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Invited Talk
Wed Jun 12 09:00 AM -- 10:00 AM (PDT) @ Hall A
The U.S. Census Bureau Tries to be a Good Data Steward in the 21st Century
John M. Abowd
[ Video] 
Invited Talk
Wed Jun 12 10:00 AM -- 10:20 AM (PDT) @ Hall A
Test of Time Award
[ Video] 
Invited Talk
Wed Jun 12 10:00 AM -- 10:20 AM (PDT) @ Hall A
Online Dictionary Learning for Sparse Coding
Julien Mairal · Francis Bach · Jean Ponce · Guillermo Sapiro
[ Slides]  [ Video] 
Break
Wed Jun 12 10:30 AM -- 11:00 AM (PDT)
Coffee Break
Oral
Wed Jun 12 11:00 AM -- 11:20 AM (PDT) @ Hall B
Social Influence as Intrinsic Motivation for Multi-Agent Deep Reinforcement Learning
In Deep RL
Natasha Jaques · Angeliki Lazaridou · Edward Hughes · Caglar Gulcehre · Pedro Ortega · DJ Strouse · Joel Z Leibo · Nando de Freitas
[ Video] 
Oral
Wed Jun 12 11:00 AM -- 11:20 AM (PDT) @ Grand Ballroom
Theoretically Principled Trade-off between Robustness and Accuracy
In Adversarial Examples
Hongyang Zhang · Yaodong Yu · Jiantao Jiao · Eric Xing · Laurent El Ghaoui · Michael Jordan
[ Video] 
Oral
Wed Jun 12 11:00 AM -- 11:20 AM (PDT) @ Hall A
Sum-of-Squares Polynomial Flow
In Deep Generative Models
Priyank Jaini · Kira A. Selby · Yaoliang Yu
[ Video] 
Oral
Wed Jun 12 11:00 AM -- 11:20 AM (PDT) @ Room 101
Distribution calibration for regression
In Gaussian Processes
Hao Song · Tom Diethe · Meelis Kull · Peter Flach
[ Video] 
Oral
Wed Jun 12 11:00 AM -- 11:20 AM (PDT) @ Room 103
Distributed Learning with Sublinear Communication
In Optimization
Jayadev Acharya · Christopher De Sa · Dylan Foster · Karthik Sridharan
[ Video] 
Oral
Wed Jun 12 11:00 AM -- 11:20 AM (PDT) @ Room 102
On the Convergence and Robustness of Adversarial Training
In Robust Statistics and Machine Learning
Yisen Wang · Xingjun Ma · James Bailey · Jinfeng Yi · Bowen Zhou · Quanquan Gu
[ Slides]  [ Video] 
Oral
Wed Jun 12 11:00 AM -- 11:20 AM (PDT) @ Room 104
Complexity of Linear Regions in Deep Networks
In Deep Learning Theory
Boris Hanin · David Rolnick
[ Video] 
Oral
Wed Jun 12 11:00 AM -- 11:20 AM (PDT) @ Room 201
Exploiting Worker Correlation for Label Aggregation in Crowdsourcing
In Applications
Yuan Li · Benjamin Rubinstein · Trevor Cohn
[ Video] 
Oral
Wed Jun 12 11:00 AM -- 11:20 AM (PDT) @ Seaside Ballroom
Optimal Algorithms for Lipschitz Bandits with Heavy-tailed Rewards
In Reinforcement Learning and Bandits
Shiyin Lu · Guanghui Wang · Yao Hu · Lijun Zhang
[ Video] 
Oral
Wed Jun 12 11:20 AM -- 11:25 AM (PDT) @ Grand Ballroom
The Odds are Odd: A Statistical Test for Detecting Adversarial Examples
In Adversarial Examples
Kevin Roth · Yannic Kilcher · Thomas Hofmann
[ Slides]  [ Video] 
Oral
Wed Jun 12 11:20 AM -- 11:25 AM (PDT) @ Seaside Ballroom
Target Tracking for Contextual Bandits: Application to Demand Side Management
In Reinforcement Learning and Bandits
Margaux Brégère · Pierre Gaillard · Yannig Goude · Gilles Stoltz
Oral
Wed Jun 12 11:20 AM -- 11:25 AM (PDT) @ Room 201
Efficient Amortised Bayesian Inference for Hierarchical and Nonlinear Dynamical Systems
In Applications
Ted Meeds · Geoffrey Roeder · Paul Grant · Andrew Phillips · Neil Dalchau
[ Slides]  [ Video] 
Oral
Wed Jun 12 11:20 AM -- 11:25 AM (PDT) @ Hall B
Maximum Entropy-Regularized Multi-Goal Reinforcement Learning
In Deep RL
Rui Zhao · Xudong Sun · Volker Tresp
[ Slides]  [ Video] 
Oral
Wed Jun 12 11:20 AM -- 11:25 AM (PDT) @ Room 103
On the Linear Speedup Analysis of Communication Efficient Momentum SGD for Distributed Non-Convex Optimization
In Optimization
Hao Yu · rong jin · Sen Yang
[ Slides]  [ Video] 
Oral
Wed Jun 12 11:20 AM -- 11:25 AM (PDT) @ Room 101
Graph Convolutional Gaussian Processes
In Gaussian Processes
Ian Walker · Ben Glocker
[ Slides]  [ Video] 
Oral
Wed Jun 12 11:20 AM -- 11:25 AM (PDT) @ Room 104
On Connected Sublevel Sets in Deep Learning
In Deep Learning Theory
Quynh Nguyen
[ Slides]  [ Video] 
Oral
Wed Jun 12 11:20 AM -- 11:25 AM (PDT) @ Room 102
Learning with Bad Training Data via Iterative Trimmed Loss Minimization
In Robust Statistics and Machine Learning
Yanyao Shen · Sujay Sanghavi
[ Slides]  [ Video] 
Oral
Wed Jun 12 11:20 AM -- 11:25 AM (PDT) @ Hall A
FloWaveNet : A Generative Flow for Raw Audio
In Deep Generative Models
Sungwon Kim · Sang-gil Lee · Jongyoon Song · Jaehyeon Kim · Sungroh Yoon
[ Slides]  [ Video] 
Oral
Wed Jun 12 11:25 AM -- 11:30 AM (PDT) @ Room 101
Asynchronous Batch Bayesian Optimisation with Improved Local Penalisation
In Gaussian Processes
Ahsan Alvi · Binxin Ru · Jan-Peter Calliess · Stephen Roberts · Michael A Osborne
[ Slides]  [ Video] 
Oral
Wed Jun 12 11:25 AM -- 11:30 AM (PDT) @ Room 102
On discriminative learning of prediction uncertainty
In Robust Statistics and Machine Learning
Vojtech Franc · Daniel Prusa
[ Slides] 
Oral
Wed Jun 12 11:25 AM -- 11:30 AM (PDT) @ Room 103
Stochastic Gradient Push for Distributed Deep Learning
In Optimization
Mahmoud Assran · Nicolas Loizou · Nicolas Ballas · Michael Rabbat
[ Slides] 
Oral
Wed Jun 12 11:25 AM -- 11:30 AM (PDT) @ Room 201
A Multitask Multiple Kernel Learning Algorithm for Survival Analysis with Application to Cancer Biology
In Applications
Onur Dereli · Ceyda Oğuz · Mehmet Gönen
[ Slides]  [ Video] 
Oral
Wed Jun 12 11:25 AM -- 11:30 AM (PDT) @ Room 104
Adversarial Examples Are a Natural Consequence of Test Error in Noise
In Deep Learning Theory
Justin Gilmer · Nicolas Ford · Nicholas Carlini · Ekin Dogus Cubuk
[ Slides]  [ Video] 
Oral
Wed Jun 12 11:25 AM -- 11:30 AM (PDT) @ Hall B
Imitating Latent Policies from Observation
In Deep RL
Ashley Edwards · Himanshu Sahni · Yannick Schroecker · Charles Isbell
[ Slides]  [ Video] 
Oral
Wed Jun 12 11:25 AM -- 11:30 AM (PDT) @ Grand Ballroom
ME-Net: Towards Effective Adversarial Robustness with Matrix Estimation
In Adversarial Examples
Yuzhe Yang · GUO ZHANG · Zhi Xu · Dina Katabi
[ Slides]  [ Video] 
Oral
Wed Jun 12 11:25 AM -- 11:30 AM (PDT) @ Hall A
Are Generative Classifiers More Robust to Adversarial Attacks?
In Deep Generative Models
Yingzhen Li · John Bradshaw · Yash Sharma
Oral
Wed Jun 12 11:25 AM -- 11:30 AM (PDT) @ Seaside Ballroom
Correlated bandits or: How to minimize mean-squared error online
In Reinforcement Learning and Bandits
Vinay Praneeth Boda · Prashanth L.A.
[ Slides]  [ Video] 
Oral
Wed Jun 12 11:30 AM -- 11:35 AM (PDT) @ Room 101
GOODE: A Gaussian Off-The-Shelf Ordinary Differential Equation Solver
In Gaussian Processes
David John · Vincent Heuveline · Michael Schober
[ Slides]  [ Video] 
Oral
Wed Jun 12 11:30 AM -- 11:35 AM (PDT) @ Hall B
SOLAR: Deep Structured Representations for Model-Based Reinforcement Learning
In Deep RL
Marvin Zhang · Sharad Vikram · Laura Smith · Pieter Abbeel · Matthew Johnson · Sergey Levine
[ Slides]  [ Video] 
Oral
Wed Jun 12 11:30 AM -- 11:35 AM (PDT) @ Room 104
Greedy Layerwise Learning Can Scale To ImageNet
In Deep Learning Theory
Eugene Belilovsky · Michael Eickenberg · Edouard Oyallon
[ Slides]  [ Video] 
Oral
Wed Jun 12 11:30 AM -- 11:35 AM (PDT) @ Room 103
Collective Model Fusion for Multiple Black-Box Experts
In Optimization
Minh Hoang · Nghia Hoang · Bryan Kian Hsiang Low · Carleton Kingsford
[ Slides]  [ Video] 
Oral
Wed Jun 12 11:30 AM -- 11:35 AM (PDT) @ Hall A
A Gradual, Semi-Discrete Approach to Generative Network Training via Explicit Wasserstein Minimization
In Deep Generative Models
Yucheng Chen · Matus Telgarsky · Chao Zhang · Bolton Bailey · Daniel Hsu · Jian Peng
[ Slides] 
Oral
Wed Jun 12 11:30 AM -- 11:35 AM (PDT) @ Grand Ballroom
Certified Adversarial Robustness via Randomized Smoothing
In Adversarial Examples
Jeremy Cohen · Elan Rosenfeld · Zico Kolter
[ Slides]  [ Video] 
Oral
Wed Jun 12 11:30 AM -- 11:35 AM (PDT) @ Room 102
Understanding and Utilizing Deep Neural Networks Trained with Noisy Labels
In Robust Statistics and Machine Learning
Pengfei Chen · Ben Liao · Guangyong Chen · Shengyu Zhang
[ Slides]  [ Video] 
Oral
Wed Jun 12 11:30 AM -- 11:35 AM (PDT) @ Seaside Ballroom
Stay With Me: Lifetime Maximization Through Heteroscedastic Linear Bandits With Reneging
In Reinforcement Learning and Bandits
Ping-Chun Hsieh · Xi Liu · Anirban Bhattacharya · P R Kumar
[ Slides]  [ Video] 
Oral
Wed Jun 12 11:30 AM -- 11:35 AM (PDT) @ Room 201
Fast and Flexible Inference of Joint Distributions from their Marginals
In Applications
Charles Frogner · Tomaso Poggio
[ Slides]  [ Video] 
Oral
Wed Jun 12 11:35 AM -- 11:40 AM (PDT) @ Seaside Ballroom
Garbage In, Reward Out: Bootstrapping Exploration in Multi-Armed Bandits
In Reinforcement Learning and Bandits
Branislav Kveton · Csaba Szepesvari · Sharan Vaswani · Zheng Wen · Tor Lattimore · Mohammad Ghavamzadeh
[ Slides]  [ Video] 
Oral
Wed Jun 12 11:35 AM -- 11:40 AM (PDT) @ Room 103
Trading Redundancy for Communication: Speeding up Distributed SGD for Non-convex Optimization
In Optimization
Farzin Haddadpour · Mohammad Mahdi Kamani · Mehrdad Mahdavi · Viveck Cadambe
[ Slides]  [ Video] 
Oral
Wed Jun 12 11:35 AM -- 11:40 AM (PDT) @ Room 104
On the Impact of the Activation function on Deep Neural Networks Training
In Deep Learning Theory
Soufiane Hayou · Arnaud Doucet · Judith Rousseau
[ Slides]  [ Video] 
Oral
Wed Jun 12 11:35 AM -- 11:40 AM (PDT) @ Room 102
Does Data Augmentation Lead to Positive Margin?
In Robust Statistics and Machine Learning
Shashank Rajput · Zhili Feng · Zachary Charles · Po-Ling Loh · Dimitris Papailiopoulos
[ Slides]  [ Video] 
Oral
Wed Jun 12 11:35 AM -- 11:40 AM (PDT) @ Room 101
Overcoming Mean-Field Approximations in Recurrent Gaussian Process Models
In Gaussian Processes
Alessandro Davide Ialongo · Mark van der Wilk · James Hensman · Carl E Rasmussen
[ Slides]  [ Video] 
Oral
Wed Jun 12 11:35 AM -- 11:40 AM (PDT) @ Grand Ballroom
Imperceptible, Robust, and Targeted Adversarial Examples for Automatic Speech Recognition
In Adversarial Examples
Yao Qin · Nicholas Carlini · Garrison Cottrell · Ian Goodfellow · Colin Raffel
[ Slides]  [ Video] 
Oral
Wed Jun 12 11:35 AM -- 11:40 AM (PDT) @ Hall A
Disentangling Disentanglement in Variational Autoencoders
In Deep Generative Models
Emile Mathieu · Tom Rainforth · N Siddharth · Yee-Whye Teh
[ Slides] 
Oral
Wed Jun 12 11:35 AM -- 11:40 AM (PDT) @ Room 201
Cognitive model priors for predicting human decisions
In Applications
Joshua C Peterson · David D Bourgin · Daniel Reichman · Thomas Griffiths · Stuart Russell
[ Slides]  [ Video] 
Oral
Wed Jun 12 11:35 AM -- 11:40 AM (PDT) @ Hall B
Dimension-Wise Importance Sampling Weight Clipping for Sample-Efficient Reinforcement Learning
In Deep RL
Seungyul Han · Youngchul Sung
[ Slides]  [ Video] 
Oral
Wed Jun 12 11:40 AM -- 12:00 PM (PDT) @ Room 104
Estimating Information Flow in Deep Neural Networks
In Deep Learning Theory
Ziv Goldfeld · Ewout van den Berg · Kristjan Greenewald · Igor Melnyk · Nam Nguyen · Brian Kingsbury · Yury Polyanskiy
[ Slides]  [ Video] 
Oral
Wed Jun 12 11:40 AM -- 12:00 PM (PDT) @ Grand Ballroom
Parsimonious Black-Box Adversarial Attacks via Efficient Combinatorial Optimization
In Adversarial Examples
Seungyong Moon · Gaon An · Hyun Oh Song
[ Video] 
Oral
Wed Jun 12 11:40 AM -- 12:00 PM (PDT) @ Hall A
EDDI: Efficient Dynamic Discovery of High-Value Information with Partial VAE
In Deep Generative Models
Chao Ma · Sebastian Tschiatschek · Konstantina Palla · Jose Miguel Hernandez-Lobato · Sebastian Nowozin · Cheng Zhang
Oral
Wed Jun 12 11:40 AM -- 12:00 PM (PDT) @ Room 201
Conditioning by adaptive sampling for robust design
In Applications
David Brookes · Jennifer Listgarten
[ Slides]  [ Video] 
Oral
Wed Jun 12 11:40 AM -- 12:00 PM (PDT) @ Seaside Ballroom
Beating Stochastic and Adversarial Semi-bandits Optimally and Simultaneously
In Reinforcement Learning and Bandits
Julian Zimmert · Haipeng Luo · Chen-Yu Wei
[ Slides]  [ Video] 
Oral
Wed Jun 12 11:40 AM -- 12:00 PM (PDT) @ Room 103
Trimming the $\ell_1$ Regularizer: Statistical Analysis, Optimization, and Applications to Deep Learning
In Optimization
Jihun Yun · Peng Zheng · Eunho Yang · Aurelie Lozano · Aleksandr Aravkin
[ Slides]  [ Video] 
Oral
Wed Jun 12 11:40 AM -- 12:00 PM (PDT) @ Room 101
AReS and MaRS - Adversarial and MMD-Minimizing Regression for SDEs
In Gaussian Processes
Gabriele Abbati · Philippe Wenk · Michael A Osborne · Andreas Krause · Bernhard Schölkopf · Stefan Bauer
[ Video] 
Oral
Wed Jun 12 11:40 AM -- 12:00 PM (PDT) @ Hall B
Structured agents for physical construction
In Deep RL
Victor Bapst · Alvaro Sanchez-Gonzalez · Carl Doersch · Kimberly Stachenfeld · Pushmeet Kohli · Peter Battaglia · Jessica Hamrick
[ Video] 
Oral
Wed Jun 12 11:40 AM -- 12:00 PM (PDT) @ Room 102
Robust Learning from Untrusted Sources
In Robust Statistics and Machine Learning
Nikola Konstantinov · Christoph H. Lampert
[ Slides]  [ Video] 
Oral
Wed Jun 12 12:00 PM -- 12:05 PM (PDT) @ Hall A
A Wrapped Normal Distribution on Hyperbolic Space for Gradient-Based Learning
In Deep Generative Models
Yoshihiro Nagano · Shoichiro Yamaguchi · Yasuhiro Fujita · Masanori Koyama
[ Slides] 
Oral
Wed Jun 12 12:00 PM -- 12:05 PM (PDT) @ Hall B
Learning Novel Policies For Tasks
In Deep RL
Yunbo Zhang · Wenhao Yu · Greg Turk
[ Slides]  [ Video] 
Oral
Wed Jun 12 12:00 PM -- 12:05 PM (PDT) @ Room 103
Compressed Factorization: Fast and Accurate Low-Rank Factorization of Compressively-Sensed Data
In Optimization
Vatsal Sharan · Kai Sheng Tai · Peter Bailis · Gregory Valiant
[ Slides]  [ Video] 
Oral
Wed Jun 12 12:00 PM -- 12:05 PM (PDT) @ Room 101
End-to-End Probabilistic Inference for Nonstationary Audio Analysis
In Gaussian Processes
William Wilkinson · Michael Riis Andersen · Joshua D. Reiss · Dan Stowell · Arno Solin
[ Slides]  [ Video] 
Oral
Wed Jun 12 12:00 PM -- 12:05 PM (PDT) @ Seaside Ballroom
Bilinear Bandits with Low-rank Structure
In Reinforcement Learning and Bandits
Kwang-Sung Jun · Rebecca Willett · Stephen Wright · Robert Nowak
[ Slides]  [ Video] 
Oral
Wed Jun 12 12:00 PM -- 12:05 PM (PDT) @ Room 201
Direct Uncertainty Prediction for Medical Second Opinions
In Applications
Maithra Raghu · Katy Blumer · Rory sayres · Ziad Obermeyer · Bobby Kleinberg · Sendhil Mullainathan · Jon Kleinberg
[ Slides]  [ Video] 
Oral
Wed Jun 12 12:00 PM -- 12:05 PM (PDT) @ Grand Ballroom
Wasserstein Adversarial Examples via Projected Sinkhorn Iterations
In Adversarial Examples
Eric Wong · Frank R Schmidt · Zico Kolter
[ Slides]  [ Video] 
Oral
Wed Jun 12 12:00 PM -- 12:05 PM (PDT) @ Room 102
SELFIE: Refurbishing Unclean Samples for Robust Deep Learning
In Robust Statistics and Machine Learning
Hwanjun Song · Minseok Kim · Jae-Gil Lee
[ Slides]  [ Video] 
Oral
Wed Jun 12 12:00 PM -- 12:05 PM (PDT) @ Room 104
The Anisotropic Noise in Stochastic Gradient Descent: Its Behavior of Escaping from Sharp Minima and Regularization Effects
In Deep Learning Theory
Zhanxing Zhu · Jingfeng Wu · Bing Yu · Lei Wu · Jinwen Ma
[ Slides]  [ Video] 
Oral
Wed Jun 12 12:05 PM -- 12:10 PM (PDT) @ Grand Ballroom
Transferable Clean-Label Poisoning Attacks on Deep Neural Nets
In Adversarial Examples
Chen Zhu · W. Ronny Huang · Hengduo Li · Gavin Taylor · Christoph Studer · Tom Goldstein
[ Slides]  [ Video] 
Oral
Wed Jun 12 12:05 PM -- 12:10 PM (PDT) @ Hall A
Emerging Convolutions for Generative Normalizing Flows
In Deep Generative Models
Emiel Hoogeboom · Rianne Van den Berg · Max Welling
[ Slides] 
Oral
Wed Jun 12 12:05 PM -- 12:10 PM (PDT) @ Room 104
Characterizing Well-Behaved vs. Pathological Deep Neural Networks
In Deep Learning Theory
Antoine Labatie
[ Slides]  [ Video] 
Oral
Wed Jun 12 12:05 PM -- 12:10 PM (PDT) @ Room 102
Zeno: Distributed Stochastic Gradient Descent with Suspicion-based Fault-tolerance
In Robust Statistics and Machine Learning
Cong Xie · Sanmi Koyejo · Indranil Gupta
[ Slides]  [ Video] 
Oral
Wed Jun 12 12:05 PM -- 12:10 PM (PDT) @ Hall B
Taming MAML: Efficient unbiased meta-reinforcement learning
In Deep RL
Hao Liu · Richard Socher · Caiming Xiong
[ Slides]  [ Video] 
Oral
Wed Jun 12 12:05 PM -- 12:10 PM (PDT) @ Room 201
Dynamic Measurement Scheduling for Event Forecasting using Deep RL
In Applications
Chun-Hao (Kingsley) Chang · Mingjie Mai · Anna Goldenberg
[ Slides]  [ Video] 
Oral
Wed Jun 12 12:05 PM -- 12:10 PM (PDT) @ Room 101
Deep Gaussian Processes with Importance-Weighted Variational Inference
In Gaussian Processes
Hugh Salimbeni · Vincent Dutordoir · James Hensman · Marc P Deisenroth
[ Slides]  [ Video] 
Oral
Wed Jun 12 12:05 PM -- 12:10 PM (PDT) @ Room 103
Noisy Dual Principal Component Pursuit
In Optimization
Tianyu Ding · Zhihui Zhu · Tianjiao Ding · Yunchen Yang · Daniel Robinson · Manolis Tsakiris · Rene Vidal
[ Slides]  [ Video] 
Oral
Wed Jun 12 12:05 PM -- 12:10 PM (PDT) @ Seaside Ballroom
Online Learning to Rank with Features
In Reinforcement Learning and Bandits
Shuai Li · Tor Lattimore · Csaba Szepesvari
[ Slides] 
Oral
Wed Jun 12 12:10 PM -- 12:15 PM (PDT) @ Room 101
Automated Model Selection with Bayesian Quadrature
In Gaussian Processes
Henry Chai · Jean-Francois Ton · Michael A Osborne · Roman Garnett
[ Slides]  [ Video] 
Oral
Wed Jun 12 12:10 PM -- 12:15 PM (PDT) @ Room 104
Understanding Geometry of Encoder-Decoder CNNs
In Deep Learning Theory
Jong Chul Ye · woonkyoung Sung
[ Slides]  [ Video] 
Oral
Wed Jun 12 12:10 PM -- 12:15 PM (PDT) @ Seaside Ballroom
On the Design of Estimators for Bandit Off-Policy Evaluation
In Reinforcement Learning and Bandits
Nikos Vlassis · Aurelien Bibaut · Maria Dimakopoulou · Tony Jebara
[ Slides]  [ Video] 
Oral
Wed Jun 12 12:10 PM -- 12:15 PM (PDT) @ Room 201
Parameter efficient training of deep convolutional neural networks by dynamic sparse reparameterization
In Applications
Hesham Mostafa · Xin Wang
[ Slides]  [ Video] 
Oral
Wed Jun 12 12:10 PM -- 12:15 PM (PDT) @ Grand Ballroom
NATTACK: Learning the Distributions of Adversarial Examples for an Improved Black-Box Attack on Deep Neural Networks
In Adversarial Examples
Yandong li · Lijun Li · Liqiang Wang · Tong Zhang · Boqing Gong
[ Slides]  [ Video] 
Oral
Wed Jun 12 12:10 PM -- 12:15 PM (PDT) @ Room 102
Concentration Inequalities for Conditional Value at Risk
In Robust Statistics and Machine Learning
Philip Thomas · Erik Learned-Miller
[ Slides] 
Oral
Wed Jun 12 12:10 PM -- 12:15 PM (PDT) @ Hall B
Self-Supervised Exploration via Disagreement
In Deep RL
Deepak Pathak · Dhiraj Gandhi · Abhinav Gupta
[ Slides]  [ Video] 
Oral
Wed Jun 12 12:10 PM -- 12:15 PM (PDT) @ Hall A
A Large-Scale Study on Regularization and Normalization in GANs
In Deep Generative Models
Karol Kurach · Mario Lucic · Xiaohua Zhai · Marcin Michalski · Sylvain Gelly
[ Slides] 
Oral
Wed Jun 12 12:10 PM -- 12:15 PM (PDT) @ Room 103
Learning a Compressed Sensing Measurement Matrix via Gradient Unrolling
In Optimization
Shanshan Wu · Alexandros Dimakis · Sujay Sanghavi · Felix Xinnan Yu · Daniel Holtmann-Rice · Dmitry Storcheus · Afshin Rostamizadeh · Sanjiv Kumar
[ Slides]  [ Video] 
Oral
Wed Jun 12 12:15 PM -- 12:20 PM (PDT) @ Room 201
DeepNose: Using artificial neural networks to represent the space of odorants
In Applications
Ngoc Tran · Daniel Kepple · Sergey Shuvaev · Alexei Koulakov
[ Slides]  [ Video] 
Oral
Wed Jun 12 12:15 PM -- 12:20 PM (PDT) @ Seaside Ballroom
Dynamic Learning with Frequent New Product Launches: A Sequential Multinomial Logit Bandit Problem
In Reinforcement Learning and Bandits
Junyu Cao · Wei Sun
[ Slides]  [ Video] 
Oral
Wed Jun 12 12:15 PM -- 12:20 PM (PDT) @ Grand Ballroom
Simple Black-box Adversarial Attacks
In Adversarial Examples
Chuan Guo · Jacob Gardner · Yurong You · Andrew Wilson · Kilian Weinberger
[ Slides]  [ Video] 
Oral
Wed Jun 12 12:15 PM -- 12:20 PM (PDT) @ Room 104
Traditional and Heavy Tailed Self Regularization in Neural Network Models
In Deep Learning Theory
Michael Mahoney · Charles H Martin
[ Slides]  [ Video] 
Oral
Wed Jun 12 12:15 PM -- 12:20 PM (PDT) @ Hall B
Efficient Off-Policy Meta-Reinforcement Learning via Probabilistic Context Variables
In Deep RL
Kate Rakelly · Aurick Zhou · Chelsea Finn · Sergey Levine · Deirdre Quillen
[ Slides]  [ Video] 
Oral
Wed Jun 12 12:15 PM -- 12:20 PM (PDT) @ Room 103
Screening rules for Lasso with non-convex Sparse Regularizers
In Optimization
alain rakotomamonjy · Gilles Gasso · Joseph Salmon
[ Slides]  [ Video] 
Oral
Wed Jun 12 12:15 PM -- 12:20 PM (PDT) @ Hall A
Variational Annealing of GANs: A Langevin Perspective
In Deep Generative Models
Chenyang Tao · Shuyang Dai · Liqun Chen · Ke Bai · Junya Chen · Chang Liu · RUIYI (ROY) ZHANG · Georgiy Bobashev · Lawrence Carin
[ Slides] 
Oral
Wed Jun 12 12:15 PM -- 12:20 PM (PDT) @ Room 102
Data Poisoning Attacks in Multi-Party Learning
In Robust Statistics and Machine Learning
Saeed Mahloujifar · Mohammad Mahmoody · Ameer Mohammed
[ Slides]  [ Video] 
Break
Wed Jun 12 12:30 PM -- 02:00 PM (PDT)
Lunch - on your own
Oral
Wed Jun 12 02:00 PM -- 02:20 PM (PDT) @ Room 101
Beyond the Chinese Restaurant and Pitman-Yor processes: Statistical Models with double power-law behavior
In Bayesian Non-parametrics
Fadhel Ayed · Juho Lee · Francois Caron
[ Video] 
Oral
Wed Jun 12 02:00 PM -- 02:20 PM (PDT) @ Grand Ballroom
Causal Identification under Markov Equivalence: Completeness Results
In Causality
Amin Jaber · Jiji Zhang · Elias Bareinboim
[ Video] 
Oral
Wed Jun 12 02:00 PM -- 02:20 PM (PDT) @ Room 103
Monge blunts Bayes: Hardness Results for Adversarial Training
In Statistical Learning Theory
Zac Cranko · Aditya Menon · Richard Nock · Cheng Soon Ong · Zhan Shi · Christian Walder
[ Slides]  [ Video] 
Oral
Wed Jun 12 02:00 PM -- 02:20 PM (PDT) @ Seaside Ballroom
Context-Aware Zero-Shot Learning for Object Recognition
In Applications: Computer Vision
Eloi Zablocki · Patrick Bordes · Laure Soulier · Benjamin Piwowarski · Patrick Gallinari
[ Video] 
Oral
Wed Jun 12 02:00 PM -- 02:20 PM (PDT) @ Hall A
Invertible Residual Networks
In Deep Learning Architectures
Jens Behrmann · Will Grathwohl · Ricky T. Q. Chen · David Duvenaud · Joern-Henrik Jacobsen
[ Video] 
Oral
Wed Jun 12 02:00 PM -- 02:20 PM (PDT) @ Hall B
The Natural Language of Actions
In Deep RL
Guy Tennenholtz · Shie Mannor
[ Slides]  [ Video] 
Oral
Wed Jun 12 02:00 PM -- 02:20 PM (PDT) @ Room 102
Distributed Weighted Matching via Randomized Composable Coresets
In Combinatorial Optimization
Sepehr Assadi · Mohammad Hossein Bateni · Vahab Mirrokni
[ Slides] 
Oral
Wed Jun 12 02:00 PM -- 02:20 PM (PDT) @ Room 201
Domain Agnostic Learning with Disentangled Representations
In Transfer and Multitask Learning
Xingchao Peng · Zijun Huang · Ximeng Sun · Kate Saenko
[ Video] 
Oral
Wed Jun 12 02:00 PM -- 02:20 PM (PDT) @ Room 104
Almost surely constrained convex optimization
In Optimization: Convex and Non-convex
Olivier Fercoq · Ahmet Alacaoglu · Ion Necoara · Volkan Cevher
[ Slides]  [ Video] 
Oral
Wed Jun 12 02:20 PM -- 02:25 PM (PDT) @ Hall A
NAS-Bench-101: Towards Reproducible Neural Architecture Search
In Deep Learning Architectures
Chris Ying · Aaron Klein · Eric Christiansen · Esteban Real · Kevin Murphy · Frank Hutter
[ Slides]  [ Video] 
Oral
Wed Jun 12 02:20 PM -- 02:25 PM (PDT) @ Grand Ballroom
Counterfactual Off-Policy Evaluation with Gumbel-Max Structural Causal Models
In Causality
Michael Oberst · David Sontag
[ Slides]  [ Video] 
Oral
Wed Jun 12 02:20 PM -- 02:25 PM (PDT) @ Room 201
Composing Value Functions in Reinforcement Learning
In Transfer and Multitask Learning
Benjamin van Niekerk · Steven James · Adam Earle · Benjamin Rosman
Oral
Wed Jun 12 02:20 PM -- 02:25 PM (PDT) @ Room 103
Better generalization with less data using robust gradient descent
In Statistical Learning Theory
Matthew J. Holland · Kazushi Ikeda
[ Slides]  [ Video] 
Oral
Wed Jun 12 02:20 PM -- 02:25 PM (PDT) @ Room 102
Multivariate Submodular Optimization
In Combinatorial Optimization
Richard Santiago · F. Bruce Shepherd
[ Slides] 
Oral
Wed Jun 12 02:20 PM -- 02:25 PM (PDT) @ Seaside Ballroom
Band-limited Training and Inference for Convolutional Neural Networks
In Applications: Computer Vision
Adam Dziedzic · John Paparrizos · Sanjay Krishnan · Aaron Elmore · Michael Franklin
[ Slides] 
Oral
Wed Jun 12 02:20 PM -- 02:25 PM (PDT) @ Room 104
Generalized Majorization-Minimization
In Optimization: Convex and Non-convex
Sobhan Naderi Parizi · Kun He · Reza Aghajani · Stan Sclaroff · Pedro Felzenszwalb
[ Slides]  [ Video] 
Oral
Wed Jun 12 02:20 PM -- 02:25 PM (PDT) @ Room 101
DP-GP-LVM: A Bayesian Non-Parametric Model for Learning Multivariate Dependency Structures
In Bayesian Non-parametrics
Andrew R Lawrence · Carl Henrik Ek · Neill Campbell
[ Slides]  [ Video] 
Oral
Wed Jun 12 02:20 PM -- 02:25 PM (PDT) @ Hall B
Control Regularization for Reduced Variance Reinforcement Learning
In Deep RL
Richard Cheng · Abhinav Verma · Gabor Orosz · Swarat Chaudhuri · Yisong Yue · Joel Burdick
[ Slides]  [ Video] 
Oral
Wed Jun 12 02:25 PM -- 02:30 PM (PDT) @ Hall A
Approximated Oracle Filter Pruning for Destructive CNN Width Optimization
In Deep Learning Architectures
XIAOHAN DING · guiguang ding · Yuchen Guo · Jungong Han · Chenggang Yan
[ Slides]  [ Video] 
Oral
Wed Jun 12 02:25 PM -- 02:30 PM (PDT) @ Room 102
Beyond Adaptive Submodularity: Approximation Guarantees of Greedy Policy with Adaptive Submodularity Ratio
In Combinatorial Optimization
Kaito Fujii · Shinsaku Sakaue
Oral
Wed Jun 12 02:25 PM -- 02:30 PM (PDT) @ Room 201
Fast Context Adaptation via Meta-Learning
In Transfer and Multitask Learning
Luisa Zintgraf · Kyriacos Shiarlis · Vitaly Kurin · Katja Hofmann · Shimon Whiteson
[ Slides]  [ Video] 
Oral
Wed Jun 12 02:25 PM -- 02:30 PM (PDT) @ Room 103
Near optimal finite time identification of arbitrary linear dynamical systems
In Statistical Learning Theory
Tuhin Sarkar · Alexander Rakhlin
[ Slides]  [ Video] 
Oral
Wed Jun 12 02:25 PM -- 02:30 PM (PDT) @ Seaside Ballroom
Learning Classifiers for Target Domain with Limited or No Labels
In Applications: Computer Vision
Pengkai Zhu · Hanxiao Wang · Venkatesh Saligrama
[ Slides] 
Oral
Wed Jun 12 02:25 PM -- 02:30 PM (PDT) @ Room 104
On the Computation and Communication Complexity of Parallel SGD with Dynamic Batch Sizes for Stochastic Non-Convex Optimization
In Optimization: Convex and Non-convex
Hao Yu · rong jin
[ Slides]  [ Video] 
Oral
Wed Jun 12 02:25 PM -- 02:30 PM (PDT) @ Room 101
Random Function Priors for Correlation Modeling
In Bayesian Non-parametrics
Aonan Zhang · John Paisley
[ Slides]  [ Video] 
Oral
Wed Jun 12 02:25 PM -- 02:30 PM (PDT) @ Hall B
On the Generalization Gap in Reparameterizable Reinforcement Learning
In Deep RL
Huan Wang · Stephan Zheng · Caiming Xiong · Richard Socher
[ Slides]  [ Video] 
Oral
Wed Jun 12 02:25 PM -- 02:30 PM (PDT) @ Grand Ballroom
Causal Discovery and Forecasting in Nonstationary Environments with State-Space Models
In Causality
Biwei Huang · Kun Zhang · Mingming Gong · Clark Glymour
[ Slides]  [ Video] 
Oral
Wed Jun 12 02:30 PM -- 02:35 PM (PDT) @ Hall B
Trajectory-Based Off-Policy Deep Reinforcement Learning
In Deep RL
Andreas Doerr · Michael Volpp · Marc Toussaint · Sebastian Trimpe · Christian Daniel
[ Slides]  [ Video] 
Oral
Wed Jun 12 02:30 PM -- 02:35 PM (PDT) @ Hall A
LegoNet: Efficient Convolutional Neural Networks with Lego Filters
In Deep Learning Architectures
Zhaohui Yang · Yunhe Wang · Chuanjian Liu · Hanting Chen · Chunjing Xu · Boxin Shi · Chao Xu · Chang Xu
[ Slides]  [ Video] 
Oral
Wed Jun 12 02:30 PM -- 02:35 PM (PDT) @ Room 104
Simple Stochastic Gradient Methods for Non-Smooth Non-Convex Regularized Optimization
In Optimization: Convex and Non-convex
Michael Metel · Akiko Takeda
[ Slides]  [ Video] 
Oral
Wed Jun 12 02:30 PM -- 02:35 PM (PDT) @ Room 201
Provable Guarantees for Gradient-Based Meta-Learning
In Transfer and Multitask Learning
Nina Balcan · Mikhail Khodak · Ameet Talwalkar
[ Slides]  [ Video] 
Oral
Wed Jun 12 02:30 PM -- 02:35 PM (PDT) @ Room 102
Approximating Orthogonal Matrices with Effective Givens Factorization
In Combinatorial Optimization
Thomas Frerix · Joan Bruna
[ Slides] 
Oral
Wed Jun 12 02:30 PM -- 02:35 PM (PDT) @ Room 103
Lossless or Quantized Boosting with Integer Arithmetic
In Statistical Learning Theory
Richard Nock · Robert C Williamson
[ Slides]  [ Video] 
Oral
Wed Jun 12 02:30 PM -- 02:35 PM (PDT) @ Grand Ballroom
Classifying Treatment Responders Under Causal Effect Monotonicity
In Causality
Nathan Kallus
[ Slides]  [ Video] 
Oral
Wed Jun 12 02:30 PM -- 02:35 PM (PDT) @ Room 101
Variational Russian Roulette for Deep Bayesian Nonparametrics
In Bayesian Non-parametrics
Kai Xu · Akash Srivastava · Charles Sutton
[ Slides]  [ Video] 
Oral
Wed Jun 12 02:30 PM -- 02:35 PM (PDT) @ Seaside Ballroom
Population Based Augmentation: Efficient Learning of Augmentation Policy Schedules
In Applications: Computer Vision
Daniel Ho · Eric Liang · Peter Chen · Ion Stoica · Pieter Abbeel
[ Slides]  [ Video] 
Oral
Wed Jun 12 02:35 PM -- 02:40 PM (PDT) @ Room 101
Incorporating Grouping Information into Bayesian Decision Tree Ensembles
In Bayesian Non-parametrics
JUNLIANG DU · Antonio Linero
[ Slides]  [ Video] 
Oral
Wed Jun 12 02:35 PM -- 02:40 PM (PDT) @ Room 102
New results on information theoretic clustering
In Combinatorial Optimization
Ferdinando Cicalese · Eduardo Laber · Lucas Murtinho
[ Slides] 
Oral
Wed Jun 12 02:35 PM -- 02:40 PM (PDT) @ Hall A
Sorting Out Lipschitz Function Approximation
In Deep Learning Architectures
Cem Anil · James Lucas · Roger Grosse
[ Slides]  [ Video] 
Oral
Wed Jun 12 02:35 PM -- 02:40 PM (PDT) @ Hall B
A Deep Reinforcement Learning Perspective on Internet Congestion Control
In Deep RL
Nathan Jay · Noga H. Rotman · Brighten Godfrey · Michael Schapira · Aviv Tamar
[ Slides]  [ Video] 
Oral
Wed Jun 12 02:35 PM -- 02:40 PM (PDT) @ Room 201
Towards Understanding Knowledge Distillation
In Transfer and Multitask Learning
Mary Phuong · Christoph H. Lampert
[ Slides]  [ Video] 
Oral
Wed Jun 12 02:35 PM -- 02:40 PM (PDT) @ Room 104
Surrogate Losses for Online Learning of Stepsizes in Stochastic Non-Convex Optimization
In Optimization: Convex and Non-convex
zhenxun zhuang · Ashok Cutkosky · Francesco Orabona
[ Slides]  [ Video] 
Oral
Wed Jun 12 02:35 PM -- 02:40 PM (PDT) @ Seaside Ballroom
Anomaly Detection With Multiple-Hypotheses Predictions
In Applications: Computer Vision
Duc Tam Nguyen · Zhongyu Lou · Michael Klar · Thomas Brox
[ Slides]  [ Video] 
Oral
Wed Jun 12 02:35 PM -- 02:40 PM (PDT) @ Room 103
Orthogonal Random Forest for Causal Inference
In Statistical Learning Theory
Miruna Oprescu · Vasilis Syrgkanis · Steven Wu
[ Slides]  [ Video] 
Oral
Wed Jun 12 02:35 PM -- 02:40 PM (PDT) @ Grand Ballroom
Learning Models from Data with Measurement Error: Tackling Underreporting
In Causality
Roy Adams · Yuelong Ji · Xiaobin Wang · Suchi Saria
[ Slides]  [ Video] 
Oral
Wed Jun 12 02:40 PM -- 03:00 PM (PDT) @ Hall B
Model-Based Active Exploration
In Deep RL
Pranav Shyam · Wojciech Jaśkowski · Faustino Gomez
[ Video] 
Oral
Wed Jun 12 02:40 PM -- 03:00 PM (PDT) @ Room 103
MONK -- Outlier-Robust Mean Embedding Estimation by Median-of-Means
In Statistical Learning Theory
Matthieu Lerasle · Zoltan Szabo · Timothée Mathieu · Guillaume Lecue
[ Video] 
Oral
Wed Jun 12 02:40 PM -- 03:00 PM (PDT) @ Grand Ballroom
Adjustment Criteria for Generalizing Experimental Findings
In Causality
Juan Correa · Jin Tian · Elias Bareinboim
[ Slides]  [ Video] 
Oral
Wed Jun 12 02:40 PM -- 03:00 PM (PDT) @ Seaside Ballroom
Kernel Mean Matching for Content Addressability of GANs
In Applications: Computer Vision
Wittawat Jitkrittum · Wittawat Jitkrittum · Patsorn Sangkloy · Patsorn Sangkloy · Muhammad Waleed Gondal · Muhammad Waleed Gondal · Amit Raj · Amit Raj · James Hays · James Hays · Bernhard Schölkopf · Bernhard Schölkopf
[ Video] 
Oral
Wed Jun 12 02:40 PM -- 03:00 PM (PDT) @ Hall A
Graph Element Networks: adaptive, structured computation and memory
In Deep Learning Architectures
Ferran Alet · Adarsh Keshav Jeewajee · Maria Bauza Villalonga · Alberto Rodriguez · Tomas Lozano-Perez · Leslie Kaelbling
[ Slides]  [ Video] 
Oral
Wed Jun 12 02:40 PM -- 03:00 PM (PDT) @ Room 104
Efficient Dictionary Learning with Gradient Descent
In Optimization: Convex and Non-convex
Dar Gilboa · Sam Buchanan · John Wright
[ Video] 
Oral
Wed Jun 12 02:40 PM -- 03:00 PM (PDT) @ Room 102
Improved Parallel Algorithms for Density-Based Network Clustering
In Combinatorial Optimization
Mohsen Ghaffari · Silvio Lattanzi · Slobodan Mitrović
[ Slides] 
Oral
Wed Jun 12 02:40 PM -- 03:00 PM (PDT) @ Room 101
Variational Implicit Processes
In Bayesian Non-parametrics
Chao Ma · Yingzhen Li · Jose Miguel Hernandez-Lobato
[ Video] 
Oral
Wed Jun 12 02:40 PM -- 03:00 PM (PDT) @ Room 201
Transferable Adversarial Training: A General Approach to Adapting Deep Classifiers
In Transfer and Multitask Learning
Hong Liu · Mingsheng Long · Jianmin Wang · Michael Jordan
[ Slides]  [ Video] 
Oral
Wed Jun 12 03:00 PM -- 03:05 PM (PDT) @ Room 201
Transferability vs. Discriminability: Batch Spectral Penalization for Adversarial Domain Adaptation
In Transfer and Multitask Learning
Xinyang Chen · Sinan Wang · Mingsheng Long · Jianmin Wang
[ Slides]  [ Video] 
Oral
Wed Jun 12 03:00 PM -- 03:05 PM (PDT) @ Hall A
Training CNNs with Selective Allocation of Channels
In Deep Learning Architectures
Jongheon Jeong · Jinwoo Shin
[ Slides]  [ Video] 
Oral
Wed Jun 12 03:00 PM -- 03:05 PM (PDT) @ Seaside Ballroom
Neural Inverse Knitting: From Images to Manufacturing Instructions
In Applications: Computer Vision
Alexandre Kaspar · Tae-Hyun Oh · Liane Makatura · Petr Kellnhofer · Wojciech Matusik
[ Slides]  [ Video] 
Oral
Wed Jun 12 03:00 PM -- 03:05 PM (PDT) @ Hall B
Extrapolating Beyond Suboptimal Demonstrations via Inverse Reinforcement Learning from Observations
In Deep RL
Daniel Brown · Wonjoon Goo · Prabhat Nagarajan · Scott Niekum
[ Slides]  [ Video] 
Oral
Wed Jun 12 03:00 PM -- 03:05 PM (PDT) @ Room 104
Plug-and-Play Methods Provably Converge with Properly Trained Denoisers
In Optimization: Convex and Non-convex
Ernest Ryu · Jialin Liu · Sicheng Wang · Xiaohan Chen · Zhangyang Wang · Wotao Yin
[ Slides]  [ Video] 
Oral
Wed Jun 12 03:00 PM -- 03:05 PM (PDT) @ Room 101
Discovering Latent Covariance Structures for Multiple Time Series
In Bayesian Non-parametrics
Anh Tong · Jaesik Choi
[ Slides]  [ Video] 
Oral
Wed Jun 12 03:00 PM -- 03:05 PM (PDT) @ Room 102
Submodular Observation Selection and Information Gathering for Quadratic Models
In Combinatorial Optimization
Abolfazl Hashemi · Mahsa Ghasemi · Haris Vikalo · Ufuk Topcu
[ Slides] 
Oral
Wed Jun 12 03:00 PM -- 03:05 PM (PDT) @ Room 103
The advantages of multiple classes for reducing overfitting from test set reuse
In Statistical Learning Theory
Vitaly Feldman · Roy Frostig · Moritz Hardt
[ Slides]  [ Video] 
Oral
Wed Jun 12 03:00 PM -- 03:05 PM (PDT) @ Grand Ballroom
Conditional Independence in Testing Bayesian Networks
In Causality
Yujia Shen · Haiying Huang · Arthur Choi · Adnan Darwiche
[ Slides]  [ Video] 
Oral
Wed Jun 12 03:05 PM -- 03:10 PM (PDT) @ Hall A
Equivariant Transformer Networks
In Deep Learning Architectures
Kai Sheng Tai · Peter Bailis · Gregory Valiant
[ Slides]  [ Video] 
Oral
Wed Jun 12 03:05 PM -- 03:10 PM (PDT) @ Room 102
Submodular Cost Submodular Cover with an Approximate Oracle
In Combinatorial Optimization
Victoria Crawford · Alan Kuhnle · My T Thai
[ Slides] 
Oral
Wed Jun 12 03:05 PM -- 03:10 PM (PDT) @ Room 103
On the statistical rate of nonlinear recovery in generative models with heavy-tailed data
In Statistical Learning Theory
Xiaohan Wei · Zhuoran Yang · Zhaoran Wang
[ Slides]  [ Video] 
Oral
Wed Jun 12 03:05 PM -- 03:10 PM (PDT) @ Grand Ballroom
Sensitivity Analysis of Linear Structural Causal Models
In Causality
Carlos Cinelli · Daniel Kumor · Bryant Chen · Judea Pearl · Elias Bareinboim
[ Slides]  [ Video] 
Oral
Wed Jun 12 03:05 PM -- 03:10 PM (PDT) @ Seaside Ballroom
Making Convolutional Networks Shift-Invariant Again
In Applications: Computer Vision
Richard Zhang
[ Slides]  [ Video] 
Oral
Wed Jun 12 03:05 PM -- 03:10 PM (PDT) @ Room 104
Riemannian adaptive stochastic gradient algorithms on matrix manifolds
In Optimization: Convex and Non-convex
Hiroyuki Kasai · Pratik Kumar Jawanpuria · Bamdev Mishra
[ Slides]  [ Video] 
Oral
Wed Jun 12 03:05 PM -- 03:10 PM (PDT) @ Room 201
Learning-to-Learn Stochastic Gradient Descent with Biased Regularization
In Transfer and Multitask Learning
Giulia Denevi · Carlo Ciliberto · Riccardo Grazzi · Massimiliano Pontil
[ Slides]  [ Video] 
Oral
Wed Jun 12 03:05 PM -- 03:10 PM (PDT) @ Room 101
Scalable Training of Inference Networks for Gaussian-Process Models
In Bayesian Non-parametrics
Jiaxin Shi · Mohammad Emtiyaz Khan · Jun Zhu
[ Slides]  [ Video] 
Oral
Wed Jun 12 03:05 PM -- 03:10 PM (PDT) @ Hall B
Distributional Multivariate Policy Evaluation and Exploration with the Bellman GAN
In Deep RL
dror freirich · Tzahi Shimkin · Ron Meir · Aviv Tamar
Oral
Wed Jun 12 03:10 PM -- 03:15 PM (PDT) @ Room 103
Phase transition in PCA with missing data: Reduced signal-to-noise ratio, not sample size!
In Statistical Learning Theory
Niels Ipsen · Lars Kai Hansen
[ Slides]  [ Video] 
Oral
Wed Jun 12 03:10 PM -- 03:15 PM (PDT) @ Room 201
BERT and PALs: Projected Attention Layers for Efficient Adaptation in Multi-Task Learning
In Transfer and Multitask Learning
Asa Cooper Stickland · Iain Murray
[ Slides]  [ Video] 
Oral
Wed Jun 12 03:10 PM -- 03:15 PM (PDT) @ Grand Ballroom
More Efficient Off-Policy Evaluation through Regularized Targeted Learning
In Causality
Aurelien Bibaut · Ivana Malenica · Nikos Vlassis · Mark van der Laan
[ Slides]  [ Video] 
Oral
Wed Jun 12 03:10 PM -- 03:15 PM (PDT) @ Seaside Ballroom
Generative Modeling of Infinite Occluded Objects for Compositional Scene Representation
In Applications: Computer Vision
Jinyang Yuan · Bin Li · Xiangyang Xue
[ Slides] 
Oral
Wed Jun 12 03:10 PM -- 03:15 PM (PDT) @ Room 101
Bayesian Optimization Meets Bayesian Optimal Stopping
In Bayesian Non-parametrics
Zhongxiang Dai · Haibin Yu · Bryan Kian Hsiang Low · Patrick Jaillet
[ Slides]  [ Video] 
Oral
Wed Jun 12 03:10 PM -- 03:15 PM (PDT) @ Hall A
Overcoming Multi-model Forgetting
In Deep Learning Architectures
Yassine Benyahia · Kaicheng Yu · Kamil Bennani-Smires · Martin Jaggi · Anthony C. Davison · Mathieu Salzmann · Claudiu Musat
[ Slides]  [ Video] 
Oral
Wed Jun 12 03:10 PM -- 03:15 PM (PDT) @ Hall B
A Baseline for Any Order Gradient Estimation in Stochastic Computation Graphs
In Deep RL
Jingkai Mao · Jakob Foerster · Tim Rocktäschel · Maruan Al-Shedivat · Gregory Farquhar · Shimon Whiteson
[ Slides]  [ Video] 
Oral
Wed Jun 12 03:10 PM -- 03:15 PM (PDT) @ Room 104
Stochastic Optimization for DC Functions and Non-smooth Non-convex Regularizers with Non-asymptotic Convergence
In Optimization: Convex and Non-convex
Yi Xu · Qi Qi · Qihang Lin · rong jin · Tianbao Yang
[ Slides]  [ Video] 
Oral
Wed Jun 12 03:10 PM -- 03:15 PM (PDT) @ Room 102
Submodular Streaming in All Its Glory: Tight Approximation, Minimum Memory and Low Adaptive Complexity
In Combinatorial Optimization
Ehsan Kazemi · Marko Mitrovic · Morteza Zadimoghaddam · Silvio Lattanzi · Amin Karbasi
[ Slides] 
Oral
Wed Jun 12 03:15 PM -- 03:20 PM (PDT) @ Seaside Ballroom
IMEXnet - A Forward Stable Deep Neural Network
In Applications: Computer Vision
Eldad Haber · Keegan Lensink · Eran Treister · Lars Ruthotto
[ Slides]  [ Video] 
Oral
Wed Jun 12 03:15 PM -- 03:20 PM (PDT) @ Room 102
Hiring Under Uncertainty
In Combinatorial Optimization
Manish Purohit · Sreenivas Gollapudi · Manish Raghavan
[ Slides] 
Oral
Wed Jun 12 03:15 PM -- 03:20 PM (PDT) @ Room 101
Learning interpretable continuous-time models of latent stochastic dynamical systems
In Bayesian Non-parametrics
Lea Duncker · Gergo Bohner · Julien Boussard · Maneesh Sahani
[ Slides]  [ Video] 
Oral
Wed Jun 12 03:15 PM -- 03:20 PM (PDT) @ Room 104
Alternating Minimizations Converge to Second-Order Optimal Solutions
In Optimization: Convex and Non-convex
Qiuwei Li · Zhihui Zhu · Gongguo Tang
[ Slides]  [ Video] 
Oral
Wed Jun 12 03:15 PM -- 03:20 PM (PDT) @ Grand Ballroom
Inferring Heterogeneous Causal Effects in Presence of Spatial Confounding
In Causality
Muhammad Osama · Dave Zachariah · Thomas Schön
[ Slides]  [ Video] 
Oral
Wed Jun 12 03:15 PM -- 03:20 PM (PDT) @ Room 103
On Medians of (Randomized) Pairwise Means
In Statistical Learning Theory
Stephan Clemencon · Pierre Laforgue · Patrice Bertail
[ Slides]  [ Video] 
Oral
Wed Jun 12 03:15 PM -- 03:20 PM (PDT) @ Hall A
Bayesian Nonparametric Federated Learning of Neural Networks
In Deep Learning Architectures
Mikhail Yurochkin · Mayank Agarwal · Soumya Ghosh · Kristjan Greenewald · Nghia Hoang · Yasaman Khazaeni
[ Slides]  [ Video] 
Oral
Wed Jun 12 03:15 PM -- 03:20 PM (PDT) @ Room 201
Towards Accurate Model Selection in Deep Unsupervised Domain Adaptation
In Transfer and Multitask Learning
Kaichao You · Ximei Wang · Mingsheng Long · Michael Jordan
Oral
Wed Jun 12 03:15 PM -- 03:20 PM (PDT) @ Hall B
Remember and Forget for Experience Replay
In Deep RL
Guido Novati · Petros Koumoutsakos
[ Slides]  [ Video] 
Break
Wed Jun 12 03:30 PM -- 04:00 PM (PDT)
Coffee Break
Oral
Wed Jun 12 04:00 PM -- 04:20 PM (PDT) @ Room 101
A Tree-Based Method for Fast Repeated Sampling of Determinantal Point Processes
In Probabilistic Inference
Jennifer Gillenwater · Alex Kulesza · Zelda Mariet · Sergei Vassilvitskii
[ Video] 
Oral
Wed Jun 12 04:00 PM -- 04:20 PM (PDT) @ Hall A
How does Disagreement Help Generalization against Label Corruption?
In Deep Learning Algorithms
Xingrui Yu · Bo Han · Jiangchao Yao · Gang Niu · Ivor Tsang · Masashi Sugiyama
[ Slides]  [ Video] 
Oral
Wed Jun 12 04:00 PM -- 04:20 PM (PDT) @ Hall B
Tensor Variable Elimination for Plated Factor Graphs
In Generative Models
Fritz Obermeyer · Elias Bingham · Martin Jankowiak · Neeraj Pradhan · Justin Chiu · Alexander Rush · Noah Goodman
[ Slides]  [ Video] 
Oral
Wed Jun 12 04:00 PM -- 04:20 PM (PDT) @ Grand Ballroom
Adversarially Learned Representations for Information Obfuscation and Inference
In Representation Learning
Martin A Bertran · Natalia Martinez Gil · Afroditi Papadaki · Qiang Qiu · Miguel Rodrigues · Galen Reeves · Guillermo Sapiro
[ Slides]  [ Video] 
Oral
Wed Jun 12 04:00 PM -- 04:20 PM (PDT) @ Room 102
Position-aware Graph Neural Networks
In Networks and Relational Learning
Jiaxuan You · Rex (Zhitao) Ying · Jure Leskovec
[ Video] 
Oral
Wed Jun 12 04:00 PM -- 04:20 PM (PDT) @ Room 104
Provably Efficient Imitation Learning from Observation Alone
In Reinforcement Learning Theory
Wen Sun · Anirudh Vemula · Byron Boots · Drew Bagnell
[ Video] 
Oral
Wed Jun 12 04:00 PM -- 04:20 PM (PDT) @ Seaside Ballroom
Do ImageNet Classifiers Generalize to ImageNet?
In Robust Statistics and Interpretability
Benjamin Recht · Rebecca Roelofs · Ludwig Schmidt · Vaishaal Shankar
[ Video] 
Oral
Wed Jun 12 04:00 PM -- 04:20 PM (PDT) @ Room 201
Active Embedding Search via Noisy Paired Comparisons
In Active Learning
Gregory Canal · Andy Massimino · Mark Davenport · Christopher Rozell
[ Slides]  [ Video] 
Oral
Wed Jun 12 04:00 PM -- 04:20 PM (PDT) @ Room 103
Accelerated Linear Convergence of Stochastic Momentum Methods in Wasserstein Distances
In Convex Optimization
Bugra Can · Mert Gurbuzbalaban · Lingjiong Zhu
[ Video] 
Oral
Wed Jun 12 04:20 PM -- 04:25 PM (PDT) @ Hall A
EigenDamage: Structured Pruning in the Kronecker-Factored Eigenbasis
In Deep Learning Algorithms
Chaoqi Wang · Roger Grosse · Sanja Fidler · Guodong Zhang
[ Slides]  [ Video] 
Oral
Wed Jun 12 04:20 PM -- 04:25 PM (PDT) @ Room 102
Detecting Overlapping and Correlated Communities without Pure Nodes: Identifiability and Algorithm
In Networks and Relational Learning
Kejun Huang · Xiao Fu
[ Slides]  [ Video] 
Oral
Wed Jun 12 04:20 PM -- 04:25 PM (PDT) @ Seaside Ballroom
Exploring the Landscape of Spatial Robustness
In Robust Statistics and Interpretability
Logan Engstrom · Brandon Tran · Dimitris Tsipras · Ludwig Schmidt · Aleksander Madry
[ Slides]  [ Video] 
Oral
Wed Jun 12 04:20 PM -- 04:25 PM (PDT) @ Room 201
Fast Direct Search in an Optimally Compressed Continuous Target Space for Efficient Multi-Label Active Learning
In Active Learning
weishi shi · Qi Yu
[ Slides]  [ Video] 
Oral
Wed Jun 12 04:20 PM -- 04:25 PM (PDT) @ Room 103
SGD without Replacement: Sharper Rates for General Smooth Convex Functions
In Convex Optimization
Dheeraj Nagaraj · Prateek Jain · Praneeth Netrapalli
[ Slides]  [ Video] 
Oral
Wed Jun 12 04:20 PM -- 04:25 PM (PDT) @ Room 104
Dead-ends and Secure Exploration in Reinforcement Learning
In Reinforcement Learning Theory
Mehdi Fatemi · Shikhar Sharma · Harm van Seijen · Samira Ebrahimi Kahou
[ Slides]  [ Video] 
Oral
Wed Jun 12 04:20 PM -- 04:25 PM (PDT) @ Grand Ballroom
Adaptive Neural Trees
In Representation Learning
Ryutaro Tanno · Kai Arulkumaran · Daniel Alexander · Antonio Criminisi · Aditya Nori
[ Slides]  [ Video] 
Oral
Wed Jun 12 04:20 PM -- 04:25 PM (PDT) @ Room 101
Nonlinear Stein Variational Gradient Descent for Learning Diversified Mixture Models
In Probabilistic Inference
Dilin Wang · Qiang Liu
[ Slides]  [ Video] 
Oral
Wed Jun 12 04:20 PM -- 04:25 PM (PDT) @ Hall B
Predicate Exchange: Inference with Declarative Knowledge
In Generative Models
Zenna Tavares · Javier Burroni · Edgar Minasyan · Armando Solar-Lezama · Rajesh Ranganath
[ Slides]  [ Video] 
Oral
Wed Jun 12 04:25 PM -- 04:30 PM (PDT) @ Room 102
Learning Generative Models across Incomparable Spaces
In Networks and Relational Learning
Charlotte Bunne · David Alvarez-Melis · Andreas Krause · Stefanie Jegelka
[ Slides]  [ Video] 
Oral
Wed Jun 12 04:25 PM -- 04:30 PM (PDT) @ Room 104
Statistics and Samples in Distributional Reinforcement Learning
In Reinforcement Learning Theory
Mark Rowland · Robert Dadashi · Saurabh Kumar · Remi Munos · Marc Bellemare · Will Dabney
[ Slides]  [ Video] 
Oral
Wed Jun 12 04:25 PM -- 04:30 PM (PDT) @ Room 201
Myopic Posterior Sampling for Adaptive Goal Oriented Design of Experiments
In Active Learning
Kirthevasan Kandasamy · Willie Neiswanger · Reed Zhang · Akshay Krishnamurthy · Jeff Schneider · Barnabás Póczos
[ Slides]  [ Video] 
Oral
Wed Jun 12 04:25 PM -- 04:30 PM (PDT) @ Hall B
Discriminative Regularization for Latent Variable Models with Applications to Electrocardiography
In Generative Models
Andrew Miller · Ziad Obermeyer · John Cunningham · Sendhil Mullainathan
[ Slides]  [ Video] 
Oral
Wed Jun 12 04:25 PM -- 04:30 PM (PDT) @ Room 103
On the Complexity of Approximating Wasserstein Barycenters
In Convex Optimization
Alexey Kroshnin · Nazarii Tupitsa · Darina Dvinskikh · Pavel Dvurechenskii · Alexander Gasnikov · Cesar Uribe
[ Slides]  [ Video] 
Oral
Wed Jun 12 04:25 PM -- 04:30 PM (PDT) @ Hall A
Addressing the Loss-Metric Mismatch with Adaptive Loss Alignment
In Deep Learning Algorithms
Chen Huang · Shuangfei Zhai · Walter Talbott · Miguel Angel Bautista Martin · Shih-Yu Sun · Carlos Guestrin · Joshua M Susskind
[ Slides]  [ Video] 
Oral
Wed Jun 12 04:25 PM -- 04:30 PM (PDT) @ Grand Ballroom
Connectivity-Optimized Representation Learning via Persistent Homology
In Representation Learning
Christoph Hofer · Roland Kwitt · Marc Niethammer · Mandar Dixit
[ Slides]  [ Video] 
Oral
Wed Jun 12 04:25 PM -- 04:30 PM (PDT) @ Room 101
Understanding and Accelerating Particle-Based Variational Inference
In Probabilistic Inference
Chang Liu · Jingwei Zhuo · Pengyu Cheng · RUIYI (ROY) ZHANG · Jun Zhu
[ Slides]  [ Video] 
Oral
Wed Jun 12 04:25 PM -- 04:30 PM (PDT) @ Seaside Ballroom
Sever: A Robust Meta-Algorithm for Stochastic Optimization
In Robust Statistics and Interpretability
Ilias Diakonikolas · Gautam Kamath · Daniel Kane · Jerry Li · Jacob Steinhardt · Alistair Stewart
[ Slides]  [ Video] 
Oral
Wed Jun 12 04:30 PM -- 04:35 PM (PDT) @ Room 102
Relational Pooling for Graph Representations
In Networks and Relational Learning
Ryan Murphy · Balasubramaniam Srinivasan · Vinayak A Rao · Bruno Ribeiro
[ Slides]  [ Video] 
Oral
Wed Jun 12 04:30 PM -- 04:35 PM (PDT) @ Hall A
Deep Compressed Sensing
In Deep Learning Algorithms
Yan Wu · Mihaela Rosca · Timothy Lillicrap
[ Slides]  [ Video] 
Oral
Wed Jun 12 04:30 PM -- 04:35 PM (PDT) @ Seaside Ballroom
Analyzing Federated Learning through an Adversarial Lens
In Robust Statistics and Interpretability
Arjun Nitin Bhagoji · Supriyo Chakraborty · Prateek Mittal · Seraphin Calo
[ Slides]  [ Video] 
Oral
Wed Jun 12 04:30 PM -- 04:35 PM (PDT) @ Room 101
Efficient learning of smooth probability functions from Bernoulli tests with guarantees
In Probabilistic Inference
Paul Rolland · Ali Kavis · Alexander Niklaus Immer · Adish Singla · Volkan Cevher
[ Slides]  [ Video] 
Oral
Wed Jun 12 04:30 PM -- 04:35 PM (PDT) @ Room 201
Bayesian Generative Active Deep Learning
In Active Learning
Toan Tran · Thanh-Toan Do · Ian Reid · Gustavo Carneiro
Oral
Wed Jun 12 04:30 PM -- 04:35 PM (PDT) @ Hall B
Hierarchical Decompositional Mixtures of Variational Autoencoders
In Generative Models
Ping Liang Tan · Robert Peharz
[ Slides]  [ Video] 
Oral
Wed Jun 12 04:30 PM -- 04:35 PM (PDT) @ Grand Ballroom
Minimal Achievable Sufficient Statistic Learning
In Representation Learning
Milan Cvitkovic · Günther Koliander
[ Slides]  [ Video] 
Oral
Wed Jun 12 04:30 PM -- 04:35 PM (PDT) @ Room 104
Hessian Aided Policy Gradient
In Reinforcement Learning Theory
Zebang Shen · Alejandro Ribeiro · Hamed Hassani · Hui Qian · Chao Mi
[ Slides]  [ Video] 
Oral
Wed Jun 12 04:30 PM -- 04:35 PM (PDT) @ Room 103
Estimate Sequences for Variance-Reduced Stochastic Composite Optimization
In Convex Optimization
Andrei Kulunchakov · Julien Mairal
[ Slides]  [ Video] 
Oral
Wed Jun 12 04:35 PM -- 04:40 PM (PDT) @ Hall A
Differentiable Dynamic Normalization for Learning Deep Representation
In Deep Learning Algorithms
Ping Luo · Peng Zhanglin · Shao Wenqi · Zhang ruimao · Ren jiamin · Wu lingyun
[ Slides]  [ Video] 
Oral
Wed Jun 12 04:35 PM -- 04:40 PM (PDT) @ Room 101
The Variational Predictive Natural Gradient
In Probabilistic Inference
Da Tang · Rajesh Ranganath
[ Slides]  [ Video] 
Oral
Wed Jun 12 04:35 PM -- 04:40 PM (PDT) @ Room 103
A Dynamical Systems Perspective on Nesterov Acceleration
In Convex Optimization
Michael Muehlebach · Michael Jordan
[ Slides]  [ Video] 
Oral
Wed Jun 12 04:35 PM -- 04:40 PM (PDT) @ Room 102
Disentangled Graph Convolutional Networks
In Networks and Relational Learning
Jianxin Ma · Peng Cui · Kun Kuang · Xin Wang · Wenwu Zhu
[ Slides]  [ Video] 
Oral
Wed Jun 12 04:35 PM -- 04:40 PM (PDT) @ Room 201
Active Learning for Probabilistic Structured Prediction of Cuts and Matchings
In Active Learning
Sima Behpour · Anqi Liu · Brian Ziebart
[ Slides]  [ Video] 
Oral
Wed Jun 12 04:35 PM -- 04:40 PM (PDT) @ Seaside Ballroom
Fairwashing: the risk of rationalization
In Robust Statistics and Interpretability
Ulrich AIVODJI · Hiromi Arai · Olivier Fortineau · Sébastien Gambs · Satoshi Hara · Alain Tapp
[ Slides]  [ Video] 
Oral
Wed Jun 12 04:35 PM -- 04:40 PM (PDT) @ Grand Ballroom
Learning to Route in Similarity Graphs
In Representation Learning
Dmitry Baranchuk · Dmitry Persiyanov · Anton Sinitsin · Artem Babenko
[ Slides]  [ Video] 
Oral
Wed Jun 12 04:35 PM -- 04:40 PM (PDT) @ Room 104
Provably Efficient Maximum Entropy Exploration
In Reinforcement Learning Theory
Elad Hazan · Sham Kakade · Karan Singh · Abby Van Soest
[ Slides]  [ Video] 
Oral
Wed Jun 12 04:35 PM -- 04:40 PM (PDT) @ Hall B
Finding Mixed Nash Equilibria of Generative Adversarial Networks
In Generative Models
Ya-Ping Hsieh · Chen Liu · Volkan Cevher
[ Slides]  [ Video] 
Oral
Wed Jun 12 04:40 PM -- 05:00 PM (PDT) @ Room 201
Active Learning with Disagreement Graphs
In Active Learning
Corinna Cortes · Giulia DeSalvo · Mehryar Mohri · Ningshan Zhang · Claudio Gentile
[ Slides]  [ Video] 
Oral
Wed Jun 12 04:40 PM -- 05:00 PM (PDT) @ Hall A
Toward Understanding the Importance of Noise in Training Neural Networks
In Deep Learning Algorithms
Mo Zhou · Tianyi Liu · Yan Li · Dachao Lin · Enlu Zhou · Tuo Zhao
[ Slides]  [ Video] 
Oral
Wed Jun 12 04:40 PM -- 05:00 PM (PDT) @ Hall B
CompILE: Compositional Imitation Learning and Execution
In Generative Models
Thomas Kipf · Yujia Li · Hanjun Dai · Vinicius Zambaldi · Alvaro Sanchez-Gonzalez · Edward Grefenstette · Pushmeet Kohli · Peter Battaglia
[ Video] 
Oral
Wed Jun 12 04:40 PM -- 05:00 PM (PDT) @ Room 104
Combining parametric and nonparametric models for off-policy evaluation
In Reinforcement Learning Theory
Omer Gottesman · Yao Liu · Scott Sussex · Emma Brunskill · Finale Doshi-Velez
[ Slides]  [ Video] 
Oral
Wed Jun 12 04:40 PM -- 05:00 PM (PDT) @ Grand Ballroom
Invariant-Equivariant Representation Learning for Multi-Class Data
In Representation Learning
Ilya Feige
[ Slides]  [ Video] 
Oral
Wed Jun 12 04:40 PM -- 05:00 PM (PDT) @ Room 101
Scalable Nonparametric Sampling from Multimodal Posteriors with the Posterior Bootstrap
In Probabilistic Inference
Edwin Fong · Simon Lyddon · Christopher Holmes
[ Slides]  [ Video] 
Oral
Wed Jun 12 04:40 PM -- 05:00 PM (PDT) @ Room 103
Random Shuffling Beats SGD after Finite Epochs
In Convex Optimization
Jeff HaoChen · Suvrit Sra
[ Slides]  [ Video] 
Oral
Wed Jun 12 04:40 PM -- 05:00 PM (PDT) @ Room 102
Open Vocabulary Learning on Source Code with a Graph-Structured Cache
In Networks and Relational Learning
Milan Cvitkovic · Badal Singh · Anima Anandkumar
[ Slides]  [ Video] 
Oral
Wed Jun 12 04:40 PM -- 05:00 PM (PDT) @ Seaside Ballroom
Understanding the Origins of Bias in Word Embeddings
In Robust Statistics and Interpretability
Marc-Etienne Brunet · Colleen Alkalay-Houlihan · Ashton Anderson · Richard Zemel
[ Video] 
Oral
Wed Jun 12 05:00 PM -- 05:05 PM (PDT) @ Seaside Ballroom
Bias Also Matters: Bias Attribution for Deep Neural Network Explanation
In Robust Statistics and Interpretability
Shengjie Wang · Tianyi Zhou · Jeff Bilmes
[ Slides]  [ Video] 
Oral
Wed Jun 12 05:00 PM -- 05:05 PM (PDT) @ Room 104
Sample-Optimal Parametric Q-Learning Using Linearly Additive Features
In Reinforcement Learning Theory
Lin Yang · Mengdi Wang
[ Slides]  [ Video] 
Oral
Wed Jun 12 05:00 PM -- 05:05 PM (PDT) @ Hall A
Cheap Orthogonal Constraints in Neural Networks: A Simple Parametrization of the Orthogonal and Unitary Group
In Deep Learning Algorithms
Mario Lezcano Casado · David Martínez-Rubio
[ Slides]  [ Video] 
Oral
Wed Jun 12 05:00 PM -- 05:05 PM (PDT) @ Hall B
Sparse Multi-Channel Variational Autoencoder for the Joint Analysis of Heterogeneous Data
In Generative Models
Luigi Antelmi · Nicholas Ayache · Philippe Robert · Marco Lorenzi
[ Slides]  [ Video] 
Oral
Wed Jun 12 05:00 PM -- 05:05 PM (PDT) @ Room 102
Learning Discrete Structures for Graph Neural Networks
In Networks and Relational Learning
Luca Franceschi · Mathias Niepert · Massimiliano Pontil · Xiao He
[ Slides]  [ Video] 
Oral
Wed Jun 12 05:00 PM -- 05:05 PM (PDT) @ Room 201
Multi-Frequency Vector Diffusion Maps
In Active Learning
Yifeng Fan · Zhizhen Zhao
[ Slides]  [ Video] 
Oral
Wed Jun 12 05:00 PM -- 05:05 PM (PDT) @ Room 101
An Instability in Variational Inference for Topic Models
In Probabilistic Inference
Behrooz Ghorbani · Hamidreza Hakim Javadi · Andrea Montanari
[ Slides]  [ Video] 
Oral
Wed Jun 12 05:00 PM -- 05:05 PM (PDT) @ Grand Ballroom
Infinite Mixture Prototypes for Few-shot Learning
In Representation Learning
Kelsey Allen · Evan Shelhamer · Hanul Shin · Josh Tenenbaum
[ Slides]  [ Video] 
Oral
Wed Jun 12 05:00 PM -- 05:05 PM (PDT) @ Room 103
First-Order Algorithms Converge Faster than $O(1/k)$ on Convex Problems
In Convex Optimization
Ching-pei Lee · Stephen Wright
[ Slides]  [ Video] 
Oral
Wed Jun 12 05:05 PM -- 05:10 PM (PDT) @ Hall A
Breaking Inter-Layer Co-Adaptation by Classifier Anonymization
In Deep Learning Algorithms
Ikuro Sato · Kohta Ishikawa · Guoqing Liu · Masayuki Tanaka
Oral
Wed Jun 12 05:05 PM -- 05:10 PM (PDT) @ Hall B
Deep Generative Learning via Variational Gradient Flow
In Generative Models
Yuan Gao · Yuling Jiao · Yang Wang · Yao Wang · Can Yang · Shunkang Zhang
[ Slides]  [ Video] 
Oral
Wed Jun 12 05:05 PM -- 05:10 PM (PDT) @ Seaside Ballroom
Interpreting Adversarially Trained Convolutional Neural Networks
In Robust Statistics and Interpretability
Tianyuan Zhang · Zhanxing Zhu
[ Slides]  [ Video] 
Oral
Wed Jun 12 05:05 PM -- 05:10 PM (PDT) @ Room 101
Bayesian Optimization of Composite Functions
In Probabilistic Inference
Raul Astudillo · Peter I Frazier
[ Slides]  [ Video] 
Oral
Wed Jun 12 05:05 PM -- 05:10 PM (PDT) @ Room 102
Compositional Fairness Constraints for Graph Embeddings
In Networks and Relational Learning
Avishek Bose · William Hamilton
[ Slides]  [ Video] 
Oral
Wed Jun 12 05:05 PM -- 05:10 PM (PDT) @ Room 104
Transfer of Samples in Policy Search via Multiple Importance Sampling
In Reinforcement Learning Theory
Andrea Tirinzoni · Mattia Salvini · Marcello Restelli
[ Slides]  [ Video] 
Oral
Wed Jun 12 05:05 PM -- 05:10 PM (PDT) @ Grand Ballroom
MixHop: Higher-Order Graph Convolutional Architectures via Sparsified Neighborhood Mixing
In Representation Learning
Sami Abu-El-Haija · Bryan Perozzi · Amol Kapoor · Nazanin Alipourfard · Kristina Lerman · Hrayr Harutyunyan · Greg Ver Steeg · Aram Galstyan
[ Slides]  [ Video] 
Oral
Wed Jun 12 05:05 PM -- 05:10 PM (PDT) @ Room 201
Co-manifold learning with missing data
In Active Learning
Gal Mishne · Eric Chi · Ronald Coifman
[ Slides]  [ Video] 
Oral
Wed Jun 12 05:05 PM -- 05:10 PM (PDT) @ Room 103
Improved Convergence for $\ell_1$ and $\ell_\infty$ Regression via Iteratively Reweighted Least Squares
In Convex Optimization
Alina Ene · Adrian Vladu
[ Slides]  [ Video] 
Oral
Wed Jun 12 05:10 PM -- 05:15 PM (PDT) @ Room 101
The Kernel Interaction Trick: Fast Bayesian Discovery of Pairwise Interactions in High Dimensions
In Probabilistic Inference
Raj Agrawal · Brian Trippe · Jonathan Huggins · Tamara Broderick
[ Slides]  [ Video] 
Oral
Wed Jun 12 05:10 PM -- 05:15 PM (PDT) @ Hall B
Flow++: Improving Flow-Based Generative Models with Variational Dequantization and Architecture Design
In Generative Models
Jonathan Ho · Peter Chen · Aravind Srinivas · Rocky Duan · Pieter Abbeel
[ Slides]  [ Video] 
Oral
Wed Jun 12 05:10 PM -- 05:15 PM (PDT) @ Room 103
Optimal Mini-Batch and Step Sizes for SAGA
In Convex Optimization
Nidham Gazagnadou · Robert Gower · Joseph Salmon
[ Slides]  [ Video] 
Oral
Wed Jun 12 05:10 PM -- 05:15 PM (PDT) @ Room 102
A Recurrent Neural Cascade-based Model for Continuous-Time Diffusion
In Networks and Relational Learning
Sylvain Lamprier
[ Slides]  [ Video] 
Oral
Wed Jun 12 05:10 PM -- 05:15 PM (PDT) @ Room 104
Exploration Conscious Reinforcement Learning Revisited
In Reinforcement Learning Theory
Lior Shani · Yonathan Efroni · Shie Mannor
[ Slides]  [ Video] 
Oral
Wed Jun 12 05:10 PM -- 05:15 PM (PDT) @ Hall A
Understanding the Impact of Entropy on Policy Optimization
In Deep Learning Algorithms
Zafarali Ahmed · Nicolas Le Roux · Mohammad Norouzi · Dale Schuurmans
[ Slides]  [ Video] 
Oral
Wed Jun 12 05:10 PM -- 05:15 PM (PDT) @ Grand Ballroom
Learn to Grow: A Continual Structure Learning Framework for Overcoming Catastrophic Forgetting
In Representation Learning
Xilai Li · Yingbo Zhou · Tianfu Wu · Richard Socher · Caiming Xiong
[ Slides]  [ Video] 
Oral
Wed Jun 12 05:10 PM -- 05:15 PM (PDT) @ Seaside Ballroom
Counterfactual Visual Explanations
In Robust Statistics and Interpretability
Yash Goyal · Ziyan Wu · Jan Ernst · Dhruv Batra · Devi Parikh · Stefan Lee
[ Slides]  [ Video] 
Oral
Wed Jun 12 05:15 PM -- 05:20 PM (PDT) @ Room 104
Kernel-Based Reinforcement Learning in Robust Markov Decision Processes
In Reinforcement Learning Theory
Shiau Hong Lim · Arnaud Autef
[ Slides]  [ Video] 
Oral
Wed Jun 12 05:15 PM -- 05:20 PM (PDT) @ Room 101
Quantile Stein Variational Gradient Descent for Batch Bayesian Optimization
In Probabilistic Inference
Chengyue Gong · Jian Peng · Qiang Liu
[ Slides]  [ Video] 
Oral
Wed Jun 12 05:15 PM -- 05:20 PM (PDT) @ Seaside Ballroom
Data Poisoning Attacks on Stochastic Bandits
In Robust Statistics and Interpretability
Fang Liu · Ness Shroff
[ Slides]  [ Video] 
Oral
Wed Jun 12 05:15 PM -- 05:20 PM (PDT) @ Hall B
Learning Neurosymbolic Generative Models via Program Synthesis
In Generative Models
Halley R Young · Osbert Bastani · Mayur Naik
[ Slides]  [ Video] 
Oral
Wed Jun 12 05:15 PM -- 05:20 PM (PDT) @ Hall A
Probability Functional Descent: A Unifying Perspective on GANs, Variational Inference, and Reinforcement Learning
In Deep Learning Algorithms
Casey Chu · Jose Blanchet · Peter Glynn
[ Slides]  [ Video] 
Oral
Wed Jun 12 05:15 PM -- 05:20 PM (PDT) @ Room 103
Differential Inclusions for Modeling Nonsmooth ADMM Variants: A Continuous Limit Theory
In Convex Optimization
Huizhuo Yuan · Yuren Zhou · Chris Junchi Li · Qingyun Sun
[ Slides]  [ Video] 
Oral
Wed Jun 12 05:15 PM -- 05:20 PM (PDT) @ Room 102
Stochastic Blockmodels meet Graph Neural Networks
In Networks and Relational Learning
Nikhil Mehta · Lawrence Carin · Piyush Rai
[ Slides]  [ Video] 
Break
Wed Jun 12 05:30 PM -- 06:00 PM (PDT)
Light Evening Snack
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #1
Sum-of-Squares Polynomial Flow
In Posters Wed
Priyank Jaini · Kira A. Selby · Yaoliang Yu
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #2
FloWaveNet : A Generative Flow for Raw Audio
In Posters Wed
Sungwon Kim · Sang-gil Lee · Jongyoon Song · Jaehyeon Kim · Sungroh Yoon
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #3
Are Generative Classifiers More Robust to Adversarial Attacks?
In Posters Wed
Yingzhen Li · John Bradshaw · Yash Sharma
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #4
A Gradual, Semi-Discrete Approach to Generative Network Training via Explicit Wasserstein Minimization
In Posters Wed
Yucheng Chen · Matus Telgarsky · Chao Zhang · Bolton Bailey · Daniel Hsu · Jian Peng
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #5
Disentangling Disentanglement in Variational Autoencoders
In Posters Wed
Emile Mathieu · Tom Rainforth · N Siddharth · Yee-Whye Teh
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #6
EDDI: Efficient Dynamic Discovery of High-Value Information with Partial VAE
In Posters Wed
Chao Ma · Sebastian Tschiatschek · Konstantina Palla · Jose Miguel Hernandez-Lobato · Sebastian Nowozin · Cheng Zhang
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #7
A Wrapped Normal Distribution on Hyperbolic Space for Gradient-Based Learning
In Posters Wed
Yoshihiro Nagano · Shoichiro Yamaguchi · Yasuhiro Fujita · Masanori Koyama
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #8
Emerging Convolutions for Generative Normalizing Flows
In Posters Wed
Emiel Hoogeboom · Rianne Van den Berg · Max Welling
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #9
A Large-Scale Study on Regularization and Normalization in GANs
In Posters Wed
Karol Kurach · Mario Lucic · Xiaohua Zhai · Marcin Michalski · Sylvain Gelly
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #10
Variational Annealing of GANs: A Langevin Perspective
In Posters Wed
Chenyang Tao · Shuyang Dai · Liqun Chen · Ke Bai · Junya Chen · Chang Liu · RUIYI (ROY) ZHANG · Georgiy Bobashev · Lawrence Carin
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #11
Invertible Residual Networks
In Posters Wed
Jens Behrmann · Will Grathwohl · Ricky T. Q. Chen · David Duvenaud · Joern-Henrik Jacobsen
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #12
NAS-Bench-101: Towards Reproducible Neural Architecture Search
In Posters Wed
Chris Ying · Aaron Klein · Eric Christiansen · Esteban Real · Kevin Murphy · Frank Hutter
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #13
Approximated Oracle Filter Pruning for Destructive CNN Width Optimization
In Posters Wed
XIAOHAN DING · guiguang ding · Yuchen Guo · Jungong Han · Chenggang Yan
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #14
LegoNet: Efficient Convolutional Neural Networks with Lego Filters
In Posters Wed
Zhaohui Yang · Yunhe Wang · Chuanjian Liu · Hanting Chen · Chunjing Xu · Boxin Shi · Chao Xu · Chang Xu
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #15
Sorting Out Lipschitz Function Approximation
In Posters Wed
Cem Anil · James Lucas · Roger Grosse
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #16
Graph Element Networks: adaptive, structured computation and memory
In Posters Wed
Ferran Alet · Adarsh Keshav Jeewajee · Maria Bauza Villalonga · Alberto Rodriguez · Tomas Lozano-Perez · Leslie Kaelbling
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #17
Training CNNs with Selective Allocation of Channels
In Posters Wed
Jongheon Jeong · Jinwoo Shin
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #18
Equivariant Transformer Networks
In Posters Wed
Kai Sheng Tai · Peter Bailis · Gregory Valiant
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #19
Overcoming Multi-model Forgetting
In Posters Wed
Yassine Benyahia · Kaicheng Yu · Kamil Bennani-Smires · Martin Jaggi · Anthony C. Davison · Mathieu Salzmann · Claudiu Musat
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #20
Bayesian Nonparametric Federated Learning of Neural Networks
In Posters Wed
Mikhail Yurochkin · Mayank Agarwal · Soumya Ghosh · Kristjan Greenewald · Nghia Hoang · Yasaman Khazaeni
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #21
How does Disagreement Help Generalization against Label Corruption?
In Posters Wed
Xingrui Yu · Bo Han · Jiangchao Yao · Gang Niu · Ivor Tsang · Masashi Sugiyama
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #22
EigenDamage: Structured Pruning in the Kronecker-Factored Eigenbasis
In Posters Wed
Chaoqi Wang · Roger Grosse · Sanja Fidler · Guodong Zhang
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #23
Addressing the Loss-Metric Mismatch with Adaptive Loss Alignment
In Posters Wed
Chen Huang · Shuangfei Zhai · Walter Talbott · Miguel Angel Bautista Martin · Shih-Yu Sun · Carlos Guestrin · Joshua M Susskind
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #24
Deep Compressed Sensing
In Posters Wed
Yan Wu · Mihaela Rosca · Timothy Lillicrap
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #25
Differentiable Dynamic Normalization for Learning Deep Representation
In Posters Wed
Ping Luo · Peng Zhanglin · Shao Wenqi · Zhang ruimao · Ren jiamin · Wu lingyun
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #26
Toward Understanding the Importance of Noise in Training Neural Networks
In Posters Wed
Mo Zhou · Tianyi Liu · Yan Li · Dachao Lin · Enlu Zhou · Tuo Zhao
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #27
Cheap Orthogonal Constraints in Neural Networks: A Simple Parametrization of the Orthogonal and Unitary Group
In Posters Wed
Mario Lezcano Casado · David Martínez-Rubio
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #28
Breaking Inter-Layer Co-Adaptation by Classifier Anonymization
In Posters Wed
Ikuro Sato · Kohta Ishikawa · Guoqing Liu · Masayuki Tanaka
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #29
Understanding the Impact of Entropy on Policy Optimization
In Posters Wed
Zafarali Ahmed · Nicolas Le Roux · Mohammad Norouzi · Dale Schuurmans
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #30
Probability Functional Descent: A Unifying Perspective on GANs, Variational Inference, and Reinforcement Learning
In Posters Wed
Casey Chu · Jose Blanchet · Peter Glynn
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #31
Social Influence as Intrinsic Motivation for Multi-Agent Deep Reinforcement Learning
In Posters Wed
Natasha Jaques · Angeliki Lazaridou · Edward Hughes · Caglar Gulcehre · Pedro Ortega · DJ Strouse · Joel Z Leibo · Nando de Freitas
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #32
Maximum Entropy-Regularized Multi-Goal Reinforcement Learning
In Posters Wed
Rui Zhao · Xudong Sun · Volker Tresp
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #33
Imitating Latent Policies from Observation
In Posters Wed
Ashley Edwards · Himanshu Sahni · Yannick Schroecker · Charles Isbell
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #34
SOLAR: Deep Structured Representations for Model-Based Reinforcement Learning
In Posters Wed
Marvin Zhang · Sharad Vikram · Laura Smith · Pieter Abbeel · Matthew Johnson · Sergey Levine
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #35
Dimension-Wise Importance Sampling Weight Clipping for Sample-Efficient Reinforcement Learning
In Posters Wed
Seungyul Han · Youngchul Sung
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #36
Structured agents for physical construction
In Posters Wed
Victor Bapst · Alvaro Sanchez-Gonzalez · Carl Doersch · Kimberly Stachenfeld · Pushmeet Kohli · Peter Battaglia · Jessica Hamrick
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #37
Learning Novel Policies For Tasks
In Posters Wed
Yunbo Zhang · Wenhao Yu · Greg Turk
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #38
Taming MAML: Efficient unbiased meta-reinforcement learning
In Posters Wed
Hao Liu · Richard Socher · Caiming Xiong
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #39
Self-Supervised Exploration via Disagreement
In Posters Wed
Deepak Pathak · Dhiraj Gandhi · Abhinav Gupta
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #40
Efficient Off-Policy Meta-Reinforcement Learning via Probabilistic Context Variables
In Posters Wed
Kate Rakelly · Aurick Zhou · Chelsea Finn · Sergey Levine · Deirdre Quillen
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #41
The Natural Language of Actions
In Posters Wed
Guy Tennenholtz · Shie Mannor
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #42
Control Regularization for Reduced Variance Reinforcement Learning
In Posters Wed
Richard Cheng · Abhinav Verma · Gabor Orosz · Swarat Chaudhuri · Yisong Yue · Joel Burdick
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #43
On the Generalization Gap in Reparameterizable Reinforcement Learning
In Posters Wed
Huan Wang · Stephan Zheng · Caiming Xiong · Richard Socher
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #44
Trajectory-Based Off-Policy Deep Reinforcement Learning
In Posters Wed
Andreas Doerr · Michael Volpp · Marc Toussaint · Sebastian Trimpe · Christian Daniel
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #45
A Deep Reinforcement Learning Perspective on Internet Congestion Control
In Posters Wed
Nathan Jay · Noga H. Rotman · Brighten Godfrey · Michael Schapira · Aviv Tamar
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #46
Model-Based Active Exploration
In Posters Wed
Pranav Shyam · Wojciech Jaśkowski · Faustino Gomez
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #47
Extrapolating Beyond Suboptimal Demonstrations via Inverse Reinforcement Learning from Observations
In Posters Wed
Daniel Brown · Wonjoon Goo · Prabhat Nagarajan · Scott Niekum
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #48
Distributional Multivariate Policy Evaluation and Exploration with the Bellman GAN
In Posters Wed
dror freirich · Tzahi Shimkin · Ron Meir · Aviv Tamar
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #49
A Baseline for Any Order Gradient Estimation in Stochastic Computation Graphs
In Posters Wed
Jingkai Mao · Jakob Foerster · Tim Rocktäschel · Maruan Al-Shedivat · Gregory Farquhar · Shimon Whiteson
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #50
Remember and Forget for Experience Replay
In Posters Wed
Guido Novati · Petros Koumoutsakos
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #51
Tensor Variable Elimination for Plated Factor Graphs
In Posters Wed
Fritz Obermeyer · Elias Bingham · Martin Jankowiak · Neeraj Pradhan · Justin Chiu · Alexander Rush · Noah Goodman
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #52
Predicate Exchange: Inference with Declarative Knowledge
In Posters Wed
Zenna Tavares · Javier Burroni · Edgar Minasyan · Armando Solar-Lezama · Rajesh Ranganath
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #53
Discriminative Regularization for Latent Variable Models with Applications to Electrocardiography
In Posters Wed
Andrew Miller · Ziad Obermeyer · John Cunningham · Sendhil Mullainathan
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #54
Hierarchical Decompositional Mixtures of Variational Autoencoders
In Posters Wed
Ping Liang Tan · Robert Peharz
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #55
Finding Mixed Nash Equilibria of Generative Adversarial Networks
In Posters Wed
Ya-Ping Hsieh · Chen Liu · Volkan Cevher
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #56
CompILE: Compositional Imitation Learning and Execution
In Posters Wed
Thomas Kipf · Yujia Li · Hanjun Dai · Vinicius Zambaldi · Alvaro Sanchez-Gonzalez · Edward Grefenstette · Pushmeet Kohli · Peter Battaglia
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #57
Sparse Multi-Channel Variational Autoencoder for the Joint Analysis of Heterogeneous Data
In Posters Wed
Luigi Antelmi · Nicholas Ayache · Philippe Robert · Marco Lorenzi
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #58
Deep Generative Learning via Variational Gradient Flow
In Posters Wed
Yuan Gao · Yuling Jiao · Yang Wang · Yao Wang · Can Yang · Shunkang Zhang
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #59
Flow++: Improving Flow-Based Generative Models with Variational Dequantization and Architecture Design
In Posters Wed
Jonathan Ho · Peter Chen · Aravind Srinivas · Rocky Duan · Pieter Abbeel
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #60
Learning Neurosymbolic Generative Models via Program Synthesis
In Posters Wed
Halley R Young · Osbert Bastani · Mayur Naik
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #61
Theoretically Principled Trade-off between Robustness and Accuracy
In Posters Wed
Hongyang Zhang · Yaodong Yu · Jiantao Jiao · Eric Xing · Laurent El Ghaoui · Michael Jordan
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #62
The Odds are Odd: A Statistical Test for Detecting Adversarial Examples
In Posters Wed
Kevin Roth · Yannic Kilcher · Thomas Hofmann
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #63
ME-Net: Towards Effective Adversarial Robustness with Matrix Estimation
In Posters Wed
Yuzhe Yang · GUO ZHANG · Zhi Xu · Dina Katabi
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #64
Certified Adversarial Robustness via Randomized Smoothing
In Posters Wed
Jeremy Cohen · Elan Rosenfeld · Zico Kolter
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #65
Imperceptible, Robust, and Targeted Adversarial Examples for Automatic Speech Recognition
In Posters Wed
Yao Qin · Nicholas Carlini · Garrison Cottrell · Ian Goodfellow · Colin Raffel
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #66
Parsimonious Black-Box Adversarial Attacks via Efficient Combinatorial Optimization
In Posters Wed
Seungyong Moon · Gaon An · Hyun Oh Song
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #67
Wasserstein Adversarial Examples via Projected Sinkhorn Iterations
In Posters Wed
Eric Wong · Frank R Schmidt · Zico Kolter
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #68
Transferable Clean-Label Poisoning Attacks on Deep Neural Nets
In Posters Wed
Chen Zhu · W. Ronny Huang · Hengduo Li · Gavin Taylor · Christoph Studer · Tom Goldstein
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #69
NATTACK: Learning the Distributions of Adversarial Examples for an Improved Black-Box Attack on Deep Neural Networks
In Posters Wed
Yandong li · Lijun Li · Liqiang Wang · Tong Zhang · Boqing Gong
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #70
Simple Black-box Adversarial Attacks
In Posters Wed
Chuan Guo · Jacob Gardner · Yurong You · Andrew Wilson · Kilian Weinberger
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #71
Causal Identification under Markov Equivalence: Completeness Results
In Posters Wed
Amin Jaber · Jiji Zhang · Elias Bareinboim
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #72
Counterfactual Off-Policy Evaluation with Gumbel-Max Structural Causal Models
In Posters Wed
Michael Oberst · David Sontag
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #73
Causal Discovery and Forecasting in Nonstationary Environments with State-Space Models
In Posters Wed
Biwei Huang · Kun Zhang · Mingming Gong · Clark Glymour
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #74
Classifying Treatment Responders Under Causal Effect Monotonicity
In Posters Wed
Nathan Kallus
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #75
Learning Models from Data with Measurement Error: Tackling Underreporting
In Posters Wed
Roy Adams · Yuelong Ji · Xiaobin Wang · Suchi Saria
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #76
Adjustment Criteria for Generalizing Experimental Findings
In Posters Wed
Juan Correa · Jin Tian · Elias Bareinboim
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #77
Conditional Independence in Testing Bayesian Networks
In Posters Wed
Yujia Shen · Haiying Huang · Arthur Choi · Adnan Darwiche
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #78
Sensitivity Analysis of Linear Structural Causal Models
In Posters Wed
Carlos Cinelli · Daniel Kumor · Bryant Chen · Judea Pearl · Elias Bareinboim
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #79
More Efficient Off-Policy Evaluation through Regularized Targeted Learning
In Posters Wed
Aurelien Bibaut · Ivana Malenica · Nikos Vlassis · Mark van der Laan
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #80
Inferring Heterogeneous Causal Effects in Presence of Spatial Confounding
In Posters Wed
Muhammad Osama · Dave Zachariah · Thomas Schön
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #81
Adversarially Learned Representations for Information Obfuscation and Inference
In Posters Wed
Martin A Bertran · Natalia Martinez Gil · Afroditi Papadaki · Qiang Qiu · Miguel Rodrigues · Galen Reeves · Guillermo Sapiro
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #82
Adaptive Neural Trees
In Posters Wed
Ryutaro Tanno · Kai Arulkumaran · Daniel Alexander · Antonio Criminisi · Aditya Nori
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #83
Connectivity-Optimized Representation Learning via Persistent Homology
In Posters Wed
Christoph Hofer · Roland Kwitt · Marc Niethammer · Mandar Dixit
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #84
Minimal Achievable Sufficient Statistic Learning
In Posters Wed
Milan Cvitkovic · Günther Koliander
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #85
Learning to Route in Similarity Graphs
In Posters Wed
Dmitry Baranchuk · Dmitry Persiyanov · Anton Sinitsin · Artem Babenko
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #86
Invariant-Equivariant Representation Learning for Multi-Class Data
In Posters Wed
Ilya Feige
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #87
Infinite Mixture Prototypes for Few-shot Learning
In Posters Wed
Kelsey Allen · Evan Shelhamer · Hanul Shin · Josh Tenenbaum
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #88
MixHop: Higher-Order Graph Convolutional Architectures via Sparsified Neighborhood Mixing
In Posters Wed
Sami Abu-El-Haija · Bryan Perozzi · Amol Kapoor · Nazanin Alipourfard · Kristina Lerman · Hrayr Harutyunyan · Greg Ver Steeg · Aram Galstyan
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #89
Learn to Grow: A Continual Structure Learning Framework for Overcoming Catastrophic Forgetting
In Posters Wed
Xilai Li · Yingbo Zhou · Tianfu Wu · Richard Socher · Caiming Xiong
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #90
Exploration Conscious Reinforcement Learning Revisited
In Posters Wed
Lior Shani · Yonathan Efroni · Shie Mannor
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #91
Complexity of Linear Regions in Deep Networks
In Posters Wed
Boris Hanin · David Rolnick
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #92
On Connected Sublevel Sets in Deep Learning
In Posters Wed
Quynh Nguyen
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #93
Adversarial Examples Are a Natural Consequence of Test Error in Noise
In Posters Wed
Justin Gilmer · Nicolas Ford · Nicholas Carlini · Ekin Dogus Cubuk
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #94
Greedy Layerwise Learning Can Scale To ImageNet
In Posters Wed
Eugene Belilovsky · Michael Eickenberg · Edouard Oyallon
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #95
On the Impact of the Activation function on Deep Neural Networks Training
In Posters Wed
Soufiane Hayou · Arnaud Doucet · Judith Rousseau
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #96
Estimating Information Flow in Deep Neural Networks
In Posters Wed
Ziv Goldfeld · Ewout van den Berg · Kristjan Greenewald · Igor Melnyk · Nam Nguyen · Brian Kingsbury · Yury Polyanskiy
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #97
The Anisotropic Noise in Stochastic Gradient Descent: Its Behavior of Escaping from Sharp Minima and Regularization Effects
In Posters Wed
Zhanxing Zhu · Jingfeng Wu · Bing Yu · Lei Wu · Jinwen Ma
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #98
Characterizing Well-Behaved vs. Pathological Deep Neural Networks
In Posters Wed
Antoine Labatie
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #99
Understanding Geometry of Encoder-Decoder CNNs
In Posters Wed
Jong Chul Ye · woonkyoung Sung
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #100
Traditional and Heavy Tailed Self Regularization in Neural Network Models
In Posters Wed
Michael Mahoney · Charles H Martin
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #101
Almost surely constrained convex optimization
In Posters Wed
Olivier Fercoq · Ahmet Alacaoglu · Ion Necoara · Volkan Cevher
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #102
Generalized Majorization-Minimization
In Posters Wed
Sobhan Naderi Parizi · Kun He · Reza Aghajani · Stan Sclaroff · Pedro Felzenszwalb
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #103
On the Computation and Communication Complexity of Parallel SGD with Dynamic Batch Sizes for Stochastic Non-Convex Optimization
In Posters Wed
Hao Yu · rong jin
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #104
Simple Stochastic Gradient Methods for Non-Smooth Non-Convex Regularized Optimization
In Posters Wed
Michael Metel · Akiko Takeda
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #105
Surrogate Losses for Online Learning of Stepsizes in Stochastic Non-Convex Optimization
In Posters Wed
zhenxun zhuang · Ashok Cutkosky · Francesco Orabona
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #106
Efficient Dictionary Learning with Gradient Descent
In Posters Wed
Dar Gilboa · Sam Buchanan · John Wright
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #107
Plug-and-Play Methods Provably Converge with Properly Trained Denoisers
In Posters Wed
Ernest Ryu · Jialin Liu · Sicheng Wang · Xiaohan Chen · Zhangyang Wang · Wotao Yin
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #108
Riemannian adaptive stochastic gradient algorithms on matrix manifolds
In Posters Wed
Hiroyuki Kasai · Pratik Kumar Jawanpuria · Bamdev Mishra
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #109
Stochastic Optimization for DC Functions and Non-smooth Non-convex Regularizers with Non-asymptotic Convergence
In Posters Wed
Yi Xu · Qi Qi · Qihang Lin · rong jin · Tianbao Yang
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #110
Alternating Minimizations Converge to Second-Order Optimal Solutions
In Posters Wed
Qiuwei Li · Zhihui Zhu · Gongguo Tang
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #111
Provably Efficient Imitation Learning from Observation Alone
In Posters Wed
Wen Sun · Anirudh Vemula · Byron Boots · Drew Bagnell
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #112
Dead-ends and Secure Exploration in Reinforcement Learning
In Posters Wed
Mehdi Fatemi · Shikhar Sharma · Harm van Seijen · Samira Ebrahimi Kahou
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #113
Statistics and Samples in Distributional Reinforcement Learning
In Posters Wed
Mark Rowland · Robert Dadashi · Saurabh Kumar · Remi Munos · Marc Bellemare · Will Dabney
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #114
Hessian Aided Policy Gradient
In Posters Wed
Zebang Shen · Alejandro Ribeiro · Hamed Hassani · Hui Qian · Chao Mi
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #115
Provably Efficient Maximum Entropy Exploration
In Posters Wed
Elad Hazan · Sham Kakade · Karan Singh · Abby Van Soest
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #116
Combining parametric and nonparametric models for off-policy evaluation
In Posters Wed
Omer Gottesman · Yao Liu · Scott Sussex · Emma Brunskill · Finale Doshi-Velez
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #117
Sample-Optimal Parametric Q-Learning Using Linearly Additive Features
In Posters Wed
Lin Yang · Mengdi Wang
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #118
Transfer of Samples in Policy Search via Multiple Importance Sampling
In Posters Wed
Andrea Tirinzoni · Mattia Salvini · Marcello Restelli
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #119
Action Robust Reinforcement Learning and Applications in Continuous Control
In Posters Wed
Chen Tessler · Chen Tessler · Yonathan Efroni · Shie Mannor
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #120
Kernel-Based Reinforcement Learning in Robust Markov Decision Processes
In Posters Wed
Shiau Hong Lim · Arnaud Autef
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #121
Optimal Algorithms for Lipschitz Bandits with Heavy-tailed Rewards
In Posters Wed
Shiyin Lu · Guanghui Wang · Yao Hu · Lijun Zhang
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #122
Target Tracking for Contextual Bandits: Application to Demand Side Management
In Posters Wed
Margaux Brégère · Pierre Gaillard · Yannig Goude · Gilles Stoltz
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #123
Correlated bandits or: How to minimize mean-squared error online
In Posters Wed
Vinay Praneeth Boda · Prashanth L.A.
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #124
Stay With Me: Lifetime Maximization Through Heteroscedastic Linear Bandits With Reneging
In Posters Wed
Ping-Chun Hsieh · Xi Liu · Anirban Bhattacharya · P R Kumar
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #125
Garbage In, Reward Out: Bootstrapping Exploration in Multi-Armed Bandits
In Posters Wed
Branislav Kveton · Csaba Szepesvari · Sharan Vaswani · Zheng Wen · Tor Lattimore · Mohammad Ghavamzadeh
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #126
Beating Stochastic and Adversarial Semi-bandits Optimally and Simultaneously
In Posters Wed
Julian Zimmert · Haipeng Luo · Chen-Yu Wei
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #127
Bilinear Bandits with Low-rank Structure
In Posters Wed
Kwang-Sung Jun · Rebecca Willett · Stephen Wright · Robert Nowak
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #128
Online Learning to Rank with Features
In Posters Wed
Shuai Li · Tor Lattimore · Csaba Szepesvari
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #129
On the Design of Estimators for Bandit Off-Policy Evaluation
In Posters Wed
Nikos Vlassis · Aurelien Bibaut · Maria Dimakopoulou · Tony Jebara
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #130
Dynamic Learning with Frequent New Product Launches: A Sequential Multinomial Logit Bandit Problem
In Posters Wed
Junyu Cao · Wei Sun
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #131
Context-Aware Zero-Shot Learning for Object Recognition
In Posters Wed
Eloi Zablocki · Patrick Bordes · Laure Soulier · Benjamin Piwowarski · Patrick Gallinari
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #132
Band-limited Training and Inference for Convolutional Neural Networks
In Posters Wed
Adam Dziedzic · John Paparrizos · Sanjay Krishnan · Aaron Elmore · Michael Franklin
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #133
Learning Classifiers for Target Domain with Limited or No Labels
In Posters Wed
Pengkai Zhu · Hanxiao Wang · Venkatesh Saligrama
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #134
Population Based Augmentation: Efficient Learning of Augmentation Policy Schedules
In Posters Wed
Daniel Ho · Eric Liang · Peter Chen · Ion Stoica · Pieter Abbeel
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #135
Anomaly Detection With Multiple-Hypotheses Predictions
In Posters Wed
Duc Tam Nguyen · Zhongyu Lou · Michael Klar · Thomas Brox
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #136
Kernel Mean Matching for Content Addressability of GANs
In Posters Wed
Wittawat Jitkrittum · Wittawat Jitkrittum · Patsorn Sangkloy · Muhammad Waleed Gondal · Amit Raj · James Hays · Bernhard Schölkopf
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #137
Neural Inverse Knitting: From Images to Manufacturing Instructions
In Posters Wed
Alexandre Kaspar · Tae-Hyun Oh · Liane Makatura · Petr Kellnhofer · Wojciech Matusik
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #138
Making Convolutional Networks Shift-Invariant Again
In Posters Wed
Richard Zhang
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #139
Generative Modeling of Infinite Occluded Objects for Compositional Scene Representation
In Posters Wed
Jinyang Yuan · Bin Li · Xiangyang Xue
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #140
IMEXnet - A Forward Stable Deep Neural Network
In Posters Wed
Eldad Haber · Keegan Lensink · Eran Treister · Lars Ruthotto
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #141
Do ImageNet Classifiers Generalize to ImageNet?
In Posters Wed
Benjamin Recht · Rebecca Roelofs · Ludwig Schmidt · Vaishaal Shankar
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #142
Exploring the Landscape of Spatial Robustness
In Posters Wed
Logan Engstrom · Brandon Tran · Dimitris Tsipras · Ludwig Schmidt · Aleksander Madry
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #143
Sever: A Robust Meta-Algorithm for Stochastic Optimization
In Posters Wed
Ilias Diakonikolas · Gautam Kamath · Daniel Kane · Jerry Li · Jacob Steinhardt · Alistair Stewart
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #144
Analyzing Federated Learning through an Adversarial Lens
In Posters Wed
Arjun Nitin Bhagoji · Supriyo Chakraborty · Prateek Mittal · Seraphin Calo
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #145
Fairwashing: the risk of rationalization
In Posters Wed
Ulrich AIVODJI · Hiromi Arai · Olivier Fortineau · Sébastien Gambs · Satoshi Hara · Alain Tapp
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #146
Understanding the Origins of Bias in Word Embeddings
In Posters Wed
Marc-Etienne Brunet · Colleen Alkalay-Houlihan · Ashton Anderson · Richard Zemel
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #147
Bias Also Matters: Bias Attribution for Deep Neural Network Explanation
In Posters Wed
Shengjie Wang · Tianyi Zhou · Jeff Bilmes
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #148
Interpreting Adversarially Trained Convolutional Neural Networks
In Posters Wed
Tianyuan Zhang · Zhanxing Zhu
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #149
Counterfactual Visual Explanations
In Posters Wed
Yash Goyal · Ziyan Wu · Jan Ernst · Dhruv Batra · Devi Parikh · Stefan Lee
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #150
Data Poisoning Attacks on Stochastic Bandits
In Posters Wed
Fang Liu · Ness Shroff
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #151
On the Convergence and Robustness of Adversarial Training
In Posters Wed
Yisen Wang · Xingjun Ma · James Bailey · Jinfeng Yi · Bowen Zhou · Quanquan Gu
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #152
Learning with Bad Training Data via Iterative Trimmed Loss Minimization
In Posters Wed
Yanyao Shen · Sujay Sanghavi
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #153
On discriminative learning of prediction uncertainty
In Posters Wed
Vojtech Franc · Daniel Prusa
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #154
Understanding and Utilizing Deep Neural Networks Trained with Noisy Labels
In Posters Wed
Pengfei Chen · Ben Liao · Guangyong Chen · Shengyu Zhang
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #155
Does Data Augmentation Lead to Positive Margin?
In Posters Wed
Shashank Rajput · Zhili Feng · Zachary Charles · Po-Ling Loh · Dimitris Papailiopoulos
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #156
Robust Learning from Untrusted Sources
In Posters Wed
Nikola Konstantinov · Christoph H. Lampert
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #157
SELFIE: Refurbishing Unclean Samples for Robust Deep Learning
In Posters Wed
Hwanjun Song · Minseok Kim · Jae-Gil Lee
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #158
Zeno: Distributed Stochastic Gradient Descent with Suspicion-based Fault-tolerance
In Posters Wed
Cong Xie · Sanmi Koyejo · Indranil Gupta
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #159
Concentration Inequalities for Conditional Value at Risk
In Posters Wed
Philip Thomas · Erik Learned-Miller
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #160
Data Poisoning Attacks in Multi-Party Learning
In Posters Wed
Saeed Mahloujifar · Mohammad Mahmoody · Ameer Mohammed
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #161
Distributed Weighted Matching via Randomized Composable Coresets
In Posters Wed
Sepehr Assadi · Mohammad Hossein Bateni · Vahab Mirrokni
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #162
Multivariate Submodular Optimization
In Posters Wed
Richard Santiago · F. Bruce Shepherd
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #163
Beyond Adaptive Submodularity: Approximation Guarantees of Greedy Policy with Adaptive Submodularity Ratio
In Posters Wed
Kaito Fujii · Shinsaku Sakaue
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #164
Approximating Orthogonal Matrices with Effective Givens Factorization
In Posters Wed
Thomas Frerix · Joan Bruna
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #165
New results on information theoretic clustering
In Posters Wed
Ferdinando Cicalese · Eduardo Laber · Lucas Murtinho
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #166
Improved Parallel Algorithms for Density-Based Network Clustering
In Posters Wed
Mohsen Ghaffari · Silvio Lattanzi · Slobodan Mitrović
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #167
Submodular Observation Selection and Information Gathering for Quadratic Models
In Posters Wed
Abolfazl Hashemi · Mahsa Ghasemi · Haris Vikalo · Ufuk Topcu
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #168
Submodular Cost Submodular Cover with an Approximate Oracle
In Posters Wed
Victoria Crawford · Alan Kuhnle · My T Thai
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #169
Submodular Streaming in All Its Glory: Tight Approximation, Minimum Memory and Low Adaptive Complexity
In Posters Wed
Ehsan Kazemi · Marko Mitrovic · Morteza Zadimoghaddam · Silvio Lattanzi · Amin Karbasi
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #170
Hiring Under Uncertainty
In Posters Wed
Manish Purohit · Sreenivas Gollapudi · Manish Raghavan
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #171
Position-aware Graph Neural Networks
In Posters Wed
Jiaxuan You · Rex (Zhitao) Ying · Jure Leskovec
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #172
Detecting Overlapping and Correlated Communities without Pure Nodes: Identifiability and Algorithm
In Posters Wed
Kejun Huang · Xiao Fu
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #173
Learning Generative Models across Incomparable Spaces
In Posters Wed
Charlotte Bunne · David Alvarez-Melis · Andreas Krause · Stefanie Jegelka
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #174
Relational Pooling for Graph Representations
In Posters Wed
Ryan Murphy · Balasubramaniam Srinivasan · Vinayak A Rao · Bruno Ribeiro
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #175
Disentangled Graph Convolutional Networks
In Posters Wed
Jianxin Ma · Peng Cui · Kun Kuang · Xin Wang · Wenwu Zhu
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #176
Open Vocabulary Learning on Source Code with a Graph-Structured Cache
In Posters Wed
Milan Cvitkovic · Badal Singh · Anima Anandkumar
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #177
Learning Discrete Structures for Graph Neural Networks
In Posters Wed
Luca Franceschi · Mathias Niepert · Massimiliano Pontil · Xiao He
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #178
Compositional Fairness Constraints for Graph Embeddings
In Posters Wed
Avishek Bose · William Hamilton
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #179
A Recurrent Neural Cascade-based Model for Continuous-Time Diffusion
In Posters Wed
Sylvain Lamprier
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #180
Stochastic Blockmodels meet Graph Neural Networks
In Posters Wed
Nikhil Mehta · Lawrence Carin · Piyush Rai
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #181
Distributed Learning with Sublinear Communication
In Posters Wed
Jayadev Acharya · Christopher De Sa · Dylan Foster · Karthik Sridharan
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #182
On the Linear Speedup Analysis of Communication Efficient Momentum SGD for Distributed Non-Convex Optimization
In Posters Wed
Hao Yu · rong jin · Sen Yang
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #183
Stochastic Gradient Push for Distributed Deep Learning
In Posters Wed
Mahmoud Assran · Nicolas Loizou · Nicolas Ballas · Michael Rabbat
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #184
Collective Model Fusion for Multiple Black-Box Experts
In Posters Wed
Minh Hoang · Nghia Hoang · Bryan Kian Hsiang Low · Carleton Kingsford
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #185
Trading Redundancy for Communication: Speeding up Distributed SGD for Non-convex Optimization
In Posters Wed
Farzin Haddadpour · Mohammad Mahdi Kamani · Mehrdad Mahdavi · Viveck Cadambe
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #186
Trimming the $\ell_1$ Regularizer: Statistical Analysis, Optimization, and Applications to Deep Learning
In Posters Wed
Jihun Yun · Peng Zheng · Eunho Yang · Aurelie Lozano · Aleksandr Aravkin
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #187
Compressed Factorization: Fast and Accurate Low-Rank Factorization of Compressively-Sensed Data
In Posters Wed
Vatsal Sharan · Kai Sheng Tai · Peter Bailis · Gregory Valiant
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #188
Noisy Dual Principal Component Pursuit
In Posters Wed
Tianyu Ding · Zhihui Zhu · Tianjiao Ding · Yunchen Yang · Daniel Robinson · Manolis Tsakiris · Rene Vidal
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #189
Learning a Compressed Sensing Measurement Matrix via Gradient Unrolling
In Posters Wed
Shanshan Wu · Alexandros Dimakis · Sujay Sanghavi · Felix Xinnan Yu · Daniel Holtmann-Rice · Dmitry Storcheus · Afshin Rostamizadeh · Sanjiv Kumar
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #190
Screening rules for Lasso with non-convex Sparse Regularizers
In Posters Wed
alain rakotomamonjy · Gilles Gasso · Joseph Salmon
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #191
Monge blunts Bayes: Hardness Results for Adversarial Training
In Posters Wed
Zac Cranko · Aditya Menon · Richard Nock · Cheng Soon Ong · Zhan Shi · Christian Walder
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #192
Better generalization with less data using robust gradient descent
In Posters Wed
Matthew J. Holland · Kazushi Ikeda
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #193
Near optimal finite time identification of arbitrary linear dynamical systems
In Posters Wed
Tuhin Sarkar · Alexander Rakhlin
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #194
Lossless or Quantized Boosting with Integer Arithmetic
In Posters Wed
Richard Nock · Robert C Williamson
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #195
Orthogonal Random Forest for Causal Inference
In Posters Wed
Miruna Oprescu · Vasilis Syrgkanis · Steven Wu
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #196
MONK -- Outlier-Robust Mean Embedding Estimation by Median-of-Means
In Posters Wed
Matthieu Lerasle · Zoltan Szabo · Timothée Mathieu · Guillaume Lecue
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #197
The advantages of multiple classes for reducing overfitting from test set reuse
In Posters Wed
Vitaly Feldman · Roy Frostig · Moritz Hardt
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #198
On the statistical rate of nonlinear recovery in generative models with heavy-tailed data
In Posters Wed
Xiaohan Wei · Zhuoran Yang · Zhaoran Wang
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #199
Phase transition in PCA with missing data: Reduced signal-to-noise ratio, not sample size!
In Posters Wed
Niels Ipsen · Lars Kai Hansen
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #200
On Medians of (Randomized) Pairwise Means
In Posters Wed
Stephan Clemencon · Pierre Laforgue · Patrice Bertail
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #201
Accelerated Linear Convergence of Stochastic Momentum Methods in Wasserstein Distances
In Posters Wed
Bugra Can · Mert Gurbuzbalaban · Lingjiong Zhu
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #202
SGD without Replacement: Sharper Rates for General Smooth Convex Functions
In Posters Wed
Dheeraj Nagaraj · Prateek Jain · Praneeth Netrapalli
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #203
On the Complexity of Approximating Wasserstein Barycenters
In Posters Wed
Alexey Kroshnin · Nazarii Tupitsa · Darina Dvinskikh · Pavel Dvurechenskii · Alexander Gasnikov · Cesar Uribe
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #204
Estimate Sequences for Variance-Reduced Stochastic Composite Optimization
In Posters Wed
Andrei Kulunchakov · Julien Mairal
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #205
A Dynamical Systems Perspective on Nesterov Acceleration
In Posters Wed
Michael Muehlebach · Michael Jordan
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #206
Random Shuffling Beats SGD after Finite Epochs
In Posters Wed
Jeff HaoChen · Suvrit Sra
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #207
First-Order Algorithms Converge Faster than $O(1/k)$ on Convex Problems
In Posters Wed
Ching-pei Lee · Stephen Wright
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #208
Improved Convergence for $\ell_1$ and $\ell_\infty$ Regression via Iteratively Reweighted Least Squares
In Posters Wed
Alina Ene · Adrian Vladu
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #209
Optimal Mini-Batch and Step Sizes for SAGA
In Posters Wed
Nidham Gazagnadou · Robert Gower · Joseph Salmon
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #210
Differential Inclusions for Modeling Nonsmooth ADMM Variants: A Continuous Limit Theory
In Posters Wed
Huizhuo Yuan · Yuren Zhou · Chris Junchi Li · Qingyun Sun
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #211
Distribution calibration for regression
In Posters Wed
Hao Song · Tom Diethe · Meelis Kull · Peter Flach
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #212
Graph Convolutional Gaussian Processes
In Posters Wed
Ian Walker · Ben Glocker
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #213
Asynchronous Batch Bayesian Optimisation with Improved Local Penalisation
In Posters Wed
Ahsan Alvi · Binxin Ru · Jan-Peter Calliess · Stephen Roberts · Michael A Osborne
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #214
GOODE: A Gaussian Off-The-Shelf Ordinary Differential Equation Solver
In Posters Wed
David John · Vincent Heuveline · Michael Schober
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #215
Overcoming Mean-Field Approximations in Recurrent Gaussian Process Models
In Posters Wed
Alessandro Davide Ialongo · Mark van der Wilk · James Hensman · Carl E Rasmussen
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #216
AReS and MaRS - Adversarial and MMD-Minimizing Regression for SDEs
In Posters Wed
Gabriele Abbati · Philippe Wenk · Michael A Osborne · Andreas Krause · Bernhard Schölkopf · Stefan Bauer
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #217
End-to-End Probabilistic Inference for Nonstationary Audio Analysis
In Posters Wed
William Wilkinson · Michael Riis Andersen · Joshua D. Reiss · Dan Stowell · Arno Solin
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #218
Deep Gaussian Processes with Importance-Weighted Variational Inference
In Posters Wed
Hugh Salimbeni · Vincent Dutordoir · James Hensman · Marc P Deisenroth
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #219
Automated Model Selection with Bayesian Quadrature
In Posters Wed
Henry Chai · Jean-Francois Ton · Michael A Osborne · Roman Garnett
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #220
Beyond the Chinese Restaurant and Pitman-Yor processes: Statistical Models with double power-law behavior
In Posters Wed
Fadhel Ayed · Juho Lee · Francois Caron
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #221
DP-GP-LVM: A Bayesian Non-Parametric Model for Learning Multivariate Dependency Structures
In Posters Wed
Andrew R Lawrence · Carl Henrik Ek · Neill Campbell
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #222
Random Function Priors for Correlation Modeling
In Posters Wed
Aonan Zhang · John Paisley
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #223
Variational Russian Roulette for Deep Bayesian Nonparametrics
In Posters Wed
Kai Xu · Akash Srivastava · Charles Sutton
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #224
Incorporating Grouping Information into Bayesian Decision Tree Ensembles
In Posters Wed
JUNLIANG DU · Antonio Linero
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #225
Variational Implicit Processes
In Posters Wed
Chao Ma · Yingzhen Li · Jose Miguel Hernandez-Lobato
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #226
Discovering Latent Covariance Structures for Multiple Time Series
In Posters Wed
Anh Tong · Jaesik Choi
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #227
Scalable Training of Inference Networks for Gaussian-Process Models
In Posters Wed
Jiaxin Shi · Mohammad Emtiyaz Khan · Jun Zhu
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #228
Bayesian Optimization Meets Bayesian Optimal Stopping
In Posters Wed
Zhongxiang Dai · Haibin Yu · Bryan Kian Hsiang Low · Patrick Jaillet
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #229
Learning interpretable continuous-time models of latent stochastic dynamical systems
In Posters Wed
Lea Duncker · Gergo Bohner · Julien Boussard · Maneesh Sahani
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #230
A Tree-Based Method for Fast Repeated Sampling of Determinantal Point Processes
In Posters Wed
Jennifer Gillenwater · Alex Kulesza · Zelda Mariet · Sergei Vassilvitskii
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #231
Nonlinear Stein Variational Gradient Descent for Learning Diversified Mixture Models
In Posters Wed
Dilin Wang · Qiang Liu
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #232
Understanding and Accelerating Particle-Based Variational Inference
In Posters Wed
Chang Liu · Jingwei Zhuo · Pengyu Cheng · RUIYI (ROY) ZHANG · Jun Zhu
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #233
Efficient learning of smooth probability functions from Bernoulli tests with guarantees
In Posters Wed
Paul Rolland · Ali Kavis · Alexander Niklaus Immer · Adish Singla · Volkan Cevher
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #234
The Variational Predictive Natural Gradient
In Posters Wed
Da Tang · Rajesh Ranganath
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #235
Scalable Nonparametric Sampling from Multimodal Posteriors with the Posterior Bootstrap
In Posters Wed
Edwin Fong · Simon Lyddon · Christopher Holmes
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #236
An Instability in Variational Inference for Topic Models
In Posters Wed
Behrooz Ghorbani · Hamidreza Hakim Javadi · Andrea Montanari
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #237
Bayesian Optimization of Composite Functions
In Posters Wed
Raul Astudillo · Peter I Frazier
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #238
The Kernel Interaction Trick: Fast Bayesian Discovery of Pairwise Interactions in High Dimensions
In Posters Wed
Raj Agrawal · Brian Trippe · Jonathan Huggins · Tamara Broderick
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #239
Quantile Stein Variational Gradient Descent for Batch Bayesian Optimization
In Posters Wed
Chengyue Gong · Jian Peng · Qiang Liu
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #240
Exploiting Worker Correlation for Label Aggregation in Crowdsourcing
In Posters Wed
Yuan Li · Benjamin Rubinstein · Trevor Cohn
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #241
Efficient Amortised Bayesian Inference for Hierarchical and Nonlinear Dynamical Systems
In Posters Wed
Ted Meeds · Geoffrey Roeder · Paul Grant · Andrew Phillips · Neil Dalchau
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #242
A Multitask Multiple Kernel Learning Algorithm for Survival Analysis with Application to Cancer Biology
In Posters Wed
Onur Dereli · Ceyda Oğuz · Mehmet Gönen
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #243
Fast and Flexible Inference of Joint Distributions from their Marginals
In Posters Wed
Charles Frogner · Tomaso Poggio
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #244
Cognitive model priors for predicting human decisions
In Posters Wed
Joshua C Peterson · David D Bourgin · Daniel Reichman · Thomas Griffiths · Stuart Russell
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom
Conditioning by adaptive sampling for robust design
In Posters Wed
David Brookes · Jennifer Listgarten
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #246
Direct Uncertainty Prediction for Medical Second Opinions
In Posters Wed
Maithra Raghu · Katy Blumer · Rory sayres · Ziad Obermeyer · Bobby Kleinberg · Sendhil Mullainathan · Jon Kleinberg
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #247
Dynamic Measurement Scheduling for Event Forecasting using Deep RL
In Posters Wed
Chun-Hao (Kingsley) Chang · Mingjie Mai · Anna Goldenberg
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #248
Parameter efficient training of deep convolutional neural networks by dynamic sparse reparameterization
In Posters Wed
Hesham Mostafa · Xin Wang
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #249
DeepNose: Using artificial neural networks to represent the space of odorants
In Posters Wed
Ngoc Tran · Daniel Kepple · Sergey Shuvaev · Alexei Koulakov
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #250
Domain Agnostic Learning with Disentangled Representations
In Posters Wed
Xingchao Peng · Zijun Huang · Ximeng Sun · Kate Saenko
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #251
Composing Value Functions in Reinforcement Learning
In Posters Wed
Benjamin van Niekerk · Steven James · Adam Earle · Benjamin Rosman
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #252
Fast Context Adaptation via Meta-Learning
In Posters Wed
Luisa Zintgraf · Kyriacos Shiarlis · Vitaly Kurin · Katja Hofmann · Shimon Whiteson
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #253
Provable Guarantees for Gradient-Based Meta-Learning
In Posters Wed
Nina Balcan · Mikhail Khodak · Ameet Talwalkar
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #254
Towards Understanding Knowledge Distillation
In Posters Wed
Mary Phuong · Christoph H. Lampert
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #255
Transferable Adversarial Training: A General Approach to Adapting Deep Classifiers
In Posters Wed
Hong Liu · Mingsheng Long · Jianmin Wang · Michael Jordan
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #256
Transferability vs. Discriminability: Batch Spectral Penalization for Adversarial Domain Adaptation
In Posters Wed
Xinyang Chen · Sinan Wang · Mingsheng Long · Jianmin Wang
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #257
Learning-to-Learn Stochastic Gradient Descent with Biased Regularization
In Posters Wed
Giulia Denevi · Carlo Ciliberto · Riccardo Grazzi · Massimiliano Pontil
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #258
BERT and PALs: Projected Attention Layers for Efficient Adaptation in Multi-Task Learning
In Posters Wed
Asa Cooper Stickland · Iain Murray
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #259
Towards Accurate Model Selection in Deep Unsupervised Domain Adaptation
In Posters Wed
Kaichao You · Ximei Wang · Mingsheng Long · Michael Jordan
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #260
Active Embedding Search via Noisy Paired Comparisons
In Posters Wed
Gregory Canal · Andy Massimino · Mark Davenport · Christopher Rozell
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #261
Fast Direct Search in an Optimally Compressed Continuous Target Space for Efficient Multi-Label Active Learning
In Posters Wed
weishi shi · Qi Yu
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #262
Myopic Posterior Sampling for Adaptive Goal Oriented Design of Experiments
In Posters Wed
Kirthevasan Kandasamy · Willie Neiswanger · Reed Zhang · Akshay Krishnamurthy · Jeff Schneider · Barnabás Póczos
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #263
Bayesian Generative Active Deep Learning
In Posters Wed
Toan Tran · Thanh-Toan Do · Ian Reid · Gustavo Carneiro
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #264
Active Learning for Probabilistic Structured Prediction of Cuts and Matchings
In Posters Wed
Sima Behpour · Anqi Liu · Brian Ziebart
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #265
Active Learning with Disagreement Graphs
In Posters Wed
Corinna Cortes · Giulia DeSalvo · Mehryar Mohri · Ningshan Zhang · Claudio Gentile
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #266
Multi-Frequency Vector Diffusion Maps
In Posters Wed
Yifeng Fan · Zhizhen Zhao
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #267
Co-manifold learning with missing data
In Posters Wed
Gal Mishne · Eric Chi · Ronald Coifman
Poster
Wed Jun 12 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #268
Hybrid Models with Deep and Invertible Features
In Posters Wed
Eric Nalisnick · Akihiro Matsukawa · Yee-Whye Teh · Dilan Gorur · Balaji Lakshminarayanan