -- Session 1
Muhan Zhang · Yixin Chen
Spotlight
Thu Dec 06 07:30 AM -- 07:35 AM (PST) @ Room 220 E
Identification and Estimation of Causal Effects from Dependent Data
In Thu Track 2 -- Session 1
Eli Sherman · Ilya Shpitser
Spotlight
Thu Dec 06 07:30 AM -- 07:35 AM (PST) @ Room 517 CD
Connectionist Temporal Classification with Maximum Entropy Regularization
In Thu Track 3 -- Session 1
Hu Liu · Sheng Jin · Changshui Zhang
Spotlight
Thu Dec 06 07:35 AM -- 07:40 AM (PST) @ Room 220 CD
Realistic Evaluation of Deep Semi-Supervised Learning Algorithms
In Thu Track 1 -- Session 1
Avital Oliver · Augustus Odena · Colin A Raffel · Ekin Dogus Cubuk · Ian Goodfellow
Spotlight
Thu Dec 06 07:35 AM -- 07:40 AM (PST) @ Room 220 E
Causal Inference via Kernel Deviance Measures
In Thu Track 2 -- Session 1
Jovana Mitrovic · Dino Sejdinovic · Yee Whye Teh
Spotlight
Thu Dec 06 07:35 AM -- 07:40 AM (PST) @ Room 517 CD
Entropy and mutual information in models of deep neural networks
In Thu Track 3 -- Session 1
Marylou Gabrié · Andre Manoel · Clément Luneau · jean barbier · Nicolas Macris · Florent Krzakala · Lenka Zdeborová
Spotlight
Thu Dec 06 07:40 AM -- 07:45 AM (PST) @ Room 220 CD
Automatic differentiation in ML: Where we are and where we should be going
In Thu Track 1 -- Session 1
Bart van Merriënboer · Olivier Breuleux · Arnaud Bergeron · Pascal Lamblin
Spotlight
Thu Dec 06 07:40 AM -- 07:45 AM (PST) @ Room 220 E
Removing Hidden Confounding by Experimental Grounding
In Thu Track 2 -- Session 1
Nathan Kallus · Aahlad Puli · Uri Shalit
Spotlight
Thu Dec 06 07:40 AM -- 07:45 AM (PST) @ Room 517 CD
The committee machine: Computational to statistical gaps in learning a two-layers neural network
In Thu Track 3 -- Session 1
Benjamin Aubin · Antoine Maillard · jean barbier · Florent Krzakala · Nicolas Macris · Lenka Zdeborová
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #1
Experimental Design for Cost-Aware Learning of Causal Graphs
In Thu Poster Session A
Erik Lindgren · Murat Kocaoglu · Alex Dimakis · Sriram Vishwanath
[ Paper] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #2
Removing Hidden Confounding by Experimental Grounding
In Thu Poster Session A
Nathan Kallus · Aahlad Puli · Uri Shalit
[ Paper]  [ Poster] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #3
Domain Adaptation by Using Causal Inference to Predict Invariant Conditional Distributions
In Thu Poster Session A
Sara Magliacane · Thijs van Ommen · Tom Claassen · Stephan Bongers · Philip Versteeg · Joris Mooij
[ Paper]  [ Poster] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #4
Structural Causal Bandits: Where to Intervene?
In Thu Poster Session A
Sanghack Lee · Elias Bareinboim
[ Paper]  [ Poster] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #5
Uplift Modeling from Separate Labels
In Thu Poster Session A
Ikko Yamane · Florian Yger · Jamal Atif · Masashi Sugiyama
[ Paper] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #6
Causal Inference with Noisy and Missing Covariates via Matrix Factorization
In Thu Poster Session A
Nathan Kallus · Xiaojie Mao · Madeleine Udell
[ Paper] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #7
Fast Estimation of Causal Interactions using Wold Processes
In Thu Poster Session A
Flavio Figueiredo · Guilherme Resende Borges · Pedro O.S. Vaz de Melo · Renato Assunção
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #8
Learning and Testing Causal Models with Interventions
In Thu Poster Session A
Jayadev Acharya · Arnab Bhattacharyya · Constantinos Daskalakis · Saravanan Kandasamy
[ Paper] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #9
Causal Inference via Kernel Deviance Measures
In Thu Poster Session A
Jovana Mitrovic · Dino Sejdinovic · Yee Whye Teh
[ Paper] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #10
Multi-domain Causal Structure Learning in Linear Systems
In Thu Poster Session A
AmirEmad Ghassami · Negar Kiyavash · Biwei Huang · Kun Zhang
[ Paper] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #11
Causal Inference and Mechanism Clustering of A Mixture of Additive Noise Models
In Thu Poster Session A
Shoubo Hu · Zhitang Chen · Vahid Partovi Nia · Laiwan CHAN · Yanhui Geng
[ Paper]  [ Poster] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #12
Direct Estimation of Differences in Causal Graphs
In Thu Poster Session A
Yuhao Wang · Chandler Squires · Anastasiya Belyaeva · Caroline Uhler
[ Paper] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #13
Identification and Estimation of Causal Effects from Dependent Data
In Thu Poster Session A
Eli Sherman · Ilya Shpitser
[ Paper] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #14
Multilingual Anchoring: Interactive Topic Modeling and Alignment Across Languages
In Thu Poster Session A
Michelle Yuan · Benjamin Van Durme · Jordan Boyd-Graber
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #15
Submodular Field Grammars: Representation, Inference, and Application to Image Parsing
In Thu Poster Session A
Abram Friesen · Pedro Domingos
[ Paper] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #16
Autoconj: Recognizing and Exploiting Conjugacy Without a Domain-Specific Language
In Thu Poster Session A
Matthew D. Hoffman · Matthew Johnson · Dustin Tran
[ Paper] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #17
Distributionally Robust Graphical Models
In Thu Poster Session A
Rizal Fathony · Ashkan Rezaei · Mohammad Ali Bashiri · Xinhua Zhang · Brian Ziebart
[ Paper] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #18
Flexible and accurate inference and learning for deep generative models
In Thu Poster Session A
Eszter Vértes · Maneesh Sahani
[ Paper] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #19
Provable Gaussian Embedding with One Observation
In Thu Poster Session A
Ming Yu · Zhuoran Yang · Tuo Zhao · Mladen Kolar · Zhaoran Wang
[ Paper] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #20
Learning and Inference in Hilbert Space with Quantum Graphical Models
In Thu Poster Session A
Siddarth Srinivasan · Carlton Downey · Byron Boots
[ Paper] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #21
Multi-value Rule Sets for Interpretable Classification with Feature-Efficient Representations
In Thu Poster Session A
Tong Wang
[ Paper] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #22
Nonparametric Bayesian Lomax delegate racing for survival analysis with competing risks
In Thu Poster Session A
Quan Zhang · Mingyuan Zhou
[ Paper]  [ Poster] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #23
Theoretical guarantees for EM under misspecified Gaussian mixture models
In Thu Poster Session A
Raaz Dwivedi · nhật Hồ · Koulik Khamaru · Martin Wainwright · Michael Jordan
[ Paper]  [ Poster] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #24
Nonparametric learning from Bayesian models with randomized objective functions
In Thu Poster Session A
Simon Lyddon · Stephen Walker · Chris C Holmes
[ Paper] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #25
Rectangular Bounding Process
In Thu Poster Session A
Xuhui Fan · Bin Li · Scott SIsson
[ Paper] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #26
A Bayesian Nonparametric View on Count-Min Sketch
In Thu Poster Session A
Diana Cai · Michael Mitzenmacher · Ryan Adams
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #27
Communication Efficient Parallel Algorithms for Optimization on Manifolds
In Thu Poster Session A
Bayan Saparbayeva · Michael Zhang · Lizhen Lin
[ Paper] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #28
Lifted Weighted Mini-Bucket
In Thu Poster Session A
Nicholas Gallo · Alexander Ihler
[ Paper] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #29
Cluster Variational Approximations for Structure Learning of Continuous-Time Bayesian Networks from Incomplete Data
In Thu Poster Session A
Dominik Linzner · Heinz Koeppl
[ Paper]  [ Poster] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #30
Faithful Inversion of Generative Models for Effective Amortized Inference
In Thu Poster Session A
Stefan Webb · Adam Golinski · Rob Zinkov · Siddharth N · Thomas Rainforth · Yee Whye Teh · Frank Wood
[ Paper] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #31
A Stein variational Newton method
In Thu Poster Session A
Gianluca Detommaso · Tiangang Cui · Youssef Marzouk · Alessio Spantini · Robert Scheichl
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #32
Reparameterization Gradient for Non-differentiable Models
In Thu Poster Session A
Wonyeol Lee · Hangyeol Yu · Hongseok Yang
[ Paper] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #33
Implicit Reparameterization Gradients
In Thu Poster Session A
Mikhail Figurnov · Shakir Mohamed · Andriy Mnih
[ Paper]  [ Poster] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #34
SLANG: Fast Structured Covariance Approximations for Bayesian Deep Learning with Natural Gradient
In Thu Poster Session A
Aaron Mishkin · Frederik Kunstner · Didrik Nielsen · Mark Schmidt · Mohammad Emtiyaz Khan
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #35
Wasserstein Variational Inference
In Thu Poster Session A
Luca Ambrogioni · Umut Güçlü · Yağmur Güçlütürk · Max Hinne · Marcel A. J. van Gerven · Eric Maris
[ Paper] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #36
Adaptive Path-Integral Autoencoders: Representation Learning and Planning for Dynamical Systems
In Thu Poster Session A
Jung-Su Ha · Young-Jin Park · Hyeok-Joo Chae · Soon-Seo Park · Han-Lim Choi
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #37
Variational Inference with Tail-adaptive f-Divergence
In Thu Poster Session A
Dilin Wang · Hao Liu · Qiang Liu
[ Paper] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #38
Boosting Black Box Variational Inference
In Thu Poster Session A
Francesco Locatello · Gideon Dresdner · Rajiv Khanna · Isabel Valera · Gunnar Ratsch
[ Paper]  [ Poster] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #39
Discretely Relaxing Continuous Variables for tractable Variational Inference
In Thu Poster Session A
Trefor Evans · Prasanth Nair
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #40
Using Large Ensembles of Control Variates for Variational Inference
In Thu Poster Session A
Tomas Geffner · Justin Domke
[ Paper] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #41
The promises and pitfalls of Stochastic Gradient Langevin Dynamics
In Thu Poster Session A
Nicolas Brosse · Alain Durmus · Eric Moulines
[ Paper] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #42
Large-Scale Stochastic Sampling from the Probability Simplex
In Thu Poster Session A
Jack Baker · Paul Fearnhead · Emily Fox · Christopher Nemeth
[ Paper]  [ Poster] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #43
Mirrored Langevin Dynamics
In Thu Poster Session A
Ya-Ping Hsieh · Ali Kavis · Paul Rolland · Volkan Cevher
[ Paper] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #44
Thermostat-assisted continuously-tempered Hamiltonian Monte Carlo for Bayesian learning
In Thu Poster Session A
Rui Luo · Jianhong Wang · Yaodong Yang · Jun WANG · Zhanxing Zhu
[ Paper] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #45
Dimensionally Tight Bounds for Second-Order Hamiltonian Monte Carlo
In Thu Poster Session A
Oren Mangoubi · Nisheeth Vishnoi
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #46
Global Convergence of Langevin Dynamics Based Algorithms for Nonconvex Optimization
In Thu Poster Session A
Pan Xu · Jinghui Chen · Difan Zou · Quanquan Gu
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #47
Meta-Learning MCMC Proposals
In Thu Poster Session A
Tongzhou Wang · YI WU · Dave Moore · Stuart Russell
[ Paper] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #48
Posterior Concentration for Sparse Deep Learning
In Thu Poster Session A
Veronika Rockova · nicholas polson
[ Paper] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #49
Analytic solution and stationary phase approximation for the Bayesian lasso and elastic net
In Thu Poster Session A
Tom Michoel
[ Paper]  [ Poster] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #50
Bayesian Model Selection Approach to Boundary Detection with Non-Local Priors
In Thu Poster Session A
Fei Jiang · Guosheng Yin · Francesca Dominici
[ Paper] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #51
Graphical model inference: Sequential Monte Carlo meets deterministic approximations
In Thu Poster Session A
Fredrik Lindsten · Jouni Helske · Matti Vihola
[ Paper]  [ Poster] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #52
Implicit Probabilistic Integrators for ODEs
In Thu Poster Session A
Onur Teymur · Han Cheng Lie · Tim Sullivan · Ben Calderhead
[ Paper] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #53
A Bayes-Sard Cubature Method
In Thu Poster Session A
Toni Karvonen · Chris Oates · Simo Sarkka
[ Paper]  [ Poster] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #54
Deep State Space Models for Time Series Forecasting
In Thu Poster Session A
Syama Sundar Rangapuram · Matthias W Seeger · Jan Gasthaus · Lorenzo Stella · Bernie Wang · Tim Januschowski
[ Paper] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #55
BRUNO: A Deep Recurrent Model for Exchangeable Data
In Thu Poster Session A
Iryna Korshunova · Jonas Degrave · Ferenc Huszar · Yarin Gal · Arthur Gretton · Joni Dambre
[ Paper]  [ Poster] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #56
Scaling Gaussian Process Regression with Derivatives
In Thu Poster Session A
David Eriksson · Kun Dong · Eric Lee · David Bindel · Andrew Wilson
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #57
Algebraic tests of general Gaussian latent tree models
In Thu Poster Session A
Dennis Leung · Mathias Drton
[ Paper]  [ Poster] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #58
Differentially Private Bayesian Inference for Exponential Families
In Thu Poster Session A
Garrett Bernstein · Daniel Sheldon
[ Paper] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #59
Semi-crowdsourced Clustering with Deep Generative Models
In Thu Poster Session A
Yucen Luo · TIAN TIAN · Jiaxin Shi · Jun Zhu · Bo Zhang
[ Paper]  [ Poster] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #60
Deep Poisson gamma dynamical systems
In Thu Poster Session A
Dandan Guo · Bo Chen · Hao Zhang · Mingyuan Zhou
[ Paper]  [ Poster] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #61
Deep State Space Models for Unconditional Word Generation
In Thu Poster Session A
Florian Schmidt · Thomas Hofmann
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #62
Modular Networks: Learning to Decompose Neural Computation
In Thu Poster Session A
Louis Kirsch · Julius Kunze · David Barber
[ Paper]  [ Poster] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #63
Gaussian Process Prior Variational Autoencoders
In Thu Poster Session A
Francesco Paolo Casale · Adrian Dalca · Luca Saglietti · Jennifer Listgarten · Nicolo Fusi
[ Paper] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #64
Bayesian Semi-supervised Learning with Graph Gaussian Processes
In Thu Poster Session A
Yin Cheng Ng · Nicolò Colombo · Ricardo Silva
[ Paper] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #65
Inference in Deep Gaussian Processes using Stochastic Gradient Hamiltonian Monte Carlo
In Thu Poster Session A
Marton Havasi · José Miguel Hernández-Lobato · Juan J. Murillo-Fuentes
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #66
Variational Bayesian Monte Carlo
In Thu Poster Session A
Luigi Acerbi
[ Paper]  [ Poster] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #67
Bayesian Alignments of Warped Multi-Output Gaussian Processes
In Thu Poster Session A
Markus Kaiser · Clemens Otte · Thomas Runkler · Carl Henrik Ek
[ Paper]  [ Poster] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #68
Automating Bayesian optimization with Bayesian optimization
In Thu Poster Session A
Gustavo Malkomes · Roman Garnett
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #69
Infinite-Horizon Gaussian Processes
In Thu Poster Session A
Arno Solin · James Hensman · Richard Turner
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #70
Learning Gaussian Processes by Minimizing PAC-Bayesian Generalization Bounds
In Thu Poster Session A
David Reeb · Andreas Doerr · Sebastian Gerwinn · Barbara Rakitsch
[ Paper]  [ Poster] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #71
Algorithmic Linearly Constrained Gaussian Processes
In Thu Poster Session A
Markus Lange-Hegermann
[ Paper] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #72
Efficient Projection onto the Perfect Phylogeny Model
In Thu Poster Session A
Bei Jia · Surjyendu Ray · Sam Safavi · José Bento
[ Paper] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #73
Distributed $k$-Clustering for Data with Heavy Noise
In Thu Poster Session A
Shi Li · Xiangyu Guo
[ Paper] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #74
Communication Compression for Decentralized Training
In Thu Poster Session A
Hanlin Tang · Shaoduo Gan · Ce Zhang · Tong Zhang · Ji Liu
[ Paper]  [ Poster] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #75
Do Less, Get More: Streaming Submodular Maximization with Subsampling
In Thu Poster Session A
Moran Feldman · Amin Karbasi · Ehsan Kazemi
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #76
Optimal Algorithms for Continuous Non-monotone Submodular and DR-Submodular Maximization
In Thu Poster Session A
Rad Niazadeh · Tim Roughgarden · Joshua Wang
[ Paper] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #77
Provable Variational Inference for Constrained Log-Submodular Models
In Thu Poster Session A
Josip Djolonga · Stefanie Jegelka · Andreas Krause
[ Paper] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #78
Fast greedy algorithms for dictionary selection with generalized sparsity constraints
In Thu Poster Session A
Kaito Fujii · Tasuku Soma
[ Paper]  [ Poster] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #79
Boolean Decision Rules via Column Generation
In Thu Poster Session A
Sanjeeb Dash · Oktay Gunluk · Dennis Wei
[ Paper]  [ Poster] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #80
Computing Kantorovich-Wasserstein Distances on $d$-dimensional histograms using $(d+1)$-partite graphs
In Thu Poster Session A
Gennaro Auricchio · Federico Bassetti · Stefano Gualandi · Marco Veneroni
[ Paper]  [ Poster] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #81
Adaptive Negative Curvature Descent with Applications in Non-convex Optimization
In Thu Poster Session A
Mingrui Liu · Zhe Li · Xiaoyu Wang · Jinfeng Yi · Tianbao Yang
[ Paper] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #82
Implicit Bias of Gradient Descent on Linear Convolutional Networks
In Thu Poster Session A
Suriya Gunasekar · Jason Lee · Daniel Soudry · Nati Srebro
[ Paper] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #83
Deep Generative Models for Distribution-Preserving Lossy Compression
In Thu Poster Session A
Michael Tschannen · Eirikur Agustsson · Mario Lucic
[ Paper]  [ Poster] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #84
Visual Object Networks: Image Generation with Disentangled 3D Representations
In Thu Poster Session A
Jun-Yan Zhu · Zhoutong Zhang · Chengkai Zhang · Jiajun Wu · Antonio Torralba · Josh Tenenbaum · Bill Freeman
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #85
Nonlocal Neural Networks, Nonlocal Diffusion and Nonlocal Modeling
In Thu Poster Session A
Yunzhe Tao · Qi Sun · Qiang Du · Wei Liu
[ Paper] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #86
Can We Gain More from Orthogonality Regularizations in Training Deep Networks?
In Thu Poster Session A
Nitin Bansal · Xiaohan Chen · Zhangyang Wang
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #87
Discrimination-aware Channel Pruning for Deep Neural Networks
In Thu Poster Session A
Zhuangwei Zhuang · Mingkui Tan · Bohan Zhuang · Jing Liu · Yong Guo · Qingyao Wu · Junzhou Huang · Jinhui Zhu
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #88
Probabilistic Model-Agnostic Meta-Learning
In Thu Poster Session A
Chelsea Finn · Kelvin Xu · Sergey Levine
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #89
FastGRNN: A Fast, Accurate, Stable and Tiny Kilobyte Sized Gated Recurrent Neural Network
In Thu Poster Session A
Aditya Kusupati · Manish Singh · Kush Bhatia · Ashish Kumar · Prateek Jain · Manik Varma
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #90
Understanding Batch Normalization
In Thu Poster Session A
Johan Bjorck · Carla Gomes · Bart Selman · Kilian Weinberger
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #91
How Many Samples are Needed to Estimate a Convolutional Neural Network?
In Thu Poster Session A
Simon Du · Yining Wang · Xiyu Zhai · Sivaraman Balakrishnan · Russ Salakhutdinov · Aarti Singh
[ Paper] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #92
Robust Detection of Adversarial Attacks by Modeling the Intrinsic Properties of Deep Neural Networks
In Thu Poster Session A
Zhihao Zheng · Pengyu Hong
[ Paper] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #93
Combinatorial Optimization with Graph Convolutional Networks and Guided Tree Search
In Thu Poster Session A
Zhuwen Li · Qifeng Chen · Vladlen Koltun
[ Paper] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #94
Automatic differentiation in ML: Where we are and where we should be going
In Thu Poster Session A
Bart van Merriënboer · Olivier Breuleux · Arnaud Bergeron · Pascal Lamblin
[ Paper] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #95
Realistic Evaluation of Deep Semi-Supervised Learning Algorithms
In Thu Poster Session A
Avital Oliver · Augustus Odena · Colin A Raffel · Ekin Dogus Cubuk · Ian Goodfellow
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #96
Toddler-Inspired Visual Object Learning
In Thu Poster Session A
Sven Bambach · David Crandall · Linda Smith · Chen Yu
[ Paper]  [ Poster] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #97
Generalisation in humans and deep neural networks
In Thu Poster Session A
Robert Geirhos · Carlos R. M. Temme · Jonas Rauber · Heiko H. Schütt · Matthias Bethge · Felix A. Wichmann
[ Paper] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #98
Assessing the Scalability of Biologically-Motivated Deep Learning Algorithms and Architectures
In Thu Poster Session A
Sergey Bartunov · Adam Santoro · Blake Richards · Luke Marris · Geoffrey E Hinton · Timothy Lillicrap
[ Paper] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #99
Incorporating Context into Language Encoding Models for fMRI
In Thu Poster Session A
Shailee Jain · Alexander Huth
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #101
Mental Sampling in Multimodal Representations
In Thu Poster Session A
Jianqiao Zhu · Adam Sanborn · Nick Chater
[ Paper] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #102
Integrated accounts of behavioral and neuroimaging data using flexible recurrent neural network models
In Thu Poster Session A
Amir Dezfouli · Richard Morris · Fabio Ramos · Peter Dayan · Bernard Balleine
[ Paper]  [ Poster] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #103
Efficient inference for time-varying behavior during learning
In Thu Poster Session A
Nicholas Roy · Ji Hyun Bak · Athena Akrami · Carlos Brody · Jonathan Pillow
[ Paper] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #104
Multivariate Convolutional Sparse Coding for Electromagnetic Brain Signals
In Thu Poster Session A
Tom Dupré la Tour · Thomas Moreau · Mainak Jas · Alexandre Gramfort
[ Paper]  [ Poster] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #105
Manifold-tiling Localized Receptive Fields are Optimal in Similarity-preserving Neural Networks
In Thu Poster Session A
Anirvan Sengupta · Cengiz Pehlevan · Mariano Tepper · Alexander Genkin · Dmitri Chklovskii
[ Paper] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #106
Connectionist Temporal Classification with Maximum Entropy Regularization
In Thu Poster Session A
Hu Liu · Sheng Jin · Changshui Zhang
[ Paper]  [ Poster] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #107
Removing the Feature Correlation Effect of Multiplicative Noise
In Thu Poster Session A
Zijun Zhang · Yining Zhang · Zongpeng Li
[ Paper]  [ Poster] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #108
Overfitting or perfect fitting? Risk bounds for classification and regression rules that interpolate
In Thu Poster Session A
Mikhail Belkin · Daniel Hsu · Partha P Mitra
[ Paper] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #109
Smoothed Analysis of Discrete Tensor Decomposition and Assemblies of Neurons
In Thu Poster Session A
Nima Anari · Constantinos Daskalakis · Wolfgang Maass · Christos Papadimitriou · Amin Saberi · Santosh Vempala
[ Paper] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #110
Entropy and mutual information in models of deep neural networks
In Thu Poster Session A
Marylou Gabrié · Andre Manoel · Clément Luneau · jean barbier · Nicolas Macris · Florent Krzakala · Lenka Zdeborová
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #111
The committee machine: Computational to statistical gaps in learning a two-layers neural network
In Thu Poster Session A
Benjamin Aubin · Antoine Maillard · jean barbier · Florent Krzakala · Nicolas Macris · Lenka Zdeborová
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #112
A Unified Framework for Extensive-Form Game Abstraction with Bounds
In Thu Poster Session A
Christian Kroer · Tuomas Sandholm
[ Paper] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #113
Connecting Optimization and Regularization Paths
In Thu Poster Session A
Arun Suggala · Adarsh Prasad · Pradeep Ravikumar
[ Paper] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #114
Overlapping Clustering Models, and One (class) SVM to Bind Them All
In Thu Poster Session A
Xueyu Mao · Purnamrita Sarkar · Deepayan Chakrabarti
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #115
Learning latent variable structured prediction models with Gaussian perturbations
In Thu Poster Session A
Kevin Bello · Jean Honorio
[ Paper] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #116
Self-Supervised Generation of Spatial Audio for 360° Video
In Thu Poster Session A
Pedro Morgado · Nuno Nvasconcelos · Timothy Langlois · Oliver Wang
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #117
Symbolic Graph Reasoning Meets Convolutions
In Thu Poster Session A
Xiaodan Liang · Zhiting Hu · Hao Zhang · Liang Lin · Eric Xing
[ Paper] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #118
Towards Deep Conversational Recommendations
In Thu Poster Session A
Raymond Li · Samira Ebrahimi Kahou · Hannes Schulz · Vincent Michalski · Laurent Charlin · Chris Pal
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #119
Human-in-the-Loop Interpretability Prior
In Thu Poster Session A
Isaac Lage · Andrew Ross · Samuel J Gershman · Been Kim · Finale Doshi-Velez
[ Paper] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #120
Why Is My Classifier Discriminatory?
In Thu Poster Session A
Irene Chen · Fredrik Johansson · David Sontag
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #121
Link Prediction Based on Graph Neural Networks
In Thu Poster Session A
Muhan Zhang · Yixin Chen
[ Paper] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #122
KONG: Kernels for ordered-neighborhood graphs
In Thu Poster Session A
Moez Draief · Konstantin Kutzkov · Kevin Scaman · Milan Vojnovic
[ Paper]  [ Poster] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #123
Efficient Stochastic Gradient Hard Thresholding
In Thu Poster Session A
Pan Zhou · Xiaotong Yuan · Jiashi Feng
[ Paper] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #124
Measures of distortion for machine learning
In Thu Poster Session A
Leena Chennuru Vankadara · Ulrike von Luxburg
[ Paper] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #125
Relating Leverage Scores and Density using Regularized Christoffel Functions
In Thu Poster Session A
Edouard Pauwels · Francis Bach · Jean-Philippe Vert
[ Paper]  [ Poster] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #126
Streaming Kernel PCA with $\tilde{O}(\sqrt{n})$ Random Features
In Thu Poster Session A
Enayat Ullah · Poorya Mianjy · Teodor Vanislavov Marinov · Raman Arora
[ Paper]  [ Poster] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #127
Learning with SGD and Random Features
In Thu Poster Session A
Luigi Carratino · Alessandro Rudi · Lorenzo Rosasco
[ Paper] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #128
But How Does It Work in Theory? Linear SVM with Random Features
In Thu Poster Session A
Yitong Sun · Anna Gilbert · Ambuj Tewari
[ Paper]  [ Poster] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #129
Statistical and Computational Trade-Offs in Kernel K-Means
In Thu Poster Session A
Daniele Calandriello · Lorenzo Rosasco
[ Paper] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #130
Quadrature-based features for kernel approximation
In Thu Poster Session A
Marina Munkhoeva · Yermek Kapushev · Evgeny Burnaev · Ivan Oseledets
[ Paper]  [ Poster] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #131
Processing of missing data by neural networks
In Thu Poster Session A
Marek Śmieja · Łukasz Struski · Jacek Tabor · Bartosz Zieliński · Przemysław Spurek
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #132
Constructing Deep Neural Networks by Bayesian Network Structure Learning
In Thu Poster Session A
Raanan Rohekar · Shami Nisimov · Yaniv Gurwicz · Guy Koren · Gal Novik
[ Paper] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #133
Mallows Models for Top-k Lists
In Thu Poster Session A
Flavio Chierichetti · Anirban Dasgupta · Shahrzad Haddadan · Ravi Kumar · Silvio Lattanzi
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #134
Cooperative neural networks (CoNN): Exploiting prior independence structure for improved classification
In Thu Poster Session A
Harsh Shrivastava · Eugene Bart · Bob Price · Hanjun Dai · Bo Dai · Srinivas Aluru
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #135
Maximum-Entropy Fine Grained Classification
In Thu Poster Session A
Abhimanyu Dubey · Otkrist Gupta · Ramesh Raskar · Nikhil Naik
[ Paper] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #136
Efficient Loss-Based Decoding on Graphs for Extreme Classification
In Thu Poster Session A
Itay Evron · Edward Moroshko · Yacov Crammer
[ Paper]  [ Poster] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #137
A no-regret generalization of hierarchical softmax to extreme multi-label classification
In Thu Poster Session A
Marek Wydmuch · Kalina Jasinska-Kobus · Mikhail Kuznetsov · Róbert Busa-Fekete · Krzysztof Dembczynski
[ Paper]  [ Poster] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #138
Efficient Gradient Computation for Structured Output Learning with Rational and Tropical Losses
In Thu Poster Session A
Corinna Cortes · Vitaly Kuznetsov · Mehryar Mohri · Dmitry Storcheus · Scott Yang
[ Paper] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #139
Deep Structured Prediction with Nonlinear Output Transformations
In Thu Poster Session A
Colin Graber · Ofer Meshi · Alex Schwing
[ Paper]  [ Poster] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #140
Mapping Images to Scene Graphs with Permutation-Invariant Structured Prediction
In Thu Poster Session A
Roei Herzig · Moshiko Raboh · Gal Chechik · Jonathan Berant · Amir Globerson
[ Paper]  [ Poster] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #141
Large Margin Deep Networks for Classification
In Thu Poster Session A
Gamaleldin Elsayed · Dilip Krishnan · Hossein Mobahi · Kevin Regan · Samy Bengio
[ Paper] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #142
Semi-supervised Deep Kernel Learning: Regression with Unlabeled Data by Minimizing Predictive Variance
In Thu Poster Session A
Neal Jean · Sang Michael Xie · Stefano Ermon
[ Paper] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #143
Multitask Boosting for Survival Analysis with Competing Risks
In Thu Poster Session A
Alexis Bellot · Mihaela van der Schaar
[ Paper] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #144
Multi-Layered Gradient Boosting Decision Trees
In Thu Poster Session A
Ji Feng · Yang Yu · Zhi-Hua Zhou
[ Paper] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #145
Unsupervised Adversarial Invariance
In Thu Poster Session A
Ayush Jaiswal · Rex Yue Wu · Wael Abd-Almageed · Prem Natarajan
[ Paper] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #146
Learning Deep Disentangled Embeddings With the F-Statistic Loss
In Thu Poster Session A
Karl Ridgeway · Michael Mozer
[ Paper]  [ Poster] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #147
Learning Latent Subspaces in Variational Autoencoders
In Thu Poster Session A
Jack Klys · Jake Snell · Richard Zemel
[ Paper] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #148
Dual Swap Disentangling
In Thu Poster Session A
Zunlei Feng · Xinchao Wang · Chenglong Ke · An-Xiang Zeng · Dacheng Tao · Mingli Song
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #149
Joint Autoregressive and Hierarchical Priors for Learned Image Compression
In Thu Poster Session A
David Minnen · Johannes Ballé · Johannes Ballé · George D Toderici
[ Paper]  [ Poster] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #150
Group Equivariant Capsule Networks
In Thu Poster Session A
Jan Eric Lenssen · Matthias Fey · Pascal Libuschewski
[ Paper] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #151
Learning Disentangled Joint Continuous and Discrete Representations
In Thu Poster Session A
Emilien Dupont
[ Paper] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #152
Image-to-image translation for cross-domain disentanglement
In Thu Poster Session A
Abel Gonzalez-Garcia · Joost van de Weijer · Yoshua Bengio
[ Paper] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB
Cooperative Learning of Audio and Video Models from Self-Supervised Synchronization
In Thu Poster Session A
Bruno Korbar · Du Tran · Lorenzo Torresani
[ Paper]  [ Poster] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #154
Non-Adversarial Mapping with VAEs
In Thu Poster Session A
Yedid Hoshen
[ Paper] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #155
Learning to Teach with Dynamic Loss Functions
In Thu Poster Session A
Lijun Wu · Fei Tian · Yingce Xia · Yang Fan · Tao Qin · Lai Jian-Huang · Tie-Yan Liu
[ Paper] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #156
Maximizing acquisition functions for Bayesian optimization
In Thu Poster Session A
James Wilson · Frank Hutter · Marc Deisenroth
[ Paper] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #157
MetaReg: Towards Domain Generalization using Meta-Regularization
In Thu Poster Session A
Yogesh Balaji · Swami Sankaranarayanan · Rama Chellappa
[ Paper]  [ Poster] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #158
Transfer Learning with Neural AutoML
In Thu Poster Session A
Catherine Wong · Neil Houlsby · Yifeng Lu · Andrea Gesmundo
[ Paper]  [ Poster] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #159
Hierarchical Reinforcement Learning for Zero-shot Generalization with Subtask Dependencies
In Thu Poster Session A
Sungryull Sohn · Junhyuk Oh · Honglak Lee
[ Paper] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #160
Lifelong Inverse Reinforcement Learning
In Thu Poster Session A
Jorge Mendez · Shashank Shivkumar · Eric Eaton
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #161
Safe Active Learning for Time-Series Modeling with Gaussian Processes
In Thu Poster Session A
Christoph Zimmer · Mona Meister · Duy Nguyen-Tuong
[ Paper] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #162
Online Structure Learning for Feed-Forward and Recurrent Sum-Product Networks
In Thu Poster Session A
Agastya Kalra · Abdullah Rashwan · Wei-Shou Hsu · Pascal Poupart · Prashant Doshi · George Trimponias
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #163
Preference Based Adaptation for Learning Objectives
In Thu Poster Session A
Yao-Xiang Ding · Zhi-Hua Zhou
[ Paper] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #164
Byzantine Stochastic Gradient Descent
In Thu Poster Session A
Dan Alistarh · Zeyuan Allen-Zhu · Jerry Li
[ Paper] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #165
Contextual bandits with surrogate losses: Margin bounds and efficient algorithms
In Thu Poster Session A
Dylan Foster · Akshay Krishnamurthy
[ Paper] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #166
Online Learning of Quantum States
In Thu Poster Session A
Scott Aaronson · Xinyi Chen · Elad Hazan · Satyen Kale · Ashwin Nayak
[ Paper] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #167
Horizon-Independent Minimax Linear Regression
In Thu Poster Session A
Alan Malek · Peter Bartlett
[ Paper]  [ Poster] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #168
Factored Bandits
In Thu Poster Session A
Julian Zimmert · Yevgeny Seldin
[ Paper] 
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #169
A Model for Learned Bloom Filters and Optimizing by Sandwiching
In Thu Poster Session A
Michael Mitzenmacher
[ Paper]  [ Poster] 
Break
Thu Dec 06 09:20 AM -- 09:45 AM (PST)
Coffee Break
Invited Talk
Thu Dec 06 11:15 AM -- 12:05 PM (PST) @ Room 220 CD
Designing Computer Systems for Software 2.0
In Thu Invited Talk 2
Kunle Olukotun
Spotlight
Thu Dec 06 12:30 PM -- 12:35 PM (PST) @ Room 220 CD
Robust Subspace Approximation in a Stream
In Thu Track 1 -- Session 2
Roie Levin · Anish Prasad Sevekari · David Woodruff
Spotlight
Thu Dec 06 12:30 PM -- 12:35 PM (PST) @ Room 220 E
Hyperbolic Neural Networks
In Thu Track 2 -- Session 2
Octavian Ganea · Gary Becigneul · Thomas Hofmann
Spotlight
Thu Dec 06 12:30 PM -- 12:35 PM (PST) @ Room 517 CD
A Simple Proximal Stochastic Gradient Method for Nonsmooth Nonconvex Optimization
In Thu Track 3 -- Session 2
Zhize Li · Jian Li
Spotlight
Thu Dec 06 12:35 PM -- 12:40 PM (PST) @ Room 220 CD
Efficient nonmyopic batch active search
In Thu Track 1 -- Session 2
Shali Jiang · Gustavo Malkomes · Matthew Abbott · Benjamin Moseley · Roman Garnett
Spotlight
Thu Dec 06 12:35 PM -- 12:40 PM (PST) @ Room 220 E
Norm matters: efficient and accurate normalization schemes in deep networks
In Thu Track 2 -- Session 2
Elad Hoffer · Ron Banner · Itay Golan · Daniel Soudry
Spotlight
Thu Dec 06 12:35 PM -- 12:40 PM (PST) @ Room 517 CD
Stochastic Chebyshev Gradient Descent for Spectral Optimization
In Thu Track 3 -- Session 2
Insu Han · Haim Avron · Jinwoo Shin
Spotlight
Thu Dec 06 12:40 PM -- 12:45 PM (PST) @ Room 220 CD
Interactive Structure Learning with Structural Query-by-Committee
In Thu Track 1 -- Session 2
Christopher Tosh · Sanjoy Dasgupta
Spotlight
Thu Dec 06 12:40 PM -- 12:45 PM (PST) @ Room 220 E
Constructing Fast Network through Deconstruction of Convolution
In Thu Track 2 -- Session 2
Yunho Jeon · Junmo Kim
Spotlight
Thu Dec 06 12:40 PM -- 12:45 PM (PST) @ Room 517 CD
LAG: Lazily Aggregated Gradient for Communication-Efficient Distributed Learning
In Thu Track 3 -- Session 2
Tianyi Chen · Georgios Giannakis · Tao Sun · Wotao Yin
Spotlight
Thu Dec 06 12:45 PM -- 12:50 PM (PST) @ Room 220 CD
Contour location via entropy reduction leveraging multiple information sources
In Thu Track 1 -- Session 2
Alexandre Marques · Remi Lam · Karen Willcox
Spotlight
Thu Dec 06 12:45 PM -- 12:50 PM (PST) @ Room 220 E
A Simple Unified Framework for Detecting Out-of-Distribution Samples and Adversarial Attacks
In Thu Track 2 -- Session 2
Kimin Lee · Kibok Lee · Honglak Lee · Jinwoo Shin
Spotlight
Thu Dec 06 12:45 PM -- 12:50 PM (PST) @ Room 517 CD
Low-rank Interaction with Sparse Additive Effects Model for Large Data Frames
In Thu Track 3 -- Session 2
Geneviève Robin · Hoi-To Wai · Julie Josse · Olga Klopp · Eric Moulines
Oral
Thu Dec 06 12:50 PM -- 01:05 PM (PST) @ Room 220 CD
Sample-Efficient Reinforcement Learning with Stochastic Ensemble Value Expansion
In Thu Track 1 -- Session 2
Jacob Buckman · Danijar Hafner · George Tucker · Eugene Brevdo · Honglak Lee
[ Video] 
Oral
Thu Dec 06 12:50 PM -- 01:05 PM (PST) @ Room 220 E
Discovery of Latent 3D Keypoints via End-to-end Geometric Reasoning
In Thu Track 2 -- Session 2
Supasorn Suwajanakorn · Noah Snavely · Jonathan Tompson · Mohammad Norouzi
[ Video] 
Oral
Thu Dec 06 12:50 PM -- 01:05 PM (PST) @ Room 517 CD
Optimal Algorithms for Non-Smooth Distributed Optimization in Networks
In Thu Track 3 -- Session 2
Kevin Scaman · Francis Bach · Sebastien Bubeck · Laurent Massoulié · Yin Tat Lee
[ Slides]  [ Video] 
Spotlight
Thu Dec 06 01:05 PM -- 01:10 PM (PST) @ Room 220 CD
Policy-Conditioned Uncertainty Sets for Robust Markov Decision Processes
In Thu Track 1 -- Session 2
Andrea Tirinzoni · Marek Petrik · Xiangli Chen · Brian Ziebart
Spotlight
Thu Dec 06 01:05 PM -- 01:10 PM (PST) @ Room 220 E
Learning Libraries of Subroutines for Neurally–Guided Bayesian Program Induction
In Thu Track 2 -- Session 2
Kevin Ellis · Lucas Morales · Mathias Sablé-Meyer · Armando Solar-Lezama · Josh Tenenbaum
Spotlight
Thu Dec 06 01:05 PM -- 01:10 PM (PST) @ Room 517 CD
Direct Runge-Kutta Discretization Achieves Acceleration
In Thu Track 3 -- Session 2
Jingzhao Zhang · Aryan Mokhtari · Suvrit Sra · Ali Jadbabaie
Spotlight
Thu Dec 06 01:10 PM -- 01:15 PM (PST) @ Room 220 CD
Learning convex bounds for linear quadratic control policy synthesis
In Thu Track 1 -- Session 2
Jack Umenberger · Thomas Schön
Spotlight
Thu Dec 06 01:10 PM -- 01:15 PM (PST) @ Room 220 E
Learning Loop Invariants for Program Verification
In Thu Track 2 -- Session 2
Xujie Si · Hanjun Dai · Mukund Raghothaman · Mayur Naik · Le Song
Spotlight
Thu Dec 06 01:10 PM -- 01:15 PM (PST) @ Room 517 CD
Limited Memory Kelley's Method Converges for Composite Convex and Submodular Objectives
In Thu Track 3 -- Session 2
Song Zhou · Swati Gupta · Madeleine Udell
Spotlight
Thu Dec 06 01:15 PM -- 01:20 PM (PST) @ Room 220 CD
Multiple-Step Greedy Policies in Approximate and Online Reinforcement Learning
In Thu Track 1 -- Session 2
Yonathan Efroni · Gal Dalal · Bruno Scherrer · Shie Mannor
Spotlight
Thu Dec 06 01:15 PM -- 01:20 PM (PST) @ Room 220 E
DeepProbLog: Neural Probabilistic Logic Programming
In Thu Track 2 -- Session 2
Robin Manhaeve · Sebastijan Dumancic · Angelika Kimmig · Thomas Demeester · Luc De Raedt
Spotlight
Thu Dec 06 01:15 PM -- 01:20 PM (PST) @ Room 517 CD
(Probably) Concave Graph Matching
In Thu Track 3 -- Session 2
Haggai Maron · Yaron Lipman
Spotlight
Thu Dec 06 01:20 PM -- 01:25 PM (PST) @ Room 220 CD
Deep Reinforcement Learning in a Handful of Trials using Probabilistic Dynamics Models
In Thu Track 1 -- Session 2
Kurtland Chua · Roberto Calandra · Rowan McAllister · Sergey Levine
Spotlight
Thu Dec 06 01:20 PM -- 01:25 PM (PST) @ Room 220 E
Learning to Infer Graphics Programs from Hand-Drawn Images
In Thu Track 2 -- Session 2
Kevin Ellis · Daniel Ritchie · Armando Solar-Lezama · Josh Tenenbaum
Spotlight
Thu Dec 06 01:20 PM -- 01:25 PM (PST) @ Room 517 CD
Graph Oracle Models, Lower Bounds, and Gaps for Parallel Stochastic Optimization
In Thu Track 3 -- Session 2
Blake Woodworth · Jialei Wang · Adam Smith · Brendan McMahan · Nati Srebro
Oral
Thu Dec 06 01:25 PM -- 01:40 PM (PST) @ Room 220 CD
Non-delusional Q-learning and value-iteration
In Thu Track 1 -- Session 2
Tyler Lu · Dale Schuurmans · Craig Boutilier
[ Video] 
Oral
Thu Dec 06 01:25 PM -- 01:40 PM (PST) @ Room 220 E
Learning to Reconstruct Shapes from Unseen Classes
In Thu Track 2 -- Session 2
Xiuming Zhang · Zhoutong Zhang · Chengkai Zhang · Josh Tenenbaum · Bill Freeman · Jiajun Wu
[ Video] 
Oral
Thu Dec 06 01:25 PM -- 01:40 PM (PST) @ Room 517 CD
Smoothed analysis of the low-rank approach for smooth semidefinite programs
In Thu Track 3 -- Session 2
Thomas Pumir · Samy Jelassi · Nicolas Boumal
[ Video] 
Spotlight
Thu Dec 06 01:40 PM -- 01:45 PM (PST) @ Room 220 CD
Bilevel learning of the Group Lasso structure
In Thu Track 1 -- Session 2
Jordan Frecon · Saverio Salzo · Massimiliano Pontil
Spotlight
Thu Dec 06 01:40 PM -- 01:45 PM (PST) @ Room 220 E
Improving Neural Program Synthesis with Inferred Execution Traces
In Thu Track 2 -- Session 2
Richard Shin · Illia Polosukhin · Dawn Song
Spotlight
Thu Dec 06 01:40 PM -- 01:45 PM (PST) @ Room 517 CD
Wasserstein Distributionally Robust Kalman Filtering
In Thu Track 3 -- Session 2
Soroosh Shafieezadeh Abadeh · Viet Anh Nguyen · Daniel Kuhn · Peyman Mohajerin Esfahani
Spotlight
Thu Dec 06 01:45 PM -- 01:50 PM (PST) @ Room 220 CD
Binary Classification from Positive-Confidence Data
In Thu Track 1 -- Session 2
Takashi Ishida · Gang Niu · Masashi Sugiyama
Spotlight
Thu Dec 06 01:45 PM -- 01:50 PM (PST) @ Room 220 E
ResNet with one-neuron hidden layers is a Universal Approximator
In Thu Track 2 -- Session 2
Hongzhou Lin · Stefanie Jegelka
Spotlight
Thu Dec 06 01:45 PM -- 01:50 PM (PST) @ Room 517 CD
Decentralize and Randomize: Faster Algorithm for Wasserstein Barycenters
In Thu Track 3 -- Session 2
Pavel Dvurechenskii · Darina Dvinskikh · Alexander Gasnikov · Cesar Uribe · Angelia Nedich
Spotlight
Thu Dec 06 01:50 PM -- 01:55 PM (PST) @ Room 220 CD
Fully Understanding The Hashing Trick
In Thu Track 1 -- Session 2
Casper B. Freksen · Lior Kamma · Kasper Green Larsen
Spotlight
Thu Dec 06 01:50 PM -- 01:55 PM (PST) @ Room 220 E
Towards Understanding Learning Representations: To What Extent Do Different Neural Networks Learn the Same Representation
In Thu Track 2 -- Session 2
Liwei Wang · Lunjia Hu · Jiayuan Gu · Zhiqiang Hu · Yue Wu · Kun He · John Hopcroft
Spotlight
Thu Dec 06 01:50 PM -- 01:55 PM (PST) @ Room 517 CD
Robust Hypothesis Testing Using Wasserstein Uncertainty Sets
In Thu Track 3 -- Session 2
Rui Gao · Liyan Xie · Yao Xie · Huan Xu
Spotlight
Thu Dec 06 01:55 PM -- 02:00 PM (PST) @ Room 220 CD
Support Recovery for Orthogonal Matching Pursuit: Upper and Lower bounds
In Thu Track 1 -- Session 2
Raghav Somani · Chirag Gupta · Prateek Jain · Praneeth Netrapalli
Spotlight
Thu Dec 06 01:55 PM -- 02:00 PM (PST) @ Room 220 E
Generalized Cross Entropy Loss for Training Deep Neural Networks with Noisy Labels
In Thu Track 2 -- Session 2
Zhilu Zhang · Mert Sabuncu
Spotlight
Thu Dec 06 01:55 PM -- 02:00 PM (PST) @ Room 517 CD
Convergence of Cubic Regularization for Nonconvex Optimization under KL Property
In Thu Track 3 -- Session 2
Yi Zhou · Zhe Wang · Yingbin Liang
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 210 #1
Streamlining Variational Inference for Constraint Satisfaction Problems
In Thu Poster Session B
Aditya Grover · Tudor Achim · Stefano Ermon
[ Paper] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 210 #2
Robust Hypothesis Testing Using Wasserstein Uncertainty Sets
In Thu Poster Session B
Rui Gao · Liyan Xie · Yao Xie · Huan Xu
[ Paper]  [ Poster] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 210 #3
Smoothed analysis of the low-rank approach for smooth semidefinite programs
In Thu Poster Session B
Thomas Pumir · Samy Jelassi · Nicolas Boumal
[ Paper] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 210 #4
Convergence of Cubic Regularization for Nonconvex Optimization under KL Property
In Thu Poster Session B
Yi Zhou · Zhe Wang · Yingbin Liang
[ Paper] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 210 #5
A Simple Proximal Stochastic Gradient Method for Nonsmooth Nonconvex Optimization
In Thu Poster Session B
Zhize Li · Jian Li
[ Paper] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 210 #6
Stochastic Chebyshev Gradient Descent for Spectral Optimization
In Thu Poster Session B
Insu Han · Haim Avron · Jinwoo Shin
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 210 #7
Proximal SCOPE for Distributed Sparse Learning
In Thu Poster Session B
Shenyi Zhao · Gong-Duo Zhang · Ming-Wei Li · Wu-Jun Li
[ Paper] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 210 #8
LAG: Lazily Aggregated Gradient for Communication-Efficient Distributed Learning
In Thu Poster Session B
Tianyi Chen · Georgios Giannakis · Tao Sun · Wotao Yin
[ Paper] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 210 #9
Direct Runge-Kutta Discretization Achieves Acceleration
In Thu Poster Session B
Jingzhao Zhang · Aryan Mokhtari · Suvrit Sra · Ali Jadbabaie
[ Paper]  [ Poster] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 210 #10
Optimal Algorithms for Non-Smooth Distributed Optimization in Networks
In Thu Poster Session B
Kevin Scaman · Francis Bach · Sebastien Bubeck · Laurent Massoulié · Yin Tat Lee
[ Paper]  [ Poster] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 210 #11
Graph Oracle Models, Lower Bounds, and Gaps for Parallel Stochastic Optimization
In Thu Poster Session B
Blake Woodworth · Jialei Wang · Adam Smith · Brendan McMahan · Nati Srebro
[ Paper] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 210 #12
(Probably) Concave Graph Matching
In Thu Poster Session B
Haggai Maron · Yaron Lipman
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 210 #13
Solving Non-smooth Constrained Programs with Lower Complexity than $\mathcal{O}(1/\varepsilon)$: A Primal-Dual Homotopy Smoothing Approach
In Thu Poster Session B
Xiaohan Wei · Hao Yu · Qing Ling · Michael Neely
[ Paper] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 210 #14
Wasserstein Distributionally Robust Kalman Filtering
In Thu Poster Session B
Soroosh Shafieezadeh Abadeh · Viet Anh Nguyen · Daniel Kuhn · Peyman Mohajerin Esfahani
[ Paper]  [ Poster] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 210 #15
Decentralize and Randomize: Faster Algorithm for Wasserstein Barycenters
In Thu Poster Session B
Pavel Dvurechenskii · Darina Dvinskikh · Alexander Gasnikov · Cesar Uribe · Angelia Nedich
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 210 #16
Limited Memory Kelley's Method Converges for Composite Convex and Submodular Objectives
In Thu Poster Session B
Song Zhou · Swati Gupta · Madeleine Udell
[ Paper] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 210 #17
Stochastic Spectral and Conjugate Descent Methods
In Thu Poster Session B
Dmitry Kovalev · Peter Richtarik · Eduard Gorbunov · Elnur Gasanov
[ Paper]  [ Poster] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 210 #18
Third-order Smoothness Helps: Faster Stochastic Optimization Algorithms for Finding Local Minima
In Thu Poster Session B
Yaodong Yu · Pan Xu · Quanquan Gu
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 210 #19
First-order Stochastic Algorithms for Escaping From Saddle Points in Almost Linear Time
In Thu Poster Session B
Yi Xu · Rong Jin · Tianbao Yang
[ Paper]  [ Poster] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 210 #20
Gen-Oja: Simple & Efficient Algorithm for Streaming Generalized Eigenvector Computation
In Thu Poster Session B
Kush Bhatia · Aldo Pacchiano · Nicolas Flammarion · Peter Bartlett · Michael Jordan
[ Paper] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 210 #21
Sparse DNNs with Improved Adversarial Robustness
In Thu Poster Session B
Yiwen Guo · Chao Zhang · Changshui Zhang · Yurong Chen
[ Paper] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 210 #22
Constructing Fast Network through Deconstruction of Convolution
In Thu Poster Session B
Yunho Jeon · Junmo Kim
[ Paper] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 210 #23
Learning Loop Invariants for Program Verification
In Thu Poster Session B
Xujie Si · Hanjun Dai · Mukund Raghothaman · Mayur Naik · Le Song
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 210 #24
Learning Libraries of Subroutines for Neurally–Guided Bayesian Program Induction
In Thu Poster Session B
Kevin Ellis · Lucas Morales · Mathias Sablé-Meyer · Armando Solar-Lezama · Josh Tenenbaum
[ Paper] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 210 #25
Learning to Infer Graphics Programs from Hand-Drawn Images
In Thu Poster Session B
Kevin Ellis · Daniel Ritchie · Armando Solar-Lezama · Josh Tenenbaum
[ Paper] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 210 #26
Towards Understanding Learning Representations: To What Extent Do Different Neural Networks Learn the Same Representation
In Thu Poster Session B
Liwei Wang · Lunjia Hu · Jiayuan Gu · Zhiqiang Hu · Yue Wu · Kun He · John Hopcroft
[ Paper] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 210 #27
Norm matters: efficient and accurate normalization schemes in deep networks
In Thu Poster Session B
Elad Hoffer · Ron Banner · Itay Golan · Daniel Soudry
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 210 #28
ResNet with one-neuron hidden layers is a Universal Approximator
In Thu Poster Session B
Hongzhou Lin · Stefanie Jegelka
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 210 #29
Hyperbolic Neural Networks
In Thu Poster Session B
Octavian Ganea · Gary Becigneul · Thomas Hofmann
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 210 #30
A Simple Unified Framework for Detecting Out-of-Distribution Samples and Adversarial Attacks
In Thu Poster Session B
Kimin Lee · Kibok Lee · Honglak Lee · Jinwoo Shin
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 210 #31
Improving Neural Program Synthesis with Inferred Execution Traces
In Thu Poster Session B
Richard Shin · Illia Polosukhin · Dawn Song
[ Paper] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 210 #32
Scaling the Poisson GLM to massive neural datasets through polynomial approximations
In Thu Poster Session B
David Zoltowski · Jonathan Pillow
[ Paper] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 210 #33
Discovery of Latent 3D Keypoints via End-to-end Geometric Reasoning
In Thu Poster Session B
Supasorn Suwajanakorn · Noah Snavely · Jonathan Tompson · Mohammad Norouzi
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 210 #34
Learning to Reconstruct Shapes from Unseen Classes
In Thu Poster Session B
Xiuming Zhang · Zhoutong Zhang · Chengkai Zhang · Josh Tenenbaum · Bill Freeman · Jiajun Wu
[ Paper] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 210 #35
Using Trusted Data to Train Deep Networks on Labels Corrupted by Severe Noise
In Thu Poster Session B
Dan Hendrycks · Mantas Mazeika · Duncan Wilson · Kevin Gimpel
[ Paper] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 210 #37
A Reduction for Efficient LDA Topic Reconstruction
In Thu Poster Session B
Matteo Almanza · Flavio Chierichetti · Alessandro Panconesi · Andrea Vattani
[ Paper] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 210 #38
A Unified View of Piecewise Linear Neural Network Verification
In Thu Poster Session B
Rudy Bunel · Ilker Turkaslan · Philip Torr · Pushmeet Kohli · Pawan K Mudigonda
[ Paper]  [ Poster] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 210 #39
Optimization over Continuous and Multi-dimensional Decisions with Observational Data
In Thu Poster Session B
Dimitris Bertsimas · Christopher McCord
[ Paper] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 210 #40
The Convergence of Sparsified Gradient Methods
In Thu Poster Session B
Dan Alistarh · Torsten Hoefler · Mikael Johansson · Nikola Konstantinov · Sarit Khirirat · Cedric Renggli
[ Paper] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 210 #41
Estimating Learnability in the Sublinear Data Regime
In Thu Poster Session B
Weihao Kong · Gregory Valiant
[ Paper] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 210 #42
Learning convex polytopes with margin
In Thu Poster Session B
Lee-Ad Gottlieb · Eran Kaufman · Aryeh Kontorovich · Gabriel Nivasch
[ Paper] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 210 #43
Ridge Regression and Provable Deterministic Ridge Leverage Score Sampling
In Thu Poster Session B
Shannon McCurdy
[ Paper] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 210 #44
GIANT: Globally Improved Approximate Newton Method for Distributed Optimization
In Thu Poster Session B
Shusen Wang · Fred Roosta · Peng Xu · Michael Mahoney
[ Paper] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 210 #45
Wavelet regression and additive models for irregularly spaced data
In Thu Poster Session B
Asad Haris · Ali Shojaie · Noah Simon
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 210 #46
New Insight into Hybrid Stochastic Gradient Descent: Beyond With-Replacement Sampling and Convexity
In Thu Poster Session B
Pan Zhou · Xiaotong Yuan · Jiashi Feng
[ Paper] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 210 #47
Sample Efficient Stochastic Gradient Iterative Hard Thresholding Method for Stochastic Sparse Linear Regression with Limited Attribute Observation
In Thu Poster Session B
Tomoya Murata · Taiji Suzuki
[ Paper] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 210 #48
Robust Subspace Approximation in a Stream
In Thu Poster Session B
Roie Levin · Anish Prasad Sevekari · David Woodruff
[ Paper] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 210 #50
A Practical Algorithm for Distributed Clustering and Outlier Detection
In Thu Poster Session B
Jiecao Chen · Erfan Sadeqi Azer · Qin Zhang
[ Paper] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 210 #51
Compact Representation of Uncertainty in Clustering
In Thu Poster Session B
Craig Greenberg · Nicholas Monath · Ari Kobren · Patrick Flaherty · Andrew McGregor · Andrew McCallum
[ Paper] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 210 #52
Bipartite Stochastic Block Models with Tiny Clusters
In Thu Poster Session B
Stefan Neumann
[ Paper] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 210 #53
Clustering Redemption–Beyond the Impossibility of Kleinberg’s Axioms
In Thu Poster Session B
Vincent Cohen-Addad · Varun Kanade · Frederik Mallmann-Trenn
[ Paper] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 210 #54
Understanding Regularized Spectral Clustering via Graph Conductance
In Thu Poster Session B
Yilin Zhang · Karl Rohe
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 210 #55
Query K-means Clustering and the Double Dixie Cup Problem
In Thu Poster Session B
Eli Chien · Chao Pan · Olgica Milenkovic
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 210 #56
How to tell when a clustering is (approximately) correct using convex relaxations
In Thu Poster Session B
Marina Meila
[ Paper] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 210 #57
Derivative Estimation in Random Design
In Thu Poster Session B
Yu Liu · Kris De Brabanter
[ Paper]  [ Poster] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 210 #58
Exploiting Numerical Sparsity for Efficient Learning : Faster Eigenvector Computation and Regression
In Thu Poster Session B
Neha Gupta · Aaron Sidford
[ Paper] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 210 #59
Boosted Sparse and Low-Rank Tensor Regression
In Thu Poster Session B
Jun Yu · Kun Chen · Wanwan Xu · Jiayu Zhou · Fei Wang
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 210 #60
An Efficient Pruning Algorithm for Robust Isotonic Regression
In Thu Poster Session B
Cong Han Lim
[ Paper] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 210 #61
A convex program for bilinear inversion of sparse vectors
In Thu Poster Session B
Alireza Aghasi · Ali Ahmed · Paul Hand · Babhru Joshi
[ Paper] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 210 #62
Efficient Convex Completion of Coupled Tensors using Coupled Nuclear Norms
In Thu Poster Session B
Kishan Wimalawarne · Hiroshi Mamitsuka
[ Paper] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 210 #63
Support Recovery for Orthogonal Matching Pursuit: Upper and Lower bounds
In Thu Poster Session B
Raghav Somani · Chirag Gupta · Prateek Jain · Praneeth Netrapalli
[ Paper]  [ Poster] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 210 #64
Learning without the Phase: Regularized PhaseMax Achieves Optimal Sample Complexity
In Thu Poster Session B
Fariborz Salehi · Ehsan Abbasi · Babak Hassibi
[ Paper] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 210 #65
On Controllable Sparse Alternatives to Softmax
In Thu Poster Session B
Anirban Laha · Saneem Ahmed Chemmengath · Priyanka Agrawal · Mitesh Khapra · Karthik Sankaranarayanan · Harish Ramaswamy
[ Paper] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 210 #66
Sparse PCA from Sparse Linear Regression
In Thu Poster Session B
Guy Bresler · Sung Min Park · Madalina Persu
[ Paper] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 210 #67
Efficient Anomaly Detection via Matrix Sketching
In Thu Poster Session B
Vatsal Sharan · Parikshit Gopalan · Udi Wieder
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 210 #69
Dimensionality Reduction for Stationary Time Series via Stochastic Nonconvex Optimization
In Thu Poster Session B
Minshuo Chen · Lin Yang · Mengdi Wang · Tuo Zhao
[ Paper]  [ Poster] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 210 #70
Contrastive Learning from Pairwise Measurements
In Thu Poster Session B
Yi Chen · Zhuoran Yang · Yuchen Xie · Zhaoran Wang
[ Paper] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 210 #71
Deep Functional Dictionaries: Learning Consistent Semantic Structures on 3D Models from Functions
In Thu Poster Session B
Minhyuk Sung · Hao Su · Ronald Yu · Leonidas Guibas
[ Paper]  [ Poster] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 210 #72
Large Scale computation of Means and Clusters for Persistence Diagrams using Optimal Transport
In Thu Poster Session B
Theo Lacombe · Marco Cuturi · Steve OUDOT
[ Paper]  [ Poster] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 210 #73
Representation Learning of Compositional Data
In Thu Poster Session B
Marta Avalos · Richard Nock · Cheng Soon Ong · Julien Rouar · Ke Sun
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 210 #74
How To Make the Gradients Small Stochastically: Even Faster Convex and Nonconvex SGD
In Thu Poster Session B
Zeyuan Allen-Zhu
[ Paper] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 210 #75
Statistical Optimality of Stochastic Gradient Descent on Hard Learning Problems through Multiple Passes
In Thu Poster Session B
Loucas Pillaud-Vivien · Alessandro Rudi · Francis Bach
[ Paper]  [ Poster] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 210 #76
Optimal Subsampling with Influence Functions
In Thu Poster Session B
Daniel Ting · Eric Brochu
[ Paper] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 210 #77
Metric on Nonlinear Dynamical Systems with Perron-Frobenius Operators
In Thu Poster Session B
Isao Ishikawa · Keisuke Fujii · Masahiro Ikeda · Yuka Hashimoto · Yoshinobu Kawahara
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 210 #78
Random Feature Stein Discrepancies
In Thu Poster Session B
Jonathan Huggins · Lester Mackey
[ Paper] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 210 #79
Informative Features for Model Comparison
In Thu Poster Session B
Wittawat Jitkrittum · Heishiro Kanagawa · Patsorn Sangkloy · James Hays · Bernhard Schölkopf · Arthur Gretton
[ Paper]  [ Poster] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 210 #80
On Fast Leverage Score Sampling and Optimal Learning
In Thu Poster Session B
Alessandro Rudi · Daniele Calandriello · Luigi Carratino · Lorenzo Rosasco
[ Paper] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 210 #81
Persistence Fisher Kernel: A Riemannian Manifold Kernel for Persistence Diagrams
In Thu Poster Session B
Tam Le · Makoto Yamada
[ Paper]  [ Poster] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 210 #82
Learning Bounds for Greedy Approximation with Explicit Feature Maps from Multiple Kernels
In Thu Poster Session B
Shahin Shahrampour · Vahid Tarokh
[ Paper] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 210 #83
RetGK: Graph Kernels based on Return Probabilities of Random Walks
In Thu Poster Session B
Zhen Zhang · Mianzhi Wang · Yijian Xiang · Yan Huang · Arye Nehorai
[ Paper]  [ Poster] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 210 #84
Nonparametric Density Estimation under Adversarial Losses
In Thu Poster Session B
Shashank Singh · Ananya Uppal · Boyue Li · Chun-Liang Li · Manzil Zaheer · Barnabas Poczos
[ Paper] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 210 #85
Deep Homogeneous Mixture Models: Representation, Separation, and Approximation
In Thu Poster Session B
Priyank Jaini · Pascal Poupart · Yaoliang Yu
[ Paper] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 210 #86
Gaussian Process Conditional Density Estimation
In Thu Poster Session B
Vincent Dutordoir · Hugh Salimbeni · James Hensman · Marc Deisenroth
[ Paper] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 210 #87
Low-rank Interaction with Sparse Additive Effects Model for Large Data Frames
In Thu Poster Session B
Geneviève Robin · Hoi-To Wai · Julie Josse · Olga Klopp · Eric Moulines
[ Paper]  [ Poster] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 210 #88
Mixture Matrix Completion
In Thu Poster Session B
Daniel Pimentel-Alarcon
[ Paper] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 210 #89
Multivariate Time Series Imputation with Generative Adversarial Networks
In Thu Poster Session B
Yonghong Luo · Xiangrui Cai · Ying ZHANG · Jun Xu · Yuan xiaojie
[ Paper] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 210 #90
Fully Understanding The Hashing Trick
In Thu Poster Session B
Lior Kamma · Casper B. Freksen · Kasper Green Larsen
[ Paper]  [ Poster] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 210 #91
Learning semantic similarity in a continuous space
In Thu Poster Session B
Michel Deudon
[ Paper] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 210 #92
Bilevel learning of the Group Lasso structure
In Thu Poster Session B
Jordan Frecon · Saverio Salzo · Massimiliano Pontil
[ Paper] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 210 #93
Bayesian Structure Learning by Recursive Bootstrap
In Thu Poster Session B
Raanan Y. Rohekar · Yaniv Gurwicz · Shami Nisimov · Guy Koren · Gal Novik
[ Paper] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 210 #94
Learning from Group Comparisons: Exploiting Higher Order Interactions
In Thu Poster Session B
Yao Li · Minhao Cheng · Kevin Fujii · Fushing Hsieh · Cho-Jui Hsieh
[ Paper] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 210 #95
A Structured Prediction Approach for Label Ranking
In Thu Poster Session B
Anna Korba · Alexandre Garcia · Florence d'Alché-Buc
[ Paper] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 210 #96
The Sample Complexity of Semi-Supervised Learning with Nonparametric Mixture Models
In Thu Poster Session B
Chen Dan · Liu Leqi · Bryon Aragam · Pradeep Ravikumar · Eric Xing
[ Paper] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 210 #97
Binary Classification from Positive-Confidence Data
In Thu Poster Session B
Takashi Ishida · Gang Niu · Masashi Sugiyama
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 210 #98
Learning SMaLL Predictors
In Thu Poster Session B
Vikas Garg · Ofer Dekel · Lin Xiao
[ Paper] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 210 #99
Contour location via entropy reduction leveraging multiple information sources
In Thu Poster Session B
Alexandre Marques · Remi Lam · Karen Willcox
[ Paper] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 210 #100
Multi-Class Learning: From Theory to Algorithm
In Thu Poster Session B
Jian Li · Yong Liu · Rong Yin · Hua Zhang · Lizhong Ding · Weiping Wang
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 517 AB #101
Generalized Cross Entropy Loss for Training Deep Neural Networks with Noisy Labels
In Thu Poster Session B
Zhilu Zhang · Mert Sabuncu
[ Paper] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 517 AB #102
A Smoother Way to Train Structured Prediction Models
In Thu Poster Session B
Krishna Pillutla · Vincent Roulet · Sham Kakade · Zaid Harchaoui
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 517 AB #103
Constrained Graph Variational Autoencoders for Molecule Design
In Thu Poster Session B
Qi Liu · Miltiadis Allamanis · Marc Brockschmidt · Alexander Gaunt
[ Paper] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 517 AB #104
Learning Beam Search Policies via Imitation Learning
In Thu Poster Session B
Renato Negrinho · Matthew Gormley · Geoffrey Gordon
[ Paper] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 517 AB #105
Loss Functions for Multiset Prediction
In Thu Poster Session B
Sean Welleck · Zixin Yao · Yu Gai · Jialin Mao · Zheng Zhang · Kyunghyun Cho
[ Paper] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 517 AB #106
Learning Confidence Sets using Support Vector Machines
In Thu Poster Session B
Wenbo Wang · Xingye Qiao
[ Paper]  [ Poster] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 517 AB #107
Fast Similarity Search via Optimal Sparse Lifting
In Thu Poster Session B
Wenye Li · Jingwei Mao · Yin Zhang · Shuguang Cui
[ Paper]  [ Poster] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 517 AB #108
The Sparse Manifold Transform
In Thu Poster Session B
Yubei Chen · Dylan Paiton · Bruno Olshausen
[ Paper] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 517 AB #109
When do random forests fail?
In Thu Poster Session B
Cheng Tang · Damien Garreau · Ulrike von Luxburg
[ Paper] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 517 AB #110
Diverse Ensemble Evolution: Curriculum Data-Model Marriage
In Thu Poster Session B
Tianyi Zhou · Shengjie Wang · Jeffrey A Bilmes
[ Paper]  [ Poster] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 517 AB #111
The Pessimistic Limits and Possibilities of Margin-based Losses in Semi-supervised Learning
In Thu Poster Session B
Jesse Krijthe · Marco Loog
[ Paper]  [ Poster] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 517 AB #112
Semi-Supervised Learning with Declaratively Specified Entropy Constraints
In Thu Poster Session B
Haitian Sun · William Cohen · Lidong Bing
[ Paper]  [ Poster] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 517 AB #113
Learning to Multitask
In Thu Poster Session B
Yu Zhang · Ying Wei · Qiang Yang
[ Paper] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 517 AB #114
CatBoost: unbiased boosting with categorical features
In Thu Poster Session B
Liudmila Prokhorenkova · Gleb Gusev · Aleksandr Vorobev · Anna Veronika Dorogush · Andrey Gulin
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 517 AB #115
Supervised autoencoders: Improving generalization performance with unsupervised regularizers
In Thu Poster Session B
Lei Le · Andrew Patterson · Martha White
[ Paper] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 517 AB #116
Representation Learning for Treatment Effect Estimation from Observational Data
In Thu Poster Session B
Liuyi Yao · Sheng Li · Yaliang Li · Mengdi Huai · Jing Gao · Aidong Zhang
[ Paper]  [ Poster] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 517 AB #117
SimplE Embedding for Link Prediction in Knowledge Graphs
In Thu Poster Session B
Seyed Mehran Kazemi · David Poole
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 517 AB #118
DeepProbLog: Neural Probabilistic Logic Programming
In Thu Poster Session B
Robin Manhaeve · Sebastijan Dumancic · Angelika Kimmig · Thomas Demeester · Luc De Raedt
[ Paper]  [ Poster] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 517 AB #119
Watch Your Step: Learning Node Embeddings via Graph Attention
In Thu Poster Session B
Sami Abu-El-Haija · Bryan Perozzi · Rami Al-Rfou · Alexander Alemi
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 517 AB #120
Invariant Representations without Adversarial Training
In Thu Poster Session B
Daniel Moyer · Shuyang Gao · Rob Brekelmans · Aram Galstyan · Greg Ver Steeg
[ Paper] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 517 AB #121
Domain-Invariant Projection Learning for Zero-Shot Recognition
In Thu Poster Session B
An Zhao · Mingyu Ding · Jiechao Guan · Zhiwu Lu · Tao Xiang · Ji-Rong Wen
[ Paper] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 517 AB #122
Unsupervised Learning of View-invariant Action Representations
In Thu Poster Session B
Junnan Li · Yongkang Wong · Qi Zhao · Mohan Kankanhalli
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 517 AB #123
Neural Architecture Optimization
In Thu Poster Session B
Renqian Luo · Fei Tian · Tao Qin · Enhong Chen · Tie-Yan Liu
[ Paper] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 517 AB #124
Scalable Hyperparameter Transfer Learning
In Thu Poster Session B
Valerio Perrone · Rodolphe Jenatton · Matthias W Seeger · Cedric Archambeau
[ Paper] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 517 AB #125
Learning To Learn Around A Common Mean
In Thu Poster Session B
Giulia Denevi · Carlo Ciliberto · Dimitris Stamos · Massimiliano Pontil
[ Paper]  [ Poster] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 517 AB #126
Hybrid-MST: A Hybrid Active Sampling Strategy for Pairwise Preference Aggregation
In Thu Poster Session B
JING LI · Rafal Mantiuk · Junle Wang · Suiyi Ling · Patrick Le Callet
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 517 AB #127
Algorithmic Assurance: An Active Approach to Algorithmic Testing using Bayesian Optimisation
In Thu Poster Session B
Shivapratap Gopakumar · Sunil Gupta · Santu Rana · Vu Nguyen · Svetha Venkatesh
[ Paper] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 517 AB #128
Understanding the Role of Adaptivity in Machine Teaching: The Case of Version Space Learners
In Thu Poster Session B
Yuxin Chen · Adish Singla · Oisin Mac Aodha · Pietro Perona · Yisong Yue
[ Paper] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 517 AB #129
Active Learning for Non-Parametric Regression Using Purely Random Trees
In Thu Poster Session B
Jack Goetz · Ambuj Tewari · Paul Zimmerman
[ Paper] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 517 AB #130
Interactive Structure Learning with Structural Query-by-Committee
In Thu Poster Session B
Christopher Tosh · Sanjoy Dasgupta
[ Paper] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 517 AB #131
Efficient nonmyopic batch active search
In Thu Poster Session B
Shali Jiang · Gustavo Malkomes · Matthew Abbott · Benjamin Moseley · Roman Garnett
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 517 AB #132
Uncertainty Sampling is Preconditioned Stochastic Gradient Descent on Zero-One Loss
In Thu Poster Session B
Stephen Mussmann · Percy Liang
[ Paper] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 517 AB #133
Online Adaptive Methods, Universality and Acceleration
In Thu Poster Session B
Kfir Y. Levy · Alp Yurtsever · Volkan Cevher
[ Paper] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 517 AB #134
Online Improper Learning with an Approximation Oracle
In Thu Poster Session B
Elad Hazan · Wei Hu · Yuanzhi Li · Zhiyuan Li
[ Paper] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 517 AB #135
Online Structured Laplace Approximations for Overcoming Catastrophic Forgetting
In Thu Poster Session B
Hippolyt Ritter · Aleksandar Botev · David Barber
[ Paper] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 517 AB #136
Approximating Real-Time Recurrent Learning with Random Kronecker Factors
In Thu Poster Session B
Asier Mujika · Florian Meier · Angelika Steger
[ Paper] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 517 AB #137
Online Reciprocal Recommendation with Theoretical Performance Guarantees
In Thu Poster Session B
Claudio Gentile · Nikos Parotsidis · Fabio Vitale
[ Paper] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 517 AB #138
Generalized Inverse Optimization through Online Learning
In Thu Poster Session B
Chaosheng Dong · Yiran Chen · Bo Zeng
[ Paper]  [ Poster] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 517 AB #139
Adaptive Online Learning in Dynamic Environments
In Thu Poster Session B
Lijun Zhang · Shiyin Lu · Zhi-Hua Zhou
[ Paper] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 517 AB #140
Online convex optimization for cumulative constraints
In Thu Poster Session B
Jianjun Yuan · Andrew Lamperski
[ Paper]  [ Poster] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 517 AB #141
Efficient online algorithms for fast-rate regret bounds under sparsity
In Thu Poster Session B
Pierre Gaillard · Olivier Wintenberger
[ Paper] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 517 AB #142
Regret Bounds for Online Portfolio Selection with a Cardinality Constraint
In Thu Poster Session B
Shinji Ito · Daisuke Hatano · Hanna Sumita · Akihiro Yabe · Takuro Fukunaga · Naonori Kakimura · Ken-Ichi Kawarabayashi
[ Paper] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 517 AB #144
Policy Regret in Repeated Games
In Thu Poster Session B
Raman Arora · Michael Dinitz · Teodor Vanislavov Marinov · Mehryar Mohri
[ Paper]  [ Poster] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 517 AB #145
Query Complexity of Bayesian Private Learning
In Thu Poster Session B
Kuang Xu
[ Paper]  [ Poster] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 517 AB #146
The Limits of Post-Selection Generalization
In Thu Poster Session B
Jonathan Ullman · Adam Smith · Kobbi Nissim · Uri Stemmer · Thomas Steinke
[ Paper] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 517 AB #147
Sequential Test for the Lowest Mean: From Thompson to Murphy Sampling
In Thu Poster Session B
Emilie Kaufmann · Wouter Koolen · Aurélien Garivier
[ Paper]  [ Poster] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 517 AB #148
Contextual Combinatorial Multi-armed Bandits with Volatile Arms and Submodular Reward
In Thu Poster Session B
Lixing Chen · Jie Xu · Zhuo Lu
[ Paper]  [ Poster] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 517 AB #149
TopRank: A practical algorithm for online stochastic ranking
In Thu Poster Session B
Tor Lattimore · Branislav Kveton · Shuai Li · Csaba Szepesvari
[ Paper] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 517 AB #150
A Bandit Approach to Sequential Experimental Design with False Discovery Control
In Thu Poster Session B
Kevin Jamieson · Lalit Jain
[ Paper] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 517 AB #151
Adaptation to Easy Data in Prediction with Limited Advice
In Thu Poster Session B
Tobias Sommer Thune · Yevgeny Seldin
[ Paper] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 517 AB #152
Differentially Private Contextual Linear Bandits
In Thu Poster Session B
Roshan Shariff · Or Sheffet
[ Paper] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 517 AB #153
Community Exploration: From Offline Optimization to Online Learning
In Thu Poster Session B
Xiaowei Chen · Weiran Huang · Wei Chen · John C. S. Lui
[ Paper]  [ Poster] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 517 AB #154
Adaptive Learning with Unknown Information Flows
In Thu Poster Session B
Yonatan Gur · Ahmadreza Momeni
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 517 AB #155
Multi-armed Bandits with Compensation
In Thu Poster Session B
Siwei Wang · Longbo Huang
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 517 AB #156
Bandit Learning with Implicit Feedback
In Thu Poster Session B
Yi Qi · Qingyun Wu · Hongning Wang · Jie Tang · Maosong Sun
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 517 AB #157
Optimistic optimization of a Brownian
In Thu Poster Session B
Jean-Bastien Grill · Michal Valko · Remi Munos
[ Paper]  [ Poster] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 517 AB #158
Bandit Learning with Positive Externalities
In Thu Poster Session B
Virag Shah · Jose Blanchet · Ramesh Johari
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 517 AB #159
An Information-Theoretic Analysis for Thompson Sampling with Many Actions
In Thu Poster Session B
Shi Dong · Benjamin Van Roy
[ Paper] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 517 AB #160
Distributed Multi-Player Bandits - a Game of Thrones Approach
In Thu Poster Session B
Ilai Bistritz · Amir Leshem
[ Paper] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 517 AB #161
PG-TS: Improved Thompson Sampling for Logistic Contextual Bandits
In Thu Poster Session B
Bianca Dumitrascu · Karen Feng · Barbara Engelhardt
[ Paper] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 517 AB #162
Non-delusional Q-learning and value-iteration
In Thu Poster Session B
Tyler Lu · Dale Schuurmans · Craig Boutilier
[ Paper] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 517 AB #163
Differentiable MPC for End-to-end Planning and Control
In Thu Poster Session B
Brandon Amos · Ivan Jimenez · Jacob I Sacks · Byron Boots · J. Zico Kolter
[ Paper]  [ Poster] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 517 AB #164
Multiple-Step Greedy Policies in Approximate and Online Reinforcement Learning
In Thu Poster Session B
Yonathan Efroni · Gal Dalal · Bruno Scherrer · Shie Mannor
[ Paper]  [ Poster] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 517 AB #165
Deep Reinforcement Learning in a Handful of Trials using Probabilistic Dynamics Models
In Thu Poster Session B
Kurtland Chua · Roberto Calandra · Rowan McAllister · Sergey Levine
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 517 AB #166
Learning convex bounds for linear quadratic control policy synthesis
In Thu Poster Session B
Jack Umenberger · Thomas Schön
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 517 AB #167
Sample-Efficient Reinforcement Learning with Stochastic Ensemble Value Expansion
In Thu Poster Session B
Jacob Buckman · Danijar Hafner · George Tucker · Eugene Brevdo · Honglak Lee
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 517 AB #168
Policy-Conditioned Uncertainty Sets for Robust Markov Decision Processes
In Thu Poster Session B
Andrea Tirinzoni · Marek Petrik · Xiangli Chen · Brian Ziebart
[ Paper] 
Poster
Thu Dec 06 02:00 PM -- 04:00 PM (PST) @ Room 517 AB
Why so gloomy? A Bayesian explanation of human pessimism bias in the multi-armed bandit task
In Thu Poster Session B
Dalin Guo · Angela Yu
[ Paper] 
Break
Thu Dec 06 03:05 PM -- 03:30 PM (PST)
Coffee Break