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Invited Talk (Breiman Lecture)
Tue Dec 10 08:30 AM -- 09:20 AM (PST) @ West Exhibition Hall C + B3
Veridical Data Science
Bin Yu
Break
Tue Dec 10 09:20 AM -- 10:05 AM (PST) @ West and East
Coffee Break
Oral
Tue Dec 10 10:05 AM -- 10:20 AM (PST) @ West Exhibition Hall A
Logarithmic Regret for Online Control
In Track 2 Session 1
Naman Agarwal · Elad Hazan · Karan Singh
[ Paper]  [ Slides] 
Oral
Tue Dec 10 10:05 AM -- 10:20 AM (PST) @ West Ballroom C
Updates of Equilibrium Prop Match Gradients of Backprop Through Time in an RNN with Static Input
In Track 4 Session 1
Maxence Ernoult · Julie Grollier · Damien Querlioz · Yoshua Bengio · Benjamin Scellier
Oral
Tue Dec 10 10:05 AM -- 10:20 AM (PST) @ West Ballroom A + B
Kernel Instrumental Variable Regression
In Track 3 Session 1
Rahul Singh · Maneesh Sahani · Arthur Gretton
[ Paper]  [ Slides] 
Oral
Tue Dec 10 10:05 AM -- 10:20 AM (PST) @ West Exhibition Hall C + B3
Uniform convergence may be unable to explain generalization in deep learning
In Track 1 Session 1
Vaishnavh Nagarajan · J. Zico Kolter
Spotlight
Tue Dec 10 10:20 AM -- 10:25 AM (PST) @ West Exhibition Hall A
List-decodable Linear Regression
In Track 2 Session 1
Sushrut Karmalkar · Adam Klivans · Pravesh Kothari
[ Paper]  [ Poster]  [ Slides] 
Spotlight
Tue Dec 10 10:20 AM -- 10:25 AM (PST) @ West Ballroom C
Legendre Memory Units: Continuous-Time Representation in Recurrent Neural Networks
In Track 4 Session 1
Aaron Voelker · Ivana Kajić · Chris Eliasmith
Spotlight
Tue Dec 10 10:20 AM -- 10:25 AM (PST) @ West Ballroom A + B
Machine Learning Estimation of Heterogeneous Treatment Effects with Instruments
In Track 3 Session 1
Vasilis Syrgkanis · Victor Lei · Miruna Oprescu · Maggie Hei · Keith Battocchi · Greg Lewis
[ Paper]  [ Slides]  [ Slides] 
Spotlight
Tue Dec 10 10:20 AM -- 10:25 AM (PST) @ West Exhibition Hall C + B3
On Exact Computation with an Infinitely Wide Neural Net
In Track 1 Session 1
Sanjeev Arora · Simon Du · Wei Hu · Zhiyuan Li · Russ Salakhutdinov · Ruosong Wang
[ Paper]  [ Poster]  [ Slides] 
Spotlight
Tue Dec 10 10:25 AM -- 10:30 AM (PST) @ West Exhibition Hall A
On the Hardness of Robust Classification
In Track 2 Session 1
Pascale Gourdeau · Varun Kanade · Marta Kwiatkowska · James Worrell
[ Paper]  [ Slides]  [ Slides] 
Spotlight
Tue Dec 10 10:25 AM -- 10:30 AM (PST) @ West Ballroom C
Point-Voxel CNN for Efficient 3D Deep Learning
In Track 4 Session 1
Zhijian Liu · Haotian Tang · Yujun Lin · Song Han
Spotlight
Tue Dec 10 10:25 AM -- 10:30 AM (PST) @ West Ballroom A + B
Identification of Conditional Causal Effects under Markov Equivalence
In Track 3 Session 1
Amin Jaber · Jiji Zhang · Elias Bareinboim
Spotlight
Tue Dec 10 10:25 AM -- 10:30 AM (PST) @ West Exhibition Hall C + B3
Generalization Bounds of Stochastic Gradient Descent for Wide and Deep Neural Networks
In Track 1 Session 1
Yuan Cao · Quanquan Gu
[ Paper]  [ Slides]  [ Slides] 
Spotlight
Tue Dec 10 10:30 AM -- 10:35 AM (PST) @ West Exhibition Hall A
Adversarial Examples Are Not Bugs, They Are Features
In Track 2 Session 1
Andrew Ilyas · Shibani Santurkar · Dimitris Tsipras · Logan Engstrom · Brandon Tran · Aleksander Madry
Spotlight
Tue Dec 10 10:30 AM -- 10:35 AM (PST) @ West Ballroom C
Neural Networks with Cheap Differential Operators
In Track 4 Session 1
Tian Qi Chen · David Duvenaud
[ Paper]  [ Poster]  [ Slides] 
Spotlight
Tue Dec 10 10:30 AM -- 10:35 AM (PST) @ West Ballroom A + B
Likelihood-Free Overcomplete ICA and Applications In Causal Discovery
In Track 3 Session 1
Chenwei DING · Mingming Gong · Kun Zhang · Dacheng Tao
[ Paper]  [ Poster]  [ Slides] 
Spotlight
Tue Dec 10 10:30 AM -- 10:35 AM (PST) @ West Exhibition Hall C + B3
Efficient and Accurate Estimation of Lipschitz Constants for Deep Neural Networks
In Track 1 Session 1
Mahyar Fazlyab · Alexander Robey · Hamed Hassani · Manfred Morari · George J. Pappas
[ Paper]  [ Slides]  [ Slides] 
Spotlight
Tue Dec 10 10:35 AM -- 10:40 AM (PST) @ West Exhibition Hall A
Empirically Measuring Concentration: Fundamental Limits on Intrinsic Robustness
In Track 2 Session 1
Saeed Mahloujifar · Xiao Zhang · Mohammad Mahmoody · David Evans
[ Paper]  [ Poster]  [ Slides]  [ Slides]  [ 3 min Video] 
Spotlight
Tue Dec 10 10:35 AM -- 10:40 AM (PST) @ West Ballroom C
Sequential Neural Processes
In Track 4 Session 1
Gautam Singh · Jaesik Yoon · Youngsung Son · Sungjin Ahn
[ Paper]  [ Slides]  [ Slides] 
Spotlight
Tue Dec 10 10:35 AM -- 10:40 AM (PST) @ West Ballroom A + B
Perceiving the arrow of time in autoregressive motion
In Track 3 Session 1
Kristof Meding · Dominik Janzing · Bernhard Schölkopf · Felix A. Wichmann
[ Paper]  [ Poster]  [ Slides] 
Spotlight
Tue Dec 10 10:35 AM -- 10:40 AM (PST) @ West Exhibition Hall C + B3
Towards Explaining the Regularization Effect of Initial Large Learning Rate in Training Neural Networks
In Track 1 Session 1
Yuanzhi Li · Colin Wei · Tengyu Ma
[ Paper]  [ Slides]  [ Slides] 
Spotlight
Tue Dec 10 10:40 AM -- 10:45 AM (PST) @ West Exhibition Hall A
Quantum Entropy Scoring for Fast Robust Mean Estimation and Improved Outlier Detection
In Track 2 Session 1
Yihe Dong · Samuel Hopkins · Jerry Li
[ Paper]  [ Poster]  [ Slides] 
Spotlight
Tue Dec 10 10:40 AM -- 10:45 AM (PST) @ West Ballroom C
Deep Equilibrium Models
In Track 4 Session 1
Shaojie Bai · J. Zico Kolter · Vladlen Koltun
[ Paper]  [ Poster]  [ Slides]  [ Slides] 
Spotlight
Tue Dec 10 10:40 AM -- 10:45 AM (PST) @ West Ballroom A + B
Conditional Independence Testing using Generative Adversarial Networks
In Track 3 Session 1
Alexis Bellot · Mihaela van der Schaar
[ Paper]  [ Poster]  [ Slides] 
Spotlight
Tue Dec 10 10:40 AM -- 10:45 AM (PST) @ West Exhibition Hall C + B3
Data-dependent Sample Complexity of Deep Neural Networks via Lipschitz Augmentation
In Track 1 Session 1
Colin Wei · Tengyu Ma
[ Paper]  [ Slides]  [ Slides] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #1
A Game Theoretic Approach to Class-wise Selective Rationalization
In Algorithms -- Adversarial Learning
Shiyu Chang · Yang Zhang · Mo Yu · Tommi Jaakkola
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #2
A Little Is Enough: Circumventing Defenses For Distributed Learning
In Algorithms -- Adversarial Learning
Moran Baruch · Gilad Baruch · Yoav Goldberg
[ Paper]  [ Slides] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #3
A New Defense Against Adversarial Images: Turning a Weakness into a Strength
In Algorithms -- Adversarial Learning
Shengyuan Hu · Tao Yu · Chuan Guo · Wei-Lun Chao · Kilian Weinberger
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #4
Tight Certificates of Adversarial Robustness for Randomly Smoothed Classifiers
In Algorithms -- Adversarial Learning
Guang-He Lee · Yang Yuan · Shiyu Chang · Tommi Jaakkola
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #5
Adversarial training for free!
In Algorithms -- Adversarial Learning
Ali Shafahi · Mahyar Najibi · Mohammad Amin Ghiasi · Zheng Xu · John Dickerson · Christoph Studer · Larry Davis · Gavin Taylor · Tom Goldstein
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #6
Certifiable Robustness to Graph Perturbations
In Algorithms -- Adversarial Learning
Aleksandar Bojchevski · Stephan Günnemann
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #7
Certified Adversarial Robustness with Additive Noise
In Algorithms -- Adversarial Learning
Bai Li · Changyou Chen · Wenlin Wang · Lawrence Carin
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #8
Defense Against Adversarial Attacks Using Feature Scattering-based Adversarial Training
In Algorithms -- Adversarial Learning
Haichao Zhang · Jianyu Wang
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #9
Efficient online learning with kernels for adversarial large scale problems
In Algorithms -- Adversarial Learning
Rémi Jézéquel · Pierre Gaillard · Alessandro Rudi
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #10
Empirically Measuring Concentration: Fundamental Limits on Intrinsic Robustness
In Algorithms -- Adversarial Learning
Saeed Mahloujifar · Xiao Zhang · Mohammad Mahmoody · David Evans
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #11
Error Correcting Output Codes Improve Probability Estimation and Adversarial Robustness of Deep Neural Networks
In Algorithms -- Adversarial Learning
Gunjan Verma · Ananthram Swami
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #12
Learning from Bad Data via Generation
In Algorithms -- Adversarial Learning
Tianyu Guo · Chang Xu · Boxin Shi · Chao Xu · Dacheng Tao
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #13
Multi-marginal Wasserstein GAN
In Algorithms -- Adversarial Learning
Jiezhang Cao · Langyuan Mo · Yifan Zhang · Kui Jia · Chunhua Shen · Mingkui Tan
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #14
ResNets Ensemble via the Feynman-Kac Formalism to Improve Natural and Robust Accuracies
In Algorithms -- Adversarial Learning
Bao Wang · Zuoqiang Shi · Stanley Osher
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #15
Subspace Attack: Exploiting Promising Subspaces for Query-Efficient Black-box Attacks
In Algorithms -- Adversarial Learning
Yiwen Guo · Ziang Yan · Changshui Zhang
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #16
ZO-AdaMM: Zeroth-Order Adaptive Momentum Method for Black-Box Optimization
In Algorithms -- Adversarial Learning
Xiangyi Chen · Sijia Liu · Kaidi Xu · Xingguo Li · Xue Lin · Mingyi Hong · David Cox
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #17
Blocking Bandits
In Algorithms -- Bandit Algorithms
Soumya Basu · Rajat Sen · Sujay Sanghavi · Sanjay Shakkottai
[ Paper]  [ Slides] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #18
Combinatorial Bandits with Relative Feedback
In Algorithms -- Bandit Algorithms
Aadirupa Saha · Aditya Gopalan
[ Paper]  [ Slides] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #19
Decentralized Cooperative Stochastic Bandits
In Algorithms -- Bandit Algorithms
David Martínez-Rubio · Varun Kanade · Patrick Rebeschini
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #20
Doubly-Robust Lasso Bandit
In Algorithms -- Bandit Algorithms
Gi-Soo Kim · Myunghee Cho Paik
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #21
Efficient Pure Exploration in Adaptive Round Model
In Algorithms -- Bandit Algorithms
Tianyuan Jin · Jieming SHI · Xiaokui Xiao · Enhong Chen
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #22
Epsilon-Best-Arm Identification in Pay-Per-Reward Multi-Armed Bandits
In Algorithms -- Bandit Algorithms
Sivan Sabato
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #23
Nonstochastic Multiarmed Bandits with Unrestricted Delays
In Algorithms -- Bandit Algorithms
Tobias Sommer Thune · Nicolò Cesa-Bianchi · Yevgeny Seldin
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #24
On the Optimality of Perturbations in Stochastic and Adversarial Multi-armed Bandit Problems
In Algorithms -- Bandit Algorithms
Baekjin Kim · Ambuj Tewari
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #25
Phase Transitions and Cyclic Phenomena in Bandits with Switching Constraints
In Algorithms -- Bandit Algorithms
David Simchi-Levi · Yunzong Xu
[ Paper]  [ Slides] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #26
Polynomial Cost of Adaptation for X-Armed Bandits
In Algorithms -- Bandit Algorithms
Hedi Hadiji
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #27
Semi-Parametric Dynamic Contextual Pricing
In Algorithms -- Bandit Algorithms
Virag Shah · Ramesh Johari · Jose Blanchet
[ Paper]  [ Slides] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #28
Coresets for Clustering with Fairness Constraints
In Algorithms -- Clustering
Lingxiao Huang · Shaofeng Jiang · Nisheeth Vishnoi
[ Paper]  [ Slides] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #29
Correlation Clustering with Adaptive Similarity Queries
In Algorithms -- Clustering
Marco Bressan · Nicolò Cesa-Bianchi · Andrea Paudice · Fabio Vitale
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #30
Correlation clustering with local objectives
In Algorithms -- Clustering
Sanchit Kalhan · Konstantin Makarychev · Timothy Zhou
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #31
Foundations of Comparison-Based Hierarchical Clustering
In Algorithms -- Clustering
Debarghya Ghoshdastidar · Michaël Perrot · Ulrike von Luxburg
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #32
Fully Dynamic Consistent Facility Location
In Algorithms -- Clustering
Vincent Cohen-Addad · Niklas Oskar D Hjuler · Nikos Parotsidis · David Saulpic · Chris Schwiegelshohn
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #33
Greedy Sampling for Approximate Clustering in the Presence of Outliers
In Algorithms -- Clustering
Aditya Bhaskara · Sharvaree Vadgama · Hong Xu
[ Paper]  [ Slides] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #34
k-Means Clustering of Lines for Big Data
In Algorithms -- Clustering
Yair Marom · Dan Feldman
[ Paper]  [ Slides] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #35
Near Neighbor: Who is the Fairest of Them All?
In Algorithms -- Clustering
Sariel Har-Peled · Sepideh Mahabadi
[ Paper]  [ Slides] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #36
Random Projections and Sampling Algorithms for Clustering of High-Dimensional Polygonal Curves
In Algorithms -- Clustering
Stefan Meintrup · Alexander Munteanu · Dennis Rohde
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #37
Same-Cluster Querying for Overlapping Clusters
In Algorithms -- Clustering
Wasim Huleihel · Arya Mazumdar · Muriel Medard · Soumyabrata Pal
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #38
Selective Sampling-based Scalable Sparse Subspace Clustering
In Algorithms -- Clustering
Shin Matsushima · Maria Brbic
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #39
Spectral Modification of Graphs for Improved Spectral Clustering
In Algorithms -- Clustering
Ioannis Koutis · Huong Le
[ Paper]  [ Slides] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #40
Subquadratic High-Dimensional Hierarchical Clustering
In Algorithms -- Clustering
Amir Abboud · Vincent Cohen-Addad · Hussein Houdrouge
[ Paper]  [ Slides] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #41
Ultra Fast Medoid Identification via Correlated Sequential Halving
In Algorithms -- Clustering
Tavor Baharav · David Tse
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #42
Ultrametric Fitting by Gradient Descent
In Algorithms -- Clustering
Giovanni Chierchia · Benjamin Perret
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #43
Backpropagation-Friendly Eigendecomposition
In Algorithms -- Components Analysis (e.g., CCA, ICA, LDA, PCA)
Wei Wang · Zheng Dang · Yinlin Hu · Pascal Fua · Mathieu Salzmann
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #44
Learning-Based Low-Rank Approximations
In Algorithms -- Components Analysis (e.g., CCA, ICA, LDA, PCA)
Piotr Indyk · Ali Vakilian · Yang Yuan
[ Paper]  [ Poster]  [ Slides] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #45
Likelihood-Free Overcomplete ICA and Applications In Causal Discovery
In Algorithms -- Components Analysis (e.g., CCA, ICA, LDA, PCA)
Chenwei DING · Mingming Gong · Kun Zhang · Dacheng Tao
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #46
Sobolev Independence Criterion
In Algorithms -- Components Analysis (e.g., CCA, ICA, LDA, PCA)
Youssef Mroueh · Tom Sercu · Mattia Rigotti · Inkit Padhi · Cicero Nogueira dos Santos
[ Paper]  [ Slides] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #47
Towards a Zero-One Law for Column Subset Selection
In Algorithms -- Components Analysis (e.g., CCA, ICA, LDA, PCA)
Zhao Song · David Woodruff · Peilin Zhong
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #48
Fisher Efficient Inference of Intractable Models
In Algorithms -- Density Estimation
Song Liu · Takafumi Kanamori · Wittawat Jitkrittum · Yu Chen
[ Paper]  [ Slides] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #49
Learning Distributions Generated by One-Layer ReLU Networks
In Algorithms -- Density Estimation
Shanshan Wu · Alex Dimakis · Sujay Sanghavi
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #50
On Fenchel Mini-Max Learning
In Algorithms -- Density Estimation
Chenyang Tao · Liqun Chen · Shuyang Dai · Junya Chen · Ke Bai · Dong Wang · Jianfeng Feng · Wenlian Lu · Georgiy Bobashev · Lawrence Carin
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #51
Practical and Consistent Estimation of f-Divergences
In Algorithms -- Density Estimation
Paul Rubenstein · Olivier Bousquet · Josip Djolonga · Carlos Riquelme · Ilya Tolstikhin
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #52
Re-examination of the Role of Latent Variables in Sequence Modeling
In Algorithms -- Density Estimation
Guokun Lai · Zihang Dai · Yiming Yang · Shinjae Yoo
[ Paper]  [ Slides] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #53
Space and Time Efficient Kernel Density Estimation in High Dimensions
In Algorithms -- Density Estimation
Arturs Backurs · Piotr Indyk · Tal Wagner
[ Paper]  [ Slides] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #54
Unconstrained Monotonic Neural Networks
In Algorithms -- Density Estimation
Antoine Wehenkel · Gilles Louppe
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #55
Mutually Regressive Point Processes
In Algorithms -- Dynamical Systems
Ifigeneia Apostolopoulou · Scott Linderman · Kyle Miller · Artur Dubrawski
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #56
Neural Networks with Cheap Differential Operators
In Algorithms -- Dynamical Systems
Tian Qi Chen · David Duvenaud
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #57
Convergence Guarantees for Adaptive Bayesian Quadrature Methods
In Algorithms -- Kernel Methods
Motonobu Kanagawa · Philipp Hennig
[ Paper]  [ Slides] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #58
Globally Convergent Newton Methods for Ill-conditioned Generalized Self-concordant Losses
In Algorithms -- Kernel Methods
Ulysse Marteau-Ferey · Francis Bach · Alessandro Rudi
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #59
Kernel Instrumental Variable Regression
In Algorithms -- Kernel Methods
Rahul Singh · Maneesh Sahani · Arthur Gretton
[ Paper]  [ Slides] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #60
Kernel Stein Tests for Multiple Model Comparison
In Algorithms -- Kernel Methods
Jen Ning Lim · Makoto Yamada · Bernhard Schölkopf · Wittawat Jitkrittum
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #61
On Exact Computation with an Infinitely Wide Neural Net
In Algorithms -- Kernel Methods
Sanjeev Arora · Simon Du · Wei Hu · Zhiyuan Li · Russ Salakhutdinov · Ruosong Wang
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #62
Solving Interpretable Kernel Dimensionality Reduction
In Algorithms -- Kernel Methods
Chieh Wu · Jared Miller · Yale Chang · Mario Sznaier · Jennifer Dy
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #63
Missing Not at Random in Matrix Completion: The Effectiveness of Estimating Missingness Probabilities Under a Low Nuclear Norm Assumption
In Algorithms -- Missing Data
Wei Ma · George H Chen
[ Paper]  [ Slides] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #64
Aligning Visual Regions and Textual Concepts for Semantic-Grounded Image Representations
In Algorithms -- Representation Learning
Fenglin Liu · Yuanxin Liu · Xuancheng Ren · Xiaodong He · Xu Sun
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #65
Augmented Neural ODEs
In Algorithms -- Representation Learning
Emilien Dupont · Arnaud Doucet · Yee Whye Teh
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #66
Beyond Vector Spaces: Compact Data Representation as Differentiable Weighted Graphs
In Algorithms -- Representation Learning
Denis Mazur · Vage Egiazarian · Stanislav Morozov · Artem Babenko
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #67
Exact Rate-Distortion in Autoencoders via Echo Noise
In Algorithms -- Representation Learning
Rob Brekelmans · Daniel Moyer · Aram Galstyan · Greg Ver Steeg
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #68
Information Competing Process for Learning Diversified Representations
In Algorithms -- Representation Learning
Jie Hu · Rongrong Ji · ShengChuan Zhang · Xiaoshuai Sun · Qixiang Ye · Chia-Wen Lin · Qi Tian
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #69
Learning low-dimensional state embeddings and metastable clusters from time series data
In Algorithms -- Representation Learning
Yifan Sun · Yaqi Duan · Hao Gong · Mengdi Wang
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #70
Learning Nonsymmetric Determinantal Point Processes
In Algorithms -- Representation Learning
Mike Gartrell · Victor-Emmanuel Brunel · Elvis Dohmatob · Syrine Krichene
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #71
Provably Powerful Graph Networks
In Algorithms -- Representation Learning
Haggai Maron · Heli Ben-Hamu · Hadar Serviansky · Yaron Lipman
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #72
Quaternion Knowledge Graph Embeddings
In Algorithms -- Representation Learning
SHUAI ZHANG · Yi Tay · Lina Yao · Qi Liu
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #73
Semi-supervisedly Co-embedding Attributed Networks
In Algorithms -- Representation Learning
Zaiqiao Meng · Shangsong Liang · Jinyuan Fang · Teng Xiao
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #74
A Direct tilde{O}(1/epsilon) Iteration Parallel Algorithm for Optimal Transport
In Algorithms -- Similarity and Distance Learning
Arun Jambulapati · Aaron Sidford · Kevin Tian
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #75
Conditional Independence Testing using Generative Adversarial Networks
In Algorithms -- Similarity and Distance Learning
Alexis Bellot · Mihaela van der Schaar
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #76
Generalized Sliced Wasserstein Distances
In Algorithms -- Similarity and Distance Learning
Soheil Kolouri · Kimia Nadjahi · Umut Simsekli · Roland Badeau · Gustavo Rohde
[ Paper]  [ Poster]  [ Slides] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #77
Hyperspherical Prototype Networks
In Algorithms -- Similarity and Distance Learning
Pascal Mettes · Elise van der Pol · Cees Snoek
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #78
Input Similarity from the Neural Network Perspective
In Algorithms -- Similarity and Distance Learning
Guillaume Charpiat · Nicolas Girard · Loris Felardos · Yuliya Tarabalka
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #79
Landmark Ordinal Embedding
In Algorithms -- Similarity and Distance Learning
Nikhil Ghosh · Yuxin Chen · Yisong Yue
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #80
Tree-Sliced Variants of Wasserstein Distances
In Algorithms -- Similarity and Distance Learning
Tam Le · Makoto Yamada · Kenji Fukumizu · Marco Cuturi
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #81
Communication-efficient Distributed SGD with Sketching
In Applications -- Communication- or Memory-Bounded Learning
Nikita Ivkin · Daniel Rothchild · Enayat Ullah · Vladimir Braverman · Ion Stoica · Raman Arora
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #82
Order Optimal One-Shot Distributed Learning
In Applications -- Communication- or Memory-Bounded Learning
Arsalan Sharifnassab · Saber Salehkaleybar · S. Jamaloddin Golestani
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #83
Approximating Interactive Human Evaluation with Self-Play for Open-Domain Dialog Systems
In Applications -- Dialog- or Communication-Based Learning
Asma Ghandeharioun · Judy Hanwen Shen · Natasha Jaques · Craig Ferguson · Noah Jones · Agata Lapedriza · Rosalind Picard
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #84
Game Design for Eliciting Distinguishable Behavior
In Applications -- Game Playing
Fan Yang · Liu Leqi · Yifan Wu · Zachary Lipton · Pradeep Ravikumar · Tom M Mitchell · William Cohen
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #85
Adversarial Examples Are Not Bugs, They Are Features
In Applications -- Privacy, Anonymity, and Security
Andrew Ilyas · Shibani Santurkar · Dimitris Tsipras · Logan Engstrom · Brandon Tran · Aleksander Madry
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #86
Average-Case Averages: Private Algorithms for Smooth Sensitivity and Mean Estimation
In Applications -- Privacy, Anonymity, and Security
Mark Bun · Thomas Steinke
[ Paper]  [ Slides] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #87
Capacity Bounded Differential Privacy
In Applications -- Privacy, Anonymity, and Security
Kamalika Chaudhuri · Jacob Imola · Ashwin Machanavajjhala
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #88
Differentially Private Anonymized Histograms
In Applications -- Privacy, Anonymity, and Security
Ananda Theertha Suresh
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #89
Differentially Private Bagging: Improved utility and cheaper privacy than subsample-and-aggregate
In Applications -- Privacy, Anonymity, and Security
James Jordon · Jinsung Yoon · Mihaela van der Schaar
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #90
Differentially Private Bayesian Linear Regression
In Applications -- Privacy, Anonymity, and Security
Garrett Bernstein · Daniel Sheldon
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #91
Efficiently Estimating Erdos-Renyi Graphs with Node Differential Privacy
In Applications -- Privacy, Anonymity, and Security
Jonathan Ullman · Adam Sealfon
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #92
Locally Private Gaussian Estimation
In Applications -- Privacy, Anonymity, and Security
Matthew Joseph · Janardhan Kulkarni · Jieming Mao · Steven Wu
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #93
Minimax Optimal Estimation of Approximate Differential Privacy on Neighboring Databases
In Applications -- Privacy, Anonymity, and Security
Xiyang Liu · Sewoong Oh
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #94
Differentially Private Algorithms for Learning Mixtures of Separated Gaussians
In Applications -- Privacy, Anonymity, and Security
Gautam Kamath · Or Sheffet · Vikrant Singhal · Jonathan Ullman
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #95
Partially Encrypted Deep Learning using Functional Encryption
In Applications -- Privacy, Anonymity, and Security
Théo Ryffel · David Pointcheval · Francis Bach · Edouard Dufour-Sans · Romain Gay
[ Paper]  [ Slides] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #96
Privacy-Preserving Classification of Personal Text Messages with Secure Multi-Party Computation
In Applications -- Privacy, Anonymity, and Security
Devin Reich · Ariel Todoki · Rafael Dowsley · Martine De Cock · Anderson Nascimento
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #97
Reward Constrained Interactive Recommendation with Natural Language Feedback
In Applications -- Recommender Systems
Ruiyi Zhang · Tong Yu · Yilin Shen · Hongxia Jin · Changyou Chen
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #98
Model-Based Reinforcement Learning with Adversarial Training for Online Recommendation
In Applications -- Recommender Systems
Xueying Bai · Jian Guan · Hongning Wang
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #99
Joint Optimization of Tree-based Index and Deep Model for Recommender Systems
In Applications -- Recommender Systems
Han Zhu · Daqing Chang · Ziru Xu · Pengye Zhang · Xiang Li · Jie He · Han Li · Jian Xu · Kun Gai
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #100
iSplit LBI: Individualized Partial Ranking with Ties via Split LBI
In Applications -- Web Applications and Internet Data
Qianqian Xu · Xinwei Sun · Zhiyong Yang · Xiaochun Cao · Qingming Huang · Yuan Yao
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #101
Structured and Deep Similarity Matching via Structured and Deep Hebbian Networks
In Deep Learning -- Biologically Plausible Deep Networks
Dina Obeid · Hugo Ramambason · Cengiz Pehlevan
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #102
Deep Learning without Weight Transport
In Deep Learning -- Biologically Plausible Deep Networks
Mohamed Akrout · Collin Wilson · Peter Humphreys · Timothy Lillicrap · Douglas Tweed
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #103
Neural networks grown and self-organized by noise
In Deep Learning -- Biologically Plausible Deep Networks
Guruprasad Raghavan · Matt Thomson
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #104
Spike-Train Level Backpropagation for Training Deep Recurrent Spiking Neural Networks
In Deep Learning -- Biologically Plausible Deep Networks
Wenrui Zhang · Peng Li
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #105
Surround Modulation: A Bio-inspired Connectivity Structure for Convolutional Neural Networks
In Deep Learning -- Biologically Plausible Deep Networks
Hosein Hasani · Mahdieh Soleymani · Hamid Aghajan
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #106
Updates of Equilibrium Prop Match Gradients of Backprop Through Time in an RNN with Static Input
In Deep Learning -- Biologically Plausible Deep Networks
Maxence Ernoult · Julie Grollier · Damien Querlioz · Yoshua Bengio · Benjamin Scellier
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #107
AGEM: Solving Linear Inverse Problems via Deep Priors and Sampling
In Deep Learning -- Deep Autoencoders
Bichuan Guo · Yuxing Han · Jiangtao Wen
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #108
Bat-G net: Bat-inspired High-Resolution 3D Image Reconstruction using Ultrasonic Echoes
In Deep Learning -- Deep Autoencoders
Gunpil Hwang · Seohyeon Kim · Hyeon-Min Bae
[ Paper]  [ Poster]  [ Slides] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #109
Continuous Hierarchical Representations with Poincaré Variational Auto-Encoders
In Deep Learning -- Deep Autoencoders
Emile Mathieu · Charline Le Lan · Chris Maddison · Ryota Tomioka · Yee Whye Teh
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #110
Channel Gating Neural Networks
In Deep Learning -- Efficient Inference Methods
Weizhe Hua · Yuan Zhou · Christopher De Sa · Zhiru Zhang · G. Edward Suh
[ Paper]  [ Slides] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #111
Deconstructing Lottery Tickets: Zeros, Signs, and the Supermask
In Deep Learning -- Efficient Inference Methods
Hattie Zhou · Janice Lan · Rosanne Liu · Jason Yosinski
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #112
Point-Voxel CNN for Efficient 3D Deep Learning
In Deep Learning -- Efficient Inference Methods
Zhijian Liu · Haotian Tang · Yujun Lin · Song Han
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #113
Gate Decorator: Global Filter Pruning Method for Accelerating Deep Convolutional Neural Networks
In Deep Learning -- Efficient Inference Methods
Zhonghui You · Kun Yan · Jinmian Ye · Meng Ma · Ping Wang
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #114
Inherent Weight Normalization in Stochastic Neural Networks
In Deep Learning -- Efficient Inference Methods
Georgios Detorakis · Sourav Dutta · Abhishek Khanna · Matthew Jerry · Suman Datta · Emre O Neftci
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #115
MetaQuant: Learning to Quantize by Learning to Penetrate Non-differentiable Quantization
In Deep Learning -- Efficient Inference Methods
Shangyu Chen · Wenya Wang · Sinno Jialin Pan
[ Paper]  [ Slides] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #116
Model Compression with Adversarial Robustness: A Unified Optimization Framework
In Deep Learning -- Efficient Inference Methods
Shupeng Gui · Haotao Wang · Haichuan Yang · Chen Yu · Zhangyang Wang · Ji Liu
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #117
Positive-Unlabeled Compression on the Cloud
In Deep Learning -- Efficient Inference Methods
Yixing Xu · Yunhe Wang · Hanting Chen · Kai Han · Chunjing XU · Dacheng Tao · Chang Xu
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #118
A Primal-Dual link between GANs and Autoencoders
In Deep Learning -- Generative Models
Hisham Husain · Richard Nock · Robert Williamson
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #119
A Prior of a Googol Gaussians: a Tensor Ring Induced Prior for Generative Models
In Deep Learning -- Generative Models
Maxim Kuznetsov · Daniil Polykovskiy · Dmitry Vetrov · Alex Zhebrak
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #120
Adversarial Self-Defense for Cycle-Consistent GANs
In Deep Learning -- Generative Models
Dina Bashkirova · Ben Usman · Kate Saenko
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #121
Controllable Text-to-Image Generation
In Deep Learning -- Generative Models
Bowen Li · Xiaojuan Qi · Thomas Lukasiewicz · Philip Torr
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #122
Dancing to Music
In Deep Learning -- Generative Models
Hsin-Ying Lee · Xiaodong Yang · Ming-Yu Liu · Ting-Chun Wang · Yu-Ding Lu · Ming-Hsuan Yang · Jan Kautz
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #123
DppNet: Approximating Determinantal Point Processes with Deep Networks
In Deep Learning -- Generative Models
Zelda Mariet · Yaniv Ovadia · Jasper Snoek
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #124
Efficient Graph Generation with Graph Recurrent Attention Networks
In Deep Learning -- Generative Models
Renjie Liao · Yujia Li · Yang Song · Shenlong Wang · Will Hamilton · David Duvenaud · Raquel Urtasun · Richard Zemel
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #125
Explicit Disentanglement of Appearance and Perspective in Generative Models
In Deep Learning -- Generative Models
Nicki Skafte · Søren Hauberg
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #126
Flow-based Image-to-Image Translation with Feature Disentanglement
In Deep Learning -- Generative Models
Ruho Kondo · Keisuke Kawano · Satoshi Koide · Takuro Kutsuna
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #127
Generalization in Generative Adversarial Networks: A Novel Perspective from Privacy Protection
In Deep Learning -- Generative Models
Bingzhe Wu · Shiwan Zhao · Chaochao Chen · Haoyang Xu · Li Wang · Xiaolu Zhang · Guangyu Sun · Jun Zhou
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #128
Improved Precision and Recall Metric for Assessing Generative Models
In Deep Learning -- Generative Models
Tuomas Kynkäänniemi · Tero Karras · Samuli Laine · Jaakko Lehtinen · Timo Aila
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #129
Knowledge Extraction with No Observable Data
In Deep Learning -- Generative Models
Jaemin Yoo · Minyong Cho · Taebum Kim · U Kang
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #130
Learn, Imagine and Create: Text-to-Image Generation from Prior Knowledge
In Deep Learning -- Generative Models
Tingting Qiao · Jing Zhang · Duanqing Xu · Dacheng Tao
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #131
PasteGAN: A Semi-Parametric Method to Generate Image from Scene Graph
In Deep Learning -- Generative Models
Yikang LI · Tao Ma · Yeqi Bai · Nan Duan · Sining Wei · Xiaogang Wang
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #132
Sequential Neural Processes
In Deep Learning -- Generative Models
Gautam Singh · Jaesik Yoon · Youngsung Son · Sungjin Ahn
[ Paper]  [ Slides] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #133
Unsupervised Keypoint Learning for Guiding Class-Conditional Video Prediction
In Deep Learning -- Generative Models
Yunji Kim · Seonghyeon Nam · In Cho · Seon Joo Kim
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #134
GNNExplainer: Generating Explanations for Graph Neural Networks
In Deep Learning -- Interaction-Based Deep Networks
Zhitao Ying · Dylan Bourgeois · Jiaxuan You · Marinka Zitnik · Jure Leskovec
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #135
An Improved Analysis of Training Over-parameterized Deep Neural Networks
In Deep Learning -- Optimization for Deep Networks
Difan Zou · Quanquan Gu
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #136
Controlling Neural Level Sets
In Deep Learning -- Optimization for Deep Networks
Matan Atzmon · Niv Haim · Lior Yariv · Ofer Israelov · Haggai Maron · Yaron Lipman
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #137
Deep Equilibrium Models
In Deep Learning -- Optimization for Deep Networks
Shaojie Bai · J. Zico Kolter · Vladlen Koltun
[ Paper]  [ Poster]  [ Slides] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #138
Differentiable Cloth Simulation for Inverse Problems
In Deep Learning -- Optimization for Deep Networks
Junbang Liang · Ming Lin · Vladlen Koltun
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #139
Efficient and Accurate Estimation of Lipschitz Constants for Deep Neural Networks
In Deep Learning -- Optimization for Deep Networks
Mahyar Fazlyab · Alexander Robey · Hamed Hassani · Manfred Morari · George J. Pappas
[ Paper]  [ Slides] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #140
Fine-grained Optimization of Deep Neural Networks
In Deep Learning -- Optimization for Deep Networks
Mete Ozay
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #141
Generalization Bounds of Stochastic Gradient Descent for Wide and Deep Neural Networks
In Deep Learning -- Optimization for Deep Networks
Yuan Cao · Quanquan Gu
[ Paper]  [ Slides] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #142
On Learning Over-parameterized Neural Networks: A Functional Approximation Perspective
In Deep Learning -- Optimization for Deep Networks
Lili Su · Pengkun Yang
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #143
Stagewise Training Accelerates Convergence of Testing Error Over SGD
In Deep Learning -- Optimization for Deep Networks
Zhuoning Yuan · Yan Yan · Rong Jin · Tianbao Yang
[ Paper]  [ Slides] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #144
Towards Explaining the Regularization Effect of Initial Large Learning Rate in Training Neural Networks
In Deep Learning -- Optimization for Deep Networks
Yuanzhi Li · Colin Wei · Tengyu Ma
[ Paper]  [ Slides] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #145
You Only Propagate Once: Accelerating Adversarial Training via Maximal Principle
In Deep Learning -- Optimization for Deep Networks
Dinghuai Zhang · Tianyuan Zhang · Yiping Lu · Zhanxing Zhu · Bin Dong
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #146
A Simple Baseline for Bayesian Uncertainty in Deep Learning
In Deep Learning -- Predictive Models
Wesley Maddox · Pavel Izmailov · Timur Garipov · Dmitry Vetrov · Andrew Gordon Wilson
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #148
High Fidelity Video Prediction with Large Stochastic Recurrent Neural Networks
In Deep Learning -- Predictive Models
Ruben Villegas · Arkanath Pathak · Harini Kannan · Dumitru Erhan · Quoc V Le · Honglak Lee
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #149
Unsupervised learning of object structure and dynamics from videos
In Deep Learning -- Predictive Models
Matthias Minderer · Chen Sun · Ruben Villegas · Forrester Cole · Kevin Murphy · Honglak Lee
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #150
Can SGD Learn Recurrent Neural Networks with Provable Generalization?
In Deep Learning -- Recurrent Networks
Zeyuan Allen-Zhu · Yuanzhi Li
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #151
Input-Cell Attention Reduces Vanishing Saliency of Recurrent Neural Networks
In Deep Learning -- Recurrent Networks
Aya Abdelsalam Ismail · Mohamed Gunady · Luiz Pessoa · Hector Corrada Bravo · Soheil Feizi
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #152
Input-Output Equivalence of Unitary and Contractive RNNs
In Deep Learning -- Recurrent Networks
Melikasadat Emami · Mojtaba Sahraee Ardakan · Sundeep Rangan · Alyson Fletcher
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #153
Kernel-Based Approaches for Sequence Modeling: Connections to Neural Methods
In Deep Learning -- Recurrent Networks
Kevin J Liang · Guoyin Wang · Yitong Li · Ricardo Henao · Lawrence Carin
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #154
Legendre Memory Units: Continuous-Time Representation in Recurrent Neural Networks
In Deep Learning -- Recurrent Networks
Aaron Voelker · Ivana Kajić · Chris Eliasmith
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #155
Non-normal Recurrent Neural Network (nnRNN): learning long time dependencies while improving expressivity with transient dynamics
In Deep Learning -- Recurrent Networks
Giancarlo Kerg · Kyle Goyette · Maximilian Puelma Touzel · Gauthier Gidel · Eugene Vorontsov · Yoshua Bengio · Guillaume Lajoie
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #156
Reverse engineering recurrent networks for sentiment classification reveals line attractor dynamics
In Deep Learning -- Recurrent Networks
Niru Maheswaranathan · Alex Williams · Matthew Golub · Surya Ganguli · David Sussillo
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #157
Root Mean Square Layer Normalization
In Deep Learning -- Recurrent Networks
Biao Zhang · Rico Sennrich
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #158
Universal Approximation of Input-Output Maps by Temporal Convolutional Nets
In Deep Learning -- Recurrent Networks
Joshua Hanson · Maxim Raginsky
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #159
A Benchmark for Interpretability Methods in Deep Neural Networks
In Deep Learning -- Visualization or Exposition Techniques for Deep Networks
Sara Hooker · Dumitru Erhan · Pieter-Jan Kindermans · Been Kim
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #160
Accurate, reliable and fast robustness evaluation
In Deep Learning -- Visualization or Exposition Techniques for Deep Networks
Wieland Brendel · Jonas Rauber · Matthias Kümmerer · Ivan Ustyuzhaninov · Matthias Bethge
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #161
Approximate Feature Collisions in Neural Nets
In Deep Learning -- Visualization or Exposition Techniques for Deep Networks
Ke Li · Tianhao Zhang · Jitendra Malik
[ Paper] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #162
Computing Linear Restrictions of Neural Networks
In Deep Learning -- Visualization or Exposition Techniques for Deep Networks
Matthew Sotoudeh · Aditya V Thakur
[ Paper]  [ Poster]  [ Slides] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #163
CXPlain: Causal Explanations for Model Interpretation under Uncertainty
In Deep Learning -- Visualization or Exposition Techniques for Deep Networks
Patrick Schwab · Walter Karlen
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #164
Deliberative Explanations: visualizing network insecurities
In Deep Learning -- Visualization or Exposition Techniques for Deep Networks
Pei Wang · Nuno Nvasconcelos
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #165
Explanations can be manipulated and geometry is to blame
In Deep Learning -- Visualization or Exposition Techniques for Deep Networks
Ann-Kathrin Dombrowski · Maximillian Alber · Christopher Anders · Marcel Ackermann · Klaus-Robert Müller · Pan Kessel
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #166
Fooling Neural Network Interpretations via Adversarial Model Manipulation
In Deep Learning -- Visualization or Exposition Techniques for Deep Networks
Juyeon Heo · Sunghwan Joo · Taesup Moon
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #167
Full-Gradient Representation for Neural Network Visualization
In Deep Learning -- Visualization or Exposition Techniques for Deep Networks
Suraj Srinivas · François Fleuret
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #168
Grid Saliency for Context Explanations of Semantic Segmentation
In Deep Learning -- Visualization or Exposition Techniques for Deep Networks
Lukas Hoyer · Mauricio Munoz · Prateek Katiyar · Anna Khoreva · Volker Fischer
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #169
Intrinsic dimension of data representations in deep neural networks
In Deep Learning -- Visualization or Exposition Techniques for Deep Networks
Alessio Ansuini · Alessandro Laio · Jakob H Macke · Davide Zoccolan
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #170
One ticket to win them all: generalizing lottery ticket initializations across datasets and optimizers
In Deep Learning -- Visualization or Exposition Techniques for Deep Networks
Ari Morcos · Haonan Yu · Michela Paganini · Yuandong Tian
[ Paper]  [ Slides] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #171
The Geometry of Deep Networks: Power Diagram Subdivision
In Deep Learning -- Visualization or Exposition Techniques for Deep Networks
Randall Balestriero · Romain Cosentino · Behnaam Aazhang · Richard Baraniuk
[ Paper]  [ Slides] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #172
Visualizing and Measuring the Geometry of BERT
In Deep Learning -- Visualization or Exposition Techniques for Deep Networks
Emily Reif · Ann Yuan · Martin Wattenberg · Fernanda Viegas · Andy Coenen · Adam Pearce · Been Kim
[ Paper]  [ Slides] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #173
Visualizing the PHATE of Neural Networks
In Deep Learning -- Visualization or Exposition Techniques for Deep Networks
Scott Gigante · Adam S Charles · Smita Krishnaswamy · Gal Mishne
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #174
A Graph Theoretic Additive Approximation of Optimal Transport
In Optimization -- Combinatorial Optimization
Nathaniel Lahn · Deepika Mulchandani · Sharath Raghvendra
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #175
Combinatorial Bayesian Optimization using the Graph Cartesian Product
In Optimization -- Combinatorial Optimization
Changyong Oh · Jakub Tomczak · Stratis Gavves · Max Welling
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #176
Exact Combinatorial Optimization with Graph Convolutional Neural Networks
In Optimization -- Combinatorial Optimization
Maxime Gasse · Didier Chetelat · Nicola Ferroni · Laurent Charlin · Andrea Lodi
[ Paper]  [ Slides] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #177
Learning Local Search Heuristics for Boolean Satisfiability
In Optimization -- Combinatorial Optimization
Emre Yolcu · Barnabas Poczos
[ Paper]  [ Slides] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #178
Learning to Perform Local Rewriting for Combinatorial Optimization
In Optimization -- Combinatorial Optimization
Xinyun Chen · Yuandong Tian
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #179
Adapting Neural Networks for the Estimation of Treatment Effects
In Probabilistic Methods -- Causal Inference
Claudia Shi · David Blei · Victor Veitch
[ Paper]  [ Slides] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #180
Causal Regularization
In Probabilistic Methods -- Causal Inference
Dominik Janzing
[ Paper]  [ Poster]  [ Slides] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #181
Characterization and Learning of Causal Graphs with Latent Variables from Soft Interventions
In Probabilistic Methods -- Causal Inference
Murat Kocaoglu · Amin Jaber · Karthikeyan Shanmugam · Elias Bareinboim
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #182
Debiased Bayesian inference for average treatment effects
In Probabilistic Methods -- Causal Inference
Kolyan Ray · Botond Szabo
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #183
Deep Generalized Method of Moments for Instrumental Variable Analysis
In Probabilistic Methods -- Causal Inference
Andrew Bennett · Nathan Kallus · Tobias Schnabel
[ Paper]  [ Slides] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #184
Efficient Identification in Linear Structural Causal Models with Instrumental Cutsets
In Probabilistic Methods -- Causal Inference
Daniel Kumor · Bryant Chen · Elias Bareinboim
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #185
Machine Learning Estimation of Heterogeneous Treatment Effects with Instruments
In Probabilistic Methods -- Causal Inference
Vasilis Syrgkanis · Victor Lei · Miruna Oprescu · Maggie Hei · Keith Battocchi · Greg Lewis
[ Paper]  [ Slides] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #186
Identification of Conditional Causal Effects under Markov Equivalence
In Probabilistic Methods -- Causal Inference
Amin Jaber · Jiji Zhang · Elias Bareinboim
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #187
Variance Reduction in Bipartite Experiments through Correlation Clustering
In Probabilistic Methods -- Causal Inference
Jean Pouget-Abadie · Kevin Aydin · Warren Schudy · Kay Brodersen · Vahab Mirrokni
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #188
Generalized Off-Policy Actor-Critic
In Reinforcement Learning and Planning -- Decision and Control
Shangtong Zhang · Wendelin Boehmer · Shimon Whiteson
[ Paper]  [ Slides] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #189
Learner-aware Teaching: Inverse Reinforcement Learning with Preferences and Constraints
In Reinforcement Learning and Planning -- Decision and Control
Sebastian Tschiatschek · Ahana Ghosh · Luis Haug · Rati Devidze · Adish Singla
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #190
Logarithmic Regret for Online Control
In Reinforcement Learning and Planning -- Decision and Control
Naman Agarwal · Elad Hazan · Karan Singh
[ Paper]  [ Slides] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #191
Adaptive Auxiliary Task Weighting for Reinforcement Learning
In Reinforcement Learning and Planning -- Decision and Control
Xingyu Lin · Harjatin Baweja · George Kantor · David Held
[ Paper]  [ Poster]  [ Slides] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #192
A Meta-MDP Approach to Exploration for Lifelong Reinforcement Learning
In Reinforcement Learning and Planning -- Exploration
Francisco Garcia · Philip Thomas
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #193
Limiting Extrapolation in Linear Approximate Value Iteration
In Reinforcement Learning and Planning -- Exploration
Andrea Zanette · Alessandro Lazaric · Mykel J Kochenderfer · Emma Brunskill
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #194
Propagating Uncertainty in Reinforcement Learning via Wasserstein Barycenters
In Reinforcement Learning and Planning -- Exploration
Alberto Maria Metelli · Amarildo Likmeta · Marcello Restelli
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #195
Provably Efficient Q-Learning with Low Switching Cost
In Reinforcement Learning and Planning -- Exploration
Yu Bai · Tengyang Xie · Nan Jiang · Yu-Xiang Wang
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #196
Regret Bounds for Learning State Representations in Reinforcement Learning
In Reinforcement Learning and Planning -- Exploration
Ronald Ortner · Matteo Pirotta · Alessandro Lazaric · Ronan Fruit · Odalric-Ambrym Maillard
[ Paper]  [ Slides] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #197
Safe Exploration for Interactive Machine Learning
In Reinforcement Learning and Planning -- Exploration
Matteo Turchetta · Felix Berkenkamp · Andreas Krause
[ Paper]  [ Slides] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #198
Successor Uncertainties: Exploration and Uncertainty in Temporal Difference Learning
In Reinforcement Learning and Planning -- Exploration
David Janz · Jiri Hron · Przemysław Mazur · Katja Hofmann · José Miguel Hernández-Lobato · Sebastian Tschiatschek
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #199
A Family of Robust Stochastic Operators for Reinforcement Learning
In Reinforcement Learning and Planning -- Markov Decision Processes
Yingdong Lu · Mark Squillante · Chai Wah Wu
[ Paper]  [ Slides] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #200
A Unified Bellman Optimality Principle Combining Reward Maximization and Empowerment
In Reinforcement Learning and Planning -- Markov Decision Processes
Felix Leibfried · Sergio Pascual-Díaz · Jordi Grau-Moya
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #201
Finite-Sample Analysis for SARSA with Linear Function Approximation
In Reinforcement Learning and Planning -- Markov Decision Processes
Shaofeng Zou · Tengyu Xu · Yingbin Liang
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #202
Maximum Expected Hitting Cost of a Markov Decision Process and Informativeness of Rewards
In Reinforcement Learning and Planning -- Markov Decision Processes
Falcon Dai · Matthew Walter
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #203
Non-Asymptotic Gap-Dependent Regret Bounds for Tabular MDPs
In Reinforcement Learning and Planning -- Markov Decision Processes
Max Simchowitz · Kevin Jamieson
[ Paper]  [ Slides] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #204
Regret Minimization for Reinforcement Learning with Vectorial Feedback and Complex Objectives
In Reinforcement Learning and Planning -- Markov Decision Processes
Wang Chi Cheung
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #205
Sampling Networks and Aggregate Simulation for Online POMDP Planning
In Reinforcement Learning and Planning -- Markov Decision Processes
Hao(Jackson) Cui · Roni Khardon
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #206
Two Time-scale Off-Policy TD Learning: Non-asymptotic Analysis over Markovian Samples
In Reinforcement Learning and Planning -- Markov Decision Processes
Tengyu Xu · Shaofeng Zou · Yingbin Liang
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #207
Value Function in Frequency Domain and the Characteristic Value Iteration Algorithm
In Reinforcement Learning and Planning -- Markov Decision Processes
Amir-massoud Farahmand
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #208
Addressing Sample Complexity in Visual Tasks Using HER and Hallucinatory GANs
In Reinforcement Learning and Planning -- Navigation
Himanshu Sahni · Toby Buckley · Pieter Abbeel · Ilya Kuzovkin
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #209
Chasing Ghosts: Instruction Following as Bayesian State Tracking
In Reinforcement Learning and Planning -- Navigation
Peter Anderson · Ayush Shrivastava · Devi Parikh · Dhruv Batra · Stefan Lee
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #210
(Nearly) Efficient Algorithms for the Graph Matching Problem on Correlated Random Graphs
In Theory -- Computational Complexity
Boaz Barak · Chi-Ning Chou · Zhixian Lei · Tselil Schramm · Yueqi Sheng
[ Paper]  [ Slides] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #211
The Parameterized Complexity of Cascading Portfolio Scheduling
In Theory -- Computational Complexity
Eduard Eiben · Robert Ganian · Iyad Kanj · Stefan Szeider
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #212
ADDIS: an adaptive discarding algorithm for online FDR control with conservative nulls
In Theory -- Frequentist Statistics
Jinjin Tian · Aaditya Ramdas
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #213
Conformal Prediction Under Covariate Shift
In Theory -- Frequentist Statistics
Ryan Tibshirani · Rina Barber · Emmanuel Candes · Aaditya Ramdas
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #214
Approximation Ratios of Graph Neural Networks for Combinatorial Problems
In Theory -- Hardness of Learning and Approximations
Ryoma Sato · Makoto Yamada · Hisashi Kashima
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #215
Deep ReLU Networks Have Surprisingly Few Activation Patterns
In Theory -- Hardness of Learning and Approximations
Boris Hanin · David Rolnick
[ Paper]  [ Slides] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #216
Efficient Approximation of Deep ReLU Networks for Functions on Low Dimensional Manifolds
In Theory -- Hardness of Learning and Approximations
Minshuo Chen · Haoming Jiang · Wenjing Liao · Tuo Zhao
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #217
Efficient Deep Approximation of GMMs
In Theory -- Hardness of Learning and Approximations
Shirin Jalali · Carl Nuzman · Iraj Saniee
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #218
Universal Invariant and Equivariant Graph Neural Networks
In Theory -- Hardness of Learning and Approximations
Nicolas Keriven · Gabriel Peyré
[ Paper]  [ Slides] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #219
Control Batch Size and Learning Rate to Generalize Well: Theoretical and Empirical Evidence
In Theory -- Learning Theory
Fengxiang He · Tongliang Liu · Dacheng Tao
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #220
Data-dependent Sample Complexity of Deep Neural Networks via Lipschitz Augmentation
In Theory -- Learning Theory
Colin Wei · Tengyu Ma
[ Paper]  [ Slides] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #221
Exact inference in structured prediction
In Theory -- Learning Theory
Kevin Bello · Jean Honorio
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #222
Globally optimal score-based learning of directed acyclic graphs in high-dimensions
In Theory -- Learning Theory
Bryon Aragam · Arash Amini · Qing Zhou
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #223
List-decodable Linear Regression
In Theory -- Learning Theory
Sushrut Karmalkar · Adam Klivans · Pravesh Kothari
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #224
On the Calibration of Multiclass Classification with Rejection
In Theory -- Learning Theory
Chenri Ni · Nontawat Charoenphakdee · Junya Honda · Masashi Sugiyama
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #225
On the Hardness of Robust Classification
In Theory -- Learning Theory
Pascale Gourdeau · Varun Kanade · Marta Kwiatkowska · James Worrell
[ Paper]  [ Slides] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #226
Optimal Analysis of Subset-Selection Based L_p Low-Rank Approximation
In Theory -- Learning Theory
Chen Dan · Hong Wang · Hongyang Zhang · Yuchen Zhou · Pradeep Ravikumar
[ Paper]  [ Poster]  [ Slides] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #227
PAC-Bayes under potentially heavy tails
In Theory -- Learning Theory
Matthew Holland
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #228
Quantum Entropy Scoring for Fast Robust Mean Estimation and Improved Outlier Detection
In Theory -- Learning Theory
Yihe Dong · Samuel Hopkins · Jerry Li
[ Paper]  [ Poster] 
Poster
Tue Dec 10 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #229
Uniform convergence may be unable to explain generalization in deep learning
In Theory -- Learning Theory
Vaishnavh Nagarajan · J. Zico Kolter
Break
Tue Dec 10 12:45 PM -- 02:15 PM (PST)
Lunch Break on Your Own
Invited Talk
Tue Dec 10 02:15 PM -- 03:05 PM (PST) @ West Exhibition Hall C + B3
Machine Learning Meets Single-Cell Biology: Insights and Challenges
Dana Pe'er
Invited Talk
Tue Dec 10 03:05 PM -- 03:25 PM (PST) @ West Exhibition Hall C + B3
Test of Time
Break
Tue Dec 10 03:25 PM -- 04:10 PM (PST) @ West and East
Coffee Break
Oral
Tue Dec 10 04:10 PM -- 04:25 PM (PST) @ West Exhibition Hall A
Trajectory of Alternating Direction Method of Multipliers and Adaptive Acceleration
In Track 2 Session 2
Clarice Poon · Jingwei Liang
[ Paper]  [ Slides] 
Oral
Tue Dec 10 04:10 PM -- 04:25 PM (PST) @ West Ballroom C
Scalable Bayesian inference of dendritic voltage via spatiotemporal recurrent state space models
In Track 4 Session 2
Ruoxi Sun · Ian Kinsella · Scott Linderman · Liam Paninski
[ Paper]  [ Slides]  [ Slides] 
Oral
Tue Dec 10 04:10 PM -- 04:25 PM (PST) @ West Ballroom A + B
Causal Confusion in Imitation Learning
In Track 3 Session 2
Pim de Haan · Dinesh Jayaraman · Sergey Levine
Oral
Tue Dec 10 04:10 PM -- 04:25 PM (PST) @ West Exhibition Hall C + B3
Generative Modeling by Estimating Gradients of the Data Distribution
In Track 1 Session 2
Yang Song · Stefano Ermon
[ Paper]  [ Poster] 
Spotlight
Tue Dec 10 04:25 PM -- 04:30 PM (PST) @ West Exhibition Hall A
Asymmetric Valleys: Beyond Sharp and Flat Local Minima
In Track 2 Session 2
Haowei He · Gao Huang · Yang Yuan
Spotlight
Tue Dec 10 04:25 PM -- 04:30 PM (PST) @ West Ballroom C
Scalable Global Optimization via Local Bayesian Optimization
In Track 4 Session 2
David Eriksson · Michael Pearce · Jacob Gardner · Ryan Turner · Matthias Poloczek
[ Paper]  [ Slides]  [ Slides] 
Spotlight
Tue Dec 10 04:25 PM -- 04:30 PM (PST) @ West Ballroom A + B
Imitation Learning from Observations by Minimizing Inverse Dynamics Disagreement
In Track 3 Session 2
Chao Yang · Xiaojian Ma · Wenbing Huang · Fuchun Sun · Huaping Liu · Junzhou Huang · Chuang Gan
[ Paper]  [ Poster]  [ Slides]  [ Slides]  [ 3 min Video] 
Spotlight
Tue Dec 10 04:25 PM -- 04:30 PM (PST) @ West Exhibition Hall C + B3
Learning Hierarchical Priors in VAEs
In Track 1 Session 2
Alexej Klushyn · Nutan Chen · Richard Kurle · Botond Cseke · Patrick van der Smagt
[ Paper]  [ Poster]  [ Slides] 
Spotlight
Tue Dec 10 04:30 PM -- 04:35 PM (PST) @ West Exhibition Hall A
Reducing the variance in online optimization by transporting past gradients
In Track 2 Session 2
Sébastien Arnold · Pierre-Antoine Manzagol · Reza Babanezhad Harikandeh · Ioannis Mitliagkas · Nicolas Le Roux
[ Paper]  [ Poster]  [ Slides]  [ Slides] 
Spotlight
Tue Dec 10 04:30 PM -- 04:35 PM (PST) @ West Ballroom C
Uncertainty on Asynchronous Time Event Prediction
In Track 4 Session 2
Marin Biloš · Bertrand Charpentier · Stephan Günnemann
[ Paper]  [ Poster]  [ Slides] 
Spotlight
Tue Dec 10 04:30 PM -- 04:35 PM (PST) @ West Ballroom A + B
Learning to Control Self-Assembling Morphologies: A Study of Generalization via Modularity
In Track 3 Session 2
Deepak Pathak · Christopher Lu · Trevor Darrell · Phillip Isola · Alexei Efros
[ Paper]  [ Slides] 
Spotlight
Tue Dec 10 04:30 PM -- 04:35 PM (PST) @ West Exhibition Hall C + B3
Implicit Generation and Modeling with Energy Based Models
In Track 1 Session 2
Yilun Du · Igor Mordatch
Spotlight
Tue Dec 10 04:35 PM -- 04:40 PM (PST) @ West Exhibition Hall A
Who is Afraid of Big Bad Minima? Analysis of gradient-flow in spiked matrix-tensor models
In Track 2 Session 2
Stefano Sarao Mannelli · Giulio Biroli · Chiara Cammarota · Florent Krzakala · Lenka Zdeborová
[ Paper]  [ Slides]  [ Slides] 
Spotlight
Tue Dec 10 04:35 PM -- 04:40 PM (PST) @ West Ballroom C
Bayesian Optimization under Heavy-tailed Payoffs
In Track 4 Session 2
Sayak Ray Chowdhury · Aditya Gopalan
[ Paper]  [ Slides]  [ Slides] 
Spotlight
Tue Dec 10 04:35 PM -- 04:40 PM (PST) @ West Ballroom A + B
A Structured Prediction Approach for Generalization in Cooperative Multi-Agent Reinforcement Learning
In Track 3 Session 2
Nicolas Carion · Nicolas Usunier · Gabriel Synnaeve · Alessandro Lazaric
[ Paper]  [ Poster]  [ Slides] 
Spotlight
Tue Dec 10 04:35 PM -- 04:40 PM (PST) @ West Exhibition Hall C + B3
Invertible Convolutional Flow
In Track 1 Session 2
Mahdi Karami · Dale Schuurmans · Jascha Sohl-Dickstein · Laurent Dinh · Daniel Duckworth
[ Paper]  [ Poster]  [ Slides]  [ Slides] 
Spotlight
Tue Dec 10 04:40 PM -- 04:45 PM (PST) @ West Exhibition Hall A
Fast and Provable ADMM for Learning with Generative Priors
In Track 2 Session 2
Fabian Latorre · Armin eftekhari · Volkan Cevher
[ Paper]  [ Poster]  [ Slides] 
Spotlight
Tue Dec 10 04:40 PM -- 04:45 PM (PST) @ West Ballroom C
Variational Bayesian Optimal Experimental Design
In Track 4 Session 2
Adam Foster · Martin Jankowiak · Elias Bingham · Paul Horsfall · Yee Whye Teh · Thomas Rainforth · Noah Goodman
[ Paper]  [ Poster]  [ Slides] 
Spotlight
Tue Dec 10 04:40 PM -- 04:45 PM (PST) @ West Ballroom A + B
Learning Compositional Neural Programs with Recursive Tree Search and Planning
In Track 3 Session 2
Thomas PIERROT · Guillaume Ligner · Scott Reed · Olivier Sigaud · Nicolas Perrin · Alexandre Laterre · David Kas · Karim Beguir · Nando de Freitas
[ Paper]  [ Poster]  [ Slides] 
Spotlight
Tue Dec 10 04:40 PM -- 04:45 PM (PST) @ West Exhibition Hall C + B3
Residual Flows for Invertible Generative Modeling
In Track 1 Session 2
Tian Qi Chen · Jens Behrmann · David Duvenaud · Joern-Henrik Jacobsen
Spotlight
Tue Dec 10 04:45 PM -- 04:50 PM (PST) @ West Exhibition Hall A
Complexity of Highly Parallel Non-Smooth Convex Optimization
In Track 2 Session 2
Sebastien Bubeck · Qijia Jiang · Yin-Tat Lee · Yuanzhi Li · Aaron Sidford
[ Paper]  [ Slides]  [ Slides] 
Spotlight
Tue Dec 10 04:45 PM -- 04:50 PM (PST) @ West Ballroom C
Implicit Posterior Variational Inference for Deep Gaussian Processes
In Track 4 Session 2
Haibin YU · Yizhou Chen · Bryan Kian Hsiang Low · Patrick Jaillet · Zhongxiang Dai
[ Paper]  [ Slides]  [ Slides] 
Spotlight
Tue Dec 10 04:45 PM -- 04:50 PM (PST) @ West Ballroom A + B
Guided Meta-Policy Search
In Track 3 Session 2
Russell Mendonca · Abhishek Gupta · Rosen Kralev · Pieter Abbeel · Sergey Levine · Chelsea Finn
[ Paper]  [ Poster]  [ Slides]  [ Slides]  [ 3 min Video] 
Spotlight
Tue Dec 10 04:45 PM -- 04:50 PM (PST) @ West Exhibition Hall C + B3
Dual Variational Generation for Low Shot Heterogeneous Face Recognition
In Track 1 Session 2
Chaoyou Fu · Xiang Wu · Yibo Hu · Huaibo Huang · Ran He
[ Paper]  [ Poster]  [ Slides] 
Oral
Tue Dec 10 04:50 PM -- 05:05 PM (PST) @ West Exhibition Hall A
Necessary and Sufficient Geometries for Gradient Methods
In Track 2 Session 2
Daniel Levy · John Duchi
[ Paper]  [ Poster] 
Oral
Tue Dec 10 04:50 PM -- 05:05 PM (PST) @ West Ballroom C
Parameter elimination in particle Gibbs sampling
In Track 4 Session 2
Anna Wigren · Riccardo Sven Risuleo · Lawrence Murray · Fredrik Lindsten
Oral
Tue Dec 10 04:50 PM -- 05:05 PM (PST) @ West Ballroom A + B
Using a Logarithmic Mapping to Enable Lower Discount Factors in Reinforcement Learning
In Track 3 Session 2
Harm Van Seijen · Mehdi Fatemi · Arash Tavakoli
[ Paper]  [ Poster] 
Oral
Tue Dec 10 04:50 PM -- 05:05 PM (PST) @ West Exhibition Hall C + B3
HYPE: A Benchmark for Human eYe Perceptual Evaluation of Generative Models
In Track 1 Session 2
Sharon Zhou · Mitchell Gordon · Ranjay Krishna · Austin Narcomey · Li Fei-Fei · Michael Bernstein
[ Paper]  [ Poster] 
Spotlight
Tue Dec 10 05:05 PM -- 05:10 PM (PST) @ West Exhibition Hall A
SySCD: A System-Aware Parallel Coordinate Descent Algorithm
In Track 2 Session 2
Nikolas Ioannou · Celestine Mendler-Dünner · Thomas Parnell
[ Paper]  [ Poster]  [ Slides]  [ Slides] 
Spotlight
Tue Dec 10 05:05 PM -- 05:10 PM (PST) @ West Ballroom C
Divide and Couple: Using Monte Carlo Variational Objectives for Posterior Approximation
In Track 4 Session 2
Justin Domke · Daniel Sheldon
[ Paper]  [ Poster]  [ Slides] 
Spotlight
Tue Dec 10 05:05 PM -- 05:10 PM (PST) @ West Ballroom A + B
Better Exploration with Optimistic Actor Critic
In Track 3 Session 2
Kamil Ciosek · Quan Vuong · Robert Loftin · Katja Hofmann
[ Paper]  [ Slides]  [ Slides] 
Spotlight
Tue Dec 10 05:05 PM -- 05:10 PM (PST) @ West Exhibition Hall C + B3
Adaptive Density Estimation for Generative Models
In Track 1 Session 2
Thomas Lucas · Konstantin Shmelkov · Karteek Alahari · Cordelia Schmid · Jakob Verbeek
[ Paper]  [ Poster]  [ Slides] 
Spotlight
Tue Dec 10 05:10 PM -- 05:15 PM (PST) @ West Exhibition Hall A
Learning Positive Functions with Pseudo Mirror Descent
In Track 2 Session 2
Yingxiang Yang · Haoxiang Wang · Negar Kiyavash · Niao He
Spotlight
Tue Dec 10 05:10 PM -- 05:15 PM (PST) @ West Ballroom C
The Randomized Midpoint Method for Log-Concave Sampling
In Track 4 Session 2
Ruoqi Shen · Yin Tat Lee
[ Paper]  [ Slides]  [ Slides] 
Spotlight
Tue Dec 10 05:10 PM -- 05:15 PM (PST) @ West Ballroom A + B
Robust exploration in linear quadratic reinforcement learning
In Track 3 Session 2
Jack Umenberger · Mina Ferizbegovic · Thomas Schön · Håkan Hjalmarsson
[ Paper]  [ Poster]  [ Slides] 
Spotlight
Tue Dec 10 05:10 PM -- 05:15 PM (PST) @ West Exhibition Hall C + B3
Twin Auxilary Classifiers GAN
In Track 1 Session 2
Mingming Gong · Yanwu Xu · Chunyuan Li · Kun Zhang · Kayhan Batmanghelich
[ Paper]  [ Slides]  [ Slides] 
Spotlight
Tue Dec 10 05:15 PM -- 05:20 PM (PST) @ West Exhibition Hall A
UniXGrad: A Universal, Adaptive Algorithm with Optimal Guarantees for Constrained Optimization
In Track 2 Session 2
Ali Kavis · Kfir Y. Levy · Francis Bach · Volkan Cevher
[ Paper]  [ Slides]  [ Slides] 
Spotlight
Tue Dec 10 05:15 PM -- 05:20 PM (PST) @ West Ballroom C
Poisson-Minibatching for Gibbs Sampling with Convergence Rate Guarantees
In Track 4 Session 2
Ruqi Zhang · Christopher De Sa
[ Paper]  [ Poster]  [ Slides] 
Spotlight
Tue Dec 10 05:15 PM -- 05:20 PM (PST) @ West Ballroom A + B
Tight Regret Bounds for Model-Based Reinforcement Learning with Greedy Policies
In Track 3 Session 2
Yonathan Efroni · Nadav Merlis · Mohammad Ghavamzadeh · Shie Mannor
[ Paper]  [ Poster]  [ Slides] 
Spotlight
Tue Dec 10 05:15 PM -- 05:20 PM (PST) @ West Exhibition Hall C + B3
Adversarial Fisher Vectors for Unsupervised Representation Learning
In Track 1 Session 2
Shuangfei Zhai · Walter Talbott · Carlos Guestrin · Joshua Susskind
[ Paper]  [ Poster]  [ Slides] 
Spotlight
Tue Dec 10 05:20 PM -- 05:25 PM (PST) @ West Exhibition Hall A
Sinkhorn Barycenters with Free Support via Frank-Wolfe Algorithm
In Track 2 Session 2
Giulia Luise · Saverio Salzo · Massimiliano Pontil · Carlo Ciliberto
[ Paper]  [ Slides]  [ Slides] 
Spotlight
Tue Dec 10 05:20 PM -- 05:25 PM (PST) @ West Ballroom C
Stochastic Proximal Langevin Algorithm: Potential Splitting and Nonasymptotic Rates
In Track 4 Session 2
Adil Salim · Dmitry Kovalev · Peter Richtarik
[ Paper]  [ Poster]  [ Slides] 
Spotlight
Tue Dec 10 05:20 PM -- 05:25 PM (PST) @ West Ballroom A + B
Hindsight Credit Assignment
In Track 3 Session 2
Anna Harutyunyan · Will Dabney · Thomas Mesnard · Mohammad Gheshlaghi Azar · Bilal Piot · Nicolas Heess · Hado van Hasselt · Gregory Wayne · Satinder Singh · Doina Precup · Remi Munos
Spotlight
Tue Dec 10 05:20 PM -- 05:25 PM (PST) @ West Exhibition Hall C + B3
Emergence of Object Segmentation in Perturbed Generative Models
In Track 1 Session 2
Adam Bielski · Paolo Favaro
[ Paper]  [ Poster]  [ Slides] 
Spotlight
Tue Dec 10 05:25 PM -- 05:30 PM (PST) @ West Exhibition Hall A
Learning dynamic polynomial proofs
In Track 2 Session 2
Alhussein Fawzi · Mateusz Malinowski · Hamza Fawzi · Omar Fawzi
[ Paper]  [ Poster]  [ Slides] 
Spotlight
Tue Dec 10 05:25 PM -- 05:30 PM (PST) @ West Ballroom C
Stochastic Runge-Kutta Accelerates Langevin Monte Carlo and Beyond
In Track 4 Session 2
Xuechen (Chen) Li · Denny Wu · Lester Mackey · Murat Erdogdu
[ Paper]  [ Slides]  [ Slides] 
Spotlight
Tue Dec 10 05:25 PM -- 05:30 PM (PST) @ West Ballroom A + B
Weight Agnostic Neural Networks
In Track 3 Session 2
Adam Gaier · David Ha
[ Paper]  [ Slides]  [ Slides] 
Spotlight
Tue Dec 10 05:25 PM -- 05:30 PM (PST) @ West Exhibition Hall C + B3
Compression with Flows via Local Bits-Back Coding
In Track 1 Session 2
Jonathan Ho · Evan Lohn · Pieter Abbeel
[ Paper]  [ Slides]  [ Slides] 
Demonstration
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #801
exBERT: A Visual Analysis Tool to Explain BERT's Learned Representations
In Demos Tue
Benjamin Hoover · Hendrik Strobelt · Sebastian Gehrmann
Demonstration
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #802
Streamlit, a new app framework for machine learning tools
In Demos Tue
Adrien Treuille · Amanda Kelly
Demonstration
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #803
Discovering Neural Wirings Neural Network Visualizer
In Demos Tue
Alvaro Herrasti · Mitchell Wortsman
Demonstration
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #804
"How can this Paper get in?" - A game to advise researchers when writing for a top AI conference
In Demos Tue
Aabhas Sharma · Narendra Nath Joshi · Michael Muller · Casey Dugan
Demonstration
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #805___1
Robot-Assisted Hair-Brushing
In Demos Tue
Eura Shin · Hejia Zhang · Rey J Pocius · Nathaniel Dennler · Heather Culbertson · Naghmeh Zamani · Stefanos Nikolaidis
Demonstration
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #805___0
Toronto Annotation Suite
In Demos Tue
Amlan Kar · Sanja Fidler · Jun Gao · Seung Wook Kim · Huan Ling
Demonstration
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #806
Learning Machines can Curl - Adaptive Deep Reinforcement Learning enables the robot Curly to win against human players in an icy world
In Demos Tue
Dong-Ok Won · Sang-Hoon Lee · Klaus-Robert Müller · Seong-Whan Lee
Demonstration
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #807
Human Gesture Recognition using Spiking Input on Akida Neuromorphic Platform
In Demos Tue
Sounak Dey · Arijit Mukherjee · Gilles BEZARD · Douglas McLelland
Demonstration
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #808
GENO -- Optimization for Classical Machine Learning Made Fast and Easy
In Demos Tue
Sören Laue · Matthias Mitterreiter · Joachim Giesen
Demonstration
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #810
SCC: Deep Reinforcement Learning Agent plays StarCraft II at competitive human level
In Demos Tue
XJ Wang · Peng Peng
Demonstration
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #811
AI in Two-sided Ride-sharing Marketplace
In Demos Tue
Zhiwei Qin · Shikai Luo · lingyu zhang · yan jiao · Xiaocheng Tang · Lulu Zhang · hongtu zhu · Jieping Ye
Demonstration
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #812
NNgen: A Model-Specific Hardware Synthesis Compiler for Deep Neural Network
In Demos Tue
Shinya Takamaeda-Yamazaki · Shinya Fujisawa · Shuichi Fujisaki
Demonstration
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #813
Realtime Modeling and Anomaly Detection in Multivariate Data Streams
In Demos Tue
Christopher Hannon · Andrey Lokhov · Deep Deka
Demonstration
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #814
Empathy based Affective Portrait Painter
In Demos Tue
Steve DiPaola · Ozge Nilay YALCIN · Nouf Abukhodair
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #1
D-VAE: A Variational Autoencoder for Directed Acyclic Graphs
In Algorithms -- AutoML
Muhan Zhang · Shali Jiang · Zhicheng Cui · Roman Garnett · Yixin Chen
[ Paper]  [ Slides] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #2
DATA: Differentiable ArchiTecture Approximation
In Algorithms -- AutoML
Jianlong Chang · xinbang zhang · Yiwen Guo · GAOFENG MENG · SHIMING XIANG · Chunhong Pan
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #3
DetNAS: Backbone Search for Object Detection
In Algorithms -- AutoML
Yukang Chen · Tong Yang · Xiangyu Zhang · GAOFENG MENG · Xinyu Xiao · Jian Sun
[ Paper]  [ Slides] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #4
Discovering Neural Wirings
In Algorithms -- AutoML
Mitchell Wortsman · Ali Farhadi · Mohammad Rastegari
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #5
Fast AutoAugment
In Algorithms -- AutoML
Sungbin Lim · Ildoo Kim · Taesup Kim · Chiheon Kim · Sungwoong Kim
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #6
Meta-Surrogate Benchmarking for Hyperparameter Optimization
In Algorithms -- AutoML
Aaron Klein · Zhenwen Dai · Frank Hutter · Neil Lawrence · Javier González
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #7
NAT: Neural Architecture Transformer for Accurate and Compact Architectures
In Algorithms -- AutoML
Yong Guo · Yin Zheng · Mingkui Tan · Qi Chen · Jian Chen · Peilin Zhao · Junzhou Huang
[ Paper]  [ Poster]  [ Slides] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #8
Network Pruning via Transformable Architecture Search
In Algorithms -- AutoML
Xuanyi Dong · Yi Yang
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #9
Scalable Global Optimization via Local Bayesian Optimization
In Algorithms -- AutoML
David Eriksson · Michael Pearce · Jacob Gardner · Ryan Turner · Matthias Poloczek
[ Paper]  [ Slides] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #10
XNAS: Neural Architecture Search with Expert Advice
In Algorithms -- AutoML
Niv Nayman · Asaf Noy · Tal Ridnik · Itamar Friedman · Rong Jin · Lihi Zelnik
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #11
Bayesian Optimization under Heavy-tailed Payoffs
In Algorithms -- Bandit Algorithms
Sayak Ray Chowdhury · Aditya Gopalan
[ Paper]  [ Slides] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #12
Connections Between Mirror Descent, Thompson Sampling and the Information Ratio
In Algorithms -- Bandit Algorithms
Julian Zimmert · Tor Lattimore
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #13
Individual Regret in Cooperative Nonstochastic Multi-Armed Bandits
In Algorithms -- Bandit Algorithms
Yogev Bar-On · Yishay Mansour
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #14
Learning Multiple Markov Chains via Adaptive Allocation
In Algorithms -- Bandit Algorithms
Mohammad Sadegh Talebi · Odalric-Ambrym Maillard
[ Paper]  [ Slides] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #15
Linear Stochastic Bandits Under Safety Constraints
In Algorithms -- Bandit Algorithms
Sanae Amani · Mahnoosh Alizadeh · Christos Thrampoulidis
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #16
Personalizing Many Decisions with High-Dimensional Covariates
In Algorithms -- Bandit Algorithms
Nima Hamidi · Mohsen Bayati · Kapil Gupta
[ Paper]  [ Slides] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #17
Non-Asymptotic Pure Exploration by Solving Games
In Algorithms -- Bandit Algorithms
Rémy Degenne · Wouter Koolen · Pierre Ménard
[ Paper]  [ Slides] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #18
Online EXP3 Learning in Adversarial Bandits with Delayed Feedback
In Algorithms -- Bandit Algorithms
Ilai Bistritz · Zhengyuan Zhou · Xi Chen · Nicholas Bambos · Jose Blanchet
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #19
Optimal Best Markovian Arm Identification with Fixed Confidence
In Algorithms -- Bandit Algorithms
Vrettos Moulos
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #20
Oracle-Efficient Algorithms for Online Linear Optimization with Bandit Feedback
In Algorithms -- Bandit Algorithms
Shinji Ito · Daisuke Hatano · Hanna Sumita · Kei Takemura · Takuro Fukunaga · Naonori Kakimura · Ken-Ichi Kawarabayashi
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #21
Regret Bounds for Thompson Sampling in Episodic Restless Bandit Problems
In Algorithms -- Bandit Algorithms
Young H Jung · Ambuj Tewari
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #22
Thresholding Bandit with Optimal Aggregate Regret
In Algorithms -- Bandit Algorithms
Chao Tao · Saúl Blanco · Jian Peng · Yuan Zhou
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #23
Weighted Linear Bandits for Non-Stationary Environments
In Algorithms -- Bandit Algorithms
Yoan Russac · Claire Vernade · Olivier Cappé
[ Paper]  [ Slides] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #24
A Linearly Convergent Proximal Gradient Algorithm for Decentralized Optimization
In Algorithms -- Large Scale Learning
Sulaiman Alghunaim · Kun Yuan · Ali H Sayed
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #25
Asymptotics for Sketching in Least Squares Regression
In Algorithms -- Large Scale Learning
Edgar Dobriban · Sifan Liu
[ Paper]  [ Slides] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #26
DETOX: A Redundancy-based Framework for Faster and More Robust Gradient Aggregation
In Algorithms -- Large Scale Learning
Shashank Rajput · Hongyi Wang · Zachary Charles · Dimitris Papailiopoulos
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #27
Large-scale optimal transport map estimation using projection pursuit
In Algorithms -- Large Scale Learning
Cheng Meng · Yuan Ke · Jingyi Zhang · Mengrui Zhang · Wenxuan Zhong · Ping Ma
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #28
Locality-Sensitive Hashing for f-Divergences: Mutual Information Loss and Beyond
In Algorithms -- Large Scale Learning
Lin Chen · Hossein Esfandiari · Gang Fu · Vahab Mirrokni
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #29
Massively scalable Sinkhorn distances via the Nyström method
In Algorithms -- Large Scale Learning
Jason Altschuler · Francis Bach · Alessandro Rudi · Jonathan Niles-Weed
[ Paper]  [ Slides] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #30
On the Global Convergence of (Fast) Incremental Expectation Maximization Methods
In Algorithms -- Large Scale Learning
Belhal Karimi · Hoi-To Wai · Eric Moulines · Marc Lavielle
[ Paper]  [ Slides] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #31
Optimal Sparsity-Sensitive Bounds for Distributed Mean Estimation
In Algorithms -- Large Scale Learning
zengfeng Huang · Ziyue Huang · Yilei WANG · Ke Yi
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #32
Qsparse-local-SGD: Distributed SGD with Quantization, Sparsification and Local Computations
In Algorithms -- Large Scale Learning
Debraj Basu · Deepesh Data · Can Karakus · Suhas Diggavi
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #33
Random Projections with Asymmetric Quantization
In Algorithms -- Large Scale Learning
Xiaoyun Li · Ping Li
[ Paper]  [ Slides] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #34
Re-randomized Densification for One Permutation Hashing and Bin-wise Consistent Weighted Sampling
In Algorithms -- Large Scale Learning
Ping Li · Xiaoyun Li · Cun-Hui Zhang
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #35
Robust and Communication-Efficient Collaborative Learning
In Algorithms -- Large Scale Learning
Amirhossein Reisizadeh · Hossein Taheri · Aryan Mokhtari · Hamed Hassani · Ramtin Pedarsani
[ Paper]  [ Poster]  [ Slides] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #36
Sampled Softmax with Random Fourier Features
In Algorithms -- Large Scale Learning
Ankit Singh Rawat · Jiecao Chen · Felix Xinnan Yu · Ananda Theertha Suresh · Sanjiv Kumar
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #37
Extreme Classification in Log Memory using Count-Min Sketch: A Case Study of Amazon Search with 50M Products
In Algorithms -- Large Scale Learning
Tharun Kumar Reddy Medini · Qixuan Huang · Yiqiu Wang · Vijai Mohan · Anshumali Shrivastava
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #38
Sliced Gromov-Wasserstein
In Algorithms -- Large Scale Learning
Titouan Vayer · Rémi Flamary · Nicolas Courty · Romain Tavenard · Laetitia Chapel
[ Paper]  [ Slides] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #39
SySCD: A System-Aware Parallel Coordinate Descent Algorithm
In Algorithms -- Large Scale Learning
Nikolas Ioannou · Celestine Mendler-Dünner · Thomas Parnell
[ Paper]  [ Poster]  [ Slides] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #40
GPipe: Efficient Training of Giant Neural Networks using Pipeline Parallelism
In Algorithms -- Large Scale Learning
Yanping Huang · Youlong Cheng · Ankur Bapna · Orhan Firat · Dehao Chen · Mia Chen · HyoukJoong Lee · Jiquan Ngiam · Quoc V Le · Yonghui Wu · zhifeng Chen
[ Paper]  [ Poster]  [ Slides] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #41
Adaptive Gradient-Based Meta-Learning Methods
In Algorithms -- Meta-Learning
Misha Khodak · Maria-Florina Balcan · Ameet Talwalkar
[ Paper]  [ Poster]  [ Slides] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #42
Guided Meta-Policy Search
In Algorithms -- Meta-Learning
Russell Mendonca · Abhishek Gupta · Rosen Kralev · Pieter Abbeel · Sergey Levine · Chelsea Finn
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #43
Learning to Propagate for Graph Meta-Learning
In Algorithms -- Meta-Learning
LU LIU · Tianyi Zhou · Guodong Long · Jing Jiang · Chengqi Zhang
[ Paper]  [ Poster]  [ Slides] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #44
Meta Learning with Relational Information for Short Sequences
In Algorithms -- Meta-Learning
Yujia Xie · Haoming Jiang · Feng Liu · Tuo Zhao · Hongyuan Zha
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #45
Meta-Curvature
In Algorithms -- Meta-Learning
Eunbyung Park · Junier Oliva
[ Paper]  [ Slides] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #46
Meta-Learning Representations for Continual Learning
In Algorithms -- Meta-Learning
Khurram Javed · Martha White
[ Paper]  [ Poster]  [ Slides] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #47
Meta-Learning with Implicit Gradients
In Algorithms -- Meta-Learning
Aravind Rajeswaran · Chelsea Finn · Sham Kakade · Sergey Levine
[ Paper]  [ Slides] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #48
Meta-Weight-Net: Learning an Explicit Mapping For Sample Weighting
In Algorithms -- Meta-Learning
Jun Shu · Qi Xie · Lixuan Yi · Qian Zhao · Sanping Zhou · Zongben Xu · Deyu Meng
[ Paper] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #49
Self-Supervised Generalisation with Meta Auxiliary Learning
In Algorithms -- Meta-Learning
Shikun Liu · Andrew Davison · Edward Johns
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #50
Iterative Least Trimmed Squares for Mixed Linear Regression
In Algorithms -- Regression
Yanyao Shen · Sujay Sanghavi
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #51
Kalman Filter, Sensor Fusion, and Constrained Regression: Equivalences and Insights
In Algorithms -- Regression
Maria Jahja · David Farrow · Roni Rosenfeld · Ryan Tibshirani
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #52
Multivariate Distributionally Robust Convex Regression under Absolute Error Loss
In Algorithms -- Regression
Jose Blanchet · Peter W Glynn · Jun Yan · Zhengqing Zhou
[ Paper]  [ Slides] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #53
Optimal Sketching for Kronecker Product Regression and Low Rank Approximation
In Algorithms -- Regression
Huaian Diao · Rajesh Jayaram · Zhao Song · Wen Sun · David Woodruff
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #54
Deep Set Prediction Networks
In Algorithms -- Structured Prediction
Yan Zhang · Jonathon Hare · Adam Prugel-Bennett
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #55
Learning Positive Functions with Pseudo Mirror Descent
In Algorithms -- Structured Prediction
Yingxiang Yang · Haoxiang Wang · Negar Kiyavash · Niao He
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #56
Localized Structured Prediction
In Algorithms -- Structured Prediction
Carlo Ciliberto · Francis Bach · Alessandro Rudi
[ Paper]  [ Slides] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #57
Online Markov Decoding: Lower Bounds and Near-Optimal Approximation Algorithms
In Algorithms -- Structured Prediction
Vikas Garg · Tamar Pichkhadze
[ Paper]  [ Slides] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #58
Retrosynthesis Prediction with Conditional Graph Logic Network
In Algorithms -- Structured Prediction
Hanjun Dai · Chengtao Li · Connor Coley · Bo Dai · Le Song
[ Paper]  [ Poster]  [ Slides] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #59
DeepUSPS: Deep Robust Unsupervised Saliency Prediction via Self-supervision
In Algorithms -- Unsupervised Learning
Tam Nguyen · Maximilian Dax · Chaithanya Kumar Mummadi · Nhung Ngo · Thi Hoai Phuong Nguyen · Zhongyu Lou · Thomas Brox
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #60
Emergence of Object Segmentation in Perturbed Generative Models
In Algorithms -- Unsupervised Learning
Adam Bielski · Paolo Favaro
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #61
On Adversarial Mixup Resynthesis
In Algorithms -- Unsupervised Learning
Christopher Beckham · Sina Honari · Alex Lamb · Vikas Verma · Farnoosh Ghadiri · R Devon Hjelm · Yoshua Bengio · Chris Pal
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #62
q-means: A quantum algorithm for unsupervised machine learning
In Algorithms -- Unsupervised Learning
Iordanis Kerenidis · Jonas Landman · Alessandro Luongo · Anupam Prakash
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #63
Scalable Gromov-Wasserstein Learning for Graph Partitioning and Matching
In Algorithms -- Unsupervised Learning
Hongteng Xu · Dixin Luo · Lawrence Carin
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #64
Symmetry-Based Disentangled Representation Learning requires Interaction with Environments
In Algorithms -- Unsupervised Learning
Hugo Caselles-Dupré · Michael Garcia Ortiz · David Filliat
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #65
Deep Structured Prediction for Facial Landmark Detection
In Applications -- Body Pose, Face, and Gesture Analysis
Lisha Chen · Hui Su · Qiang Ji
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #66
Dual Variational Generation for Low Shot Heterogeneous Face Recognition
In Applications -- Body Pose, Face, and Gesture Analysis
Chaoyou Fu · Xiang Wu · Yibo Hu · Huaibo Huang · Ran He
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #67
Face Reconstruction from Voice using Generative Adversarial Networks
In Applications -- Body Pose, Face, and Gesture Analysis
Yandong Wen · Bhiksha Raj · Rita Singh
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #68
Learning Temporal Pose Estimation from Sparsely-Labeled Videos
In Applications -- Body Pose, Face, and Gesture Analysis
Gedas Bertasius · Christoph Feichtenhofer · Du Tran · Jianbo Shi · Lorenzo Torresani
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #69
Multi-label Co-regularization for Semi-supervised Facial Action Unit Recognition
In Applications -- Body Pose, Face, and Gesture Analysis
Xuesong Niu · Hu Han · Shiguang Shan · Xilin Chen
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #70
Sim2real transfer learning for 3D human pose estimation: motion to the rescue
In Applications -- Body Pose, Face, and Gesture Analysis
Carl Doersch · Andrew Zisserman
[ Paper]  [ Slides] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #71
Adaptive Density Estimation for Generative Models
In Deep Learning -- Generative Models
Thomas Lucas · Konstantin Shmelkov · Karteek Alahari · Cordelia Schmid · Jakob Verbeek
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #72
Adversarial Fisher Vectors for Unsupervised Representation Learning
In Deep Learning -- Generative Models
Shuangfei Zhai · Walter Talbott · Carlos Guestrin · Joshua Susskind
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #73
Co-Generation with GANs using AIS based HMC
In Deep Learning -- Generative Models
Tiantian Fang · Alex Schwing
[ Paper]  [ Slides] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #74
Compression with Flows via Local Bits-Back Coding
In Deep Learning -- Generative Models
Jonathan Ho · Evan Lohn · Pieter Abbeel
[ Paper]  [ Slides] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #75
Direct Optimization through $\arg \max$ for Discrete Variational Auto-Encoder
In Deep Learning -- Generative Models
Guy Lorberbom · Andreea Gane · Tommi Jaakkola · Tamir Hazan
[ Paper]  [ Slides] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #76
Fast and Provable ADMM for Learning with Generative Priors
In Deep Learning -- Generative Models
Fabian Latorre · Armin eftekhari · Volkan Cevher
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #77
Generative Modeling by Estimating Gradients of the Data Distribution
In Deep Learning -- Generative Models
Yang Song · Stefano Ermon
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #78
HYPE: A Benchmark for Human eYe Perceptual Evaluation of Generative Models
In Deep Learning -- Generative Models
Sharon Zhou · Mitchell Gordon · Ranjay Krishna · Austin Narcomey · Li Fei-Fei · Michael Bernstein
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #79
Implicit Generation and Modeling with Energy Based Models
In Deep Learning -- Generative Models
Yilun Du · Igor Mordatch
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #80
Invertible Convolutional Flow
In Deep Learning -- Generative Models
Mahdi Karami · Dale Schuurmans · Jascha Sohl-Dickstein · Laurent Dinh · Daniel Duckworth
[ Paper]  [ Poster]  [ Slides] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #81
Latent Ordinary Differential Equations for Irregularly-Sampled Time Series
In Deep Learning -- Generative Models
Yulia Rubanova · Tian Qi Chen · David Duvenaud
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #82
MaCow: Masked Convolutional Generative Flow
In Deep Learning -- Generative Models
Xuezhe Ma · Xiang Kong · Shanghang Zhang · Eduard Hovy
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #83
Mining GOLD Samples for Conditional GANs
In Deep Learning -- Generative Models
Sangwoo Mo · Chiheon Kim · Sungwoong Kim · Minsu Cho · Jinwoo Shin
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #84
Learning Non-Convergent Non-Persistent Short-Run MCMC Toward Energy-Based Model
In Deep Learning -- Generative Models
Erik Nijkamp · Mitch Hill · Song-Chun Zhu · Ying Nian Wu
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #85
Residual Flows for Invertible Generative Modeling
In Deep Learning -- Generative Models
Tian Qi Chen · Jens Behrmann · David Duvenaud · Joern-Henrik Jacobsen
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #86
Time-series Generative Adversarial Networks
In Deep Learning -- Generative Models
Jinsung Yoon · Daniel Jarrett · Mihaela van der Schaar
[ Paper]  [ Slides] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #87
Twin Auxilary Classifiers GAN
In Deep Learning -- Generative Models
Mingming Gong · Yanwu Xu · Chunyuan Li · Kun Zhang · Kayhan Batmanghelich
[ Paper]  [ Slides] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #88
Constrained deep neural network architecture search for IoT devices accounting for hardware calibration
In Deep Learning -- Optimization for Deep Networks
Florian Scheidegger · Luca Benini · Costas Bekas · A. Cristiano I. Malossi
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #89
Implicit Regularization of Discrete Gradient Dynamics in Linear Neural Networks
In Deep Learning -- Optimization for Deep Networks
Gauthier Gidel · Francis Bach · Simon Lacoste-Julien
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #90
In-Place Zero-Space Memory Protection for CNN
In Deep Learning -- Optimization for Deep Networks
Hui Guan · Lin Ning · Zhen Lin · Xipeng Shen · Huiyang Zhou · Seung-Hwan Lim
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #91
Large Scale Structure of Neural Network Loss Landscapes
In Deep Learning -- Optimization for Deep Networks
Stanislav Fort · Stanislaw Jastrzebski
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #92
Learning and Generalization in Overparameterized Neural Networks, Going Beyond Two Layers
In Deep Learning -- Optimization for Deep Networks
Zeyuan Allen-Zhu · Yuanzhi Li · Yingyu Liang
[ Paper]  [ Slides] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #93
Limitations of the empirical Fisher approximation for natural gradient descent
In Deep Learning -- Optimization for Deep Networks
Frederik Kunstner · Philipp Hennig · Lukas Balles
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #94
Maximum Mean Discrepancy Gradient Flow
In Deep Learning -- Optimization for Deep Networks
Michael Arbel · Anna Korba · Adil Salim · Arthur Gretton
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #95
On Lazy Training in Differentiable Programming
In Deep Learning -- Optimization for Deep Networks
Lénaïc Chizat · Edouard Oyallon · Francis Bach
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #96
Reducing the variance in online optimization by transporting past gradients
In Deep Learning -- Optimization for Deep Networks
Sébastien Arnold · Pierre-Antoine Manzagol · Reza Babanezhad Harikandeh · Ioannis Mitliagkas · Nicolas Le Roux
[ Paper]  [ Poster]  [ Slides] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #97
Tight Sample Complexity of Learning One-hidden-layer Convolutional Neural Networks
In Deep Learning -- Optimization for Deep Networks
Yuan Cao · Quanquan Gu
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #98
Understanding and Improving Layer Normalization
In Deep Learning -- Optimization for Deep Networks
Jingjing Xu · Xu Sun · Zhiyuan Zhang · Guangxiang Zhao · Junyang Lin
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #99
LCA: Loss Change Allocation for Neural Network Training
In Deep Learning -- Optimization for Deep Networks
Janice Lan · Rosanne Liu · Hattie Zhou · Jason Yosinski
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #100
A Communication Efficient Stochastic Multi-Block Alternating Direction Method of Multipliers
In Optimization -- Convex Optimization
Hao Yu
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #101
A First-Order Algorithmic Framework for Wasserstein Distributionally Robust Logistic Regression
In Optimization -- Convex Optimization
Jiajin Li · SEN HUANG · Anthony Man-Cho So
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #102
Acceleration via Symplectic Discretization of High-Resolution Differential Equations
In Optimization -- Convex Optimization
Bin Shi · Simon Du · Weijie Su · Michael Jordan
[ Paper]  [ Slides] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #103
An Accelerated Decentralized Stochastic Proximal Algorithm for Finite Sums
In Optimization -- Convex Optimization
Hadrien Hendrikx · Francis Bach · Laurent Massoulié
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #104
An adaptive Mirror-Prox method for variational inequalities with singular operators
In Optimization -- Convex Optimization
Kimon Antonakopoulos · Veronica Belmega · Panayotis Mertikopoulos
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #105
Blended Matching Pursuit
In Optimization -- Convex Optimization
Cyrille Combettes · Sebastian Pokutta
[ Paper]  [ Slides] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #106
Communication-Efficient Distributed Learning via Lazily Aggregated Quantized Gradients
In Optimization -- Convex Optimization
Jun Sun · Tianyi Chen · Georgios Giannakis · Zaiyue Yang
[ Paper]  [ Slides] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #107
Complexity of Highly Parallel Non-Smooth Convex Optimization
In Optimization -- Convex Optimization
Sebastien Bubeck · Qijia Jiang · Yin-Tat Lee · Yuanzhi Li · Aaron Sidford
[ Paper]  [ Slides] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #108
Efficient Symmetric Norm Regression via Linear Sketching
In Optimization -- Convex Optimization
Zhao Song · Ruosong Wang · Lin Yang · Hongyang Zhang · Peilin Zhong
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #109
General Proximal Incremental Aggregated Gradient Algorithms: Better and Novel Results under General Scheme
In Optimization -- Convex Optimization
Tao Sun · Yuejiao Sun · Dongsheng Li · Qing Liao
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #110
Interior-Point Methods Strike Back: Solving the Wasserstein Barycenter Problem
In Optimization -- Convex Optimization
DongDong Ge · Haoyue Wang · Zikai Xiong · Yinyu Ye
[ Paper]  [ Slides] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #111
Necessary and Sufficient Geometries for Gradient Methods
In Optimization -- Convex Optimization
Daniel Levy · John Duchi
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #112
On the Curved Geometry of Accelerated Optimization
In Optimization -- Convex Optimization
Aaron Defazio
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #113
Sinkhorn Barycenters with Free Support via Frank-Wolfe Algorithm
In Optimization -- Convex Optimization
Giulia Luise · Saverio Salzo · Massimiliano Pontil · Carlo Ciliberto
[ Paper]  [ Slides] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #114
Tight Dimension Independent Lower Bound on the Expected Convergence Rate for Diminishing Step Sizes in SGD
In Optimization -- Convex Optimization
Ha Nguyen · Lam Nguyen · Marten van Dijk
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #115
Trajectory of Alternating Direction Method of Multipliers and Adaptive Acceleration
In Optimization -- Convex Optimization
Clarice Poon · Jingwei Liang
[ Paper]  [ Slides] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #116
Asymmetric Valleys: Beyond Sharp and Flat Local Minima
In Optimization -- Non-Convex Optimization
Haowei He · Gao Huang · Yang Yuan
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #117
Beyond Alternating Updates for Matrix Factorization with Inertial Bregman Proximal Gradient Algorithms
In Optimization -- Non-Convex Optimization
Mahesh Chandra Mukkamala · Peter Ochs
[ Paper]  [ Slides] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #118
Efficiently escaping saddle points on manifolds
In Optimization -- Non-Convex Optimization
Christopher Criscitiello · Nicolas Boumal
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #119
Global Convergence of Least Squares EM for Demixing Two Log-Concave Densities
In Optimization -- Non-Convex Optimization
Wei Qian · Yuqian Zhang · Yudong Chen
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #120
Learning dynamic polynomial proofs
In Optimization -- Non-Convex Optimization
Alhussein Fawzi · Mateusz Malinowski · Hamza Fawzi · Omar Fawzi
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #121
Non-asymptotic Analysis of Stochastic Methods for Non-Smooth Non-Convex Regularized Problems
In Optimization -- Non-Convex Optimization
Yi Xu · Rong Jin · Tianbao Yang
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #122
Nonconvex Low-Rank Symmetric Tensor Completion from Noisy Data
In Optimization -- Non-Convex Optimization
Changxiao Cai · Gen Li · H. Vincent Poor · Yuxin Chen
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #123
Painless Stochastic Gradient: Interpolation, Line-Search, and Convergence Rates
In Optimization -- Non-Convex Optimization
Sharan Vaswani · Aaron Mishkin · Issam Laradji · Mark Schmidt · Gauthier Gidel · Simon Lacoste-Julien
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #124
SpiderBoost and Momentum: Faster Variance Reduction Algorithms
In Optimization -- Non-Convex Optimization
Zhe Wang · Kaiyi Ji · Yi Zhou · Yingbin Liang · Vahid Tarokh
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #125
SSRGD: Simple Stochastic Recursive Gradient Descent for Escaping Saddle Points
In Optimization -- Non-Convex Optimization
Zhize Li
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #126
The Landscape of Non-convex Empirical Risk with Degenerate Population Risk
In Optimization -- Non-Convex Optimization
Shuang Li · Gongguo Tang · Michael B Wakin
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #127
Who is Afraid of Big Bad Minima? Analysis of gradient-flow in spiked matrix-tensor models
In Optimization -- Non-Convex Optimization
Stefano Sarao Mannelli · Giulio Biroli · Chiara Cammarota · Florent Krzakala · Lenka Zdeborová
[ Paper]  [ Slides] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #128
Double Quantization for Communication-Efficient Distributed Optimization
In Optimization -- Stochastic Optimization
Yue Yu · Jiaxiang Wu · Longbo Huang
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #129
Optimal Decision Tree with Noisy Outcomes
In Optimization -- Stochastic Optimization
Su Jia · viswanath nagarajan · Fatemeh Navidi · R Ravi
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #130
Optimal Statistical Rates for Decentralised Non-Parametric Regression with Linear Speed-Up
In Optimization -- Stochastic Optimization
Dominic Richards · Patrick Rebeschini
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #131
RSN: Randomized Subspace Newton
In Optimization -- Stochastic Optimization
Robert Gower · Dmitry Kovalev · Felix Lieder · Peter Richtarik
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #132
Towards closing the gap between the theory and practice of SVRG
In Optimization -- Stochastic Optimization
Othmane Sebbouh · Nidham Gazagnadou · Samy Jelassi · Francis Bach · Robert Gower
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #133
UniXGrad: A Universal, Adaptive Algorithm with Optimal Guarantees for Constrained Optimization
In Optimization -- Stochastic Optimization
Ali Kavis · Kfir Y. Levy · Francis Bach · Volkan Cevher
[ Paper]  [ Slides] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #134
Identifying Causal Effects via Context-specific Independence Relations
In Probabilistic Methods -- Causal Inference
Santtu Tikka · Antti Hyttinen · Juha Karvanen
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #135
Integrating Markov processes with structural causal modeling enables counterfactual inference in complex systems
In Probabilistic Methods -- Causal Inference
Robert Ness · Kaushal Paneri · Olga Vitek
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #136
Near-Optimal Reinforcement Learning in Dynamic Treatment Regimes
In Probabilistic Methods -- Causal Inference
Junzhe Zhang · Elias Bareinboim
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #137
Policy Evaluation with Latent Confounders via Optimal Balance
In Probabilistic Methods -- Causal Inference
Andrew Bennett · Nathan Kallus
[ Paper]  [ Slides] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #138
Sample Efficient Active Learning of Causal Trees
In Probabilistic Methods -- Causal Inference
Kristjan Greenewald · Dmitriy Katz · Karthikeyan Shanmugam · Sara Magliacane · Murat Kocaoglu · Enric Boix-Adsera · Guy Bresler
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #139
Selecting causal brain features with a single conditional independence test per feature
In Probabilistic Methods -- Causal Inference
Atalanti Mastakouri · Bernhard Schölkopf · Dominik Janzing
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #140
Specific and Shared Causal Relation Modeling and Mechanism-Based Clustering
In Probabilistic Methods -- Causal Inference
Biwei Huang · Kun Zhang · Pengtao Xie · Mingming Gong · Eric Xing · Clark Glymour
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #141
The Case for Evaluating Causal Models Using Interventional Measures and Empirical Data
In Probabilistic Methods -- Causal Inference
Amanda Gentzel · Dan Garant · David Jensen
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #142
Triad Constraints for Learning Causal Structure of Latent Variables
In Probabilistic Methods -- Causal Inference
Ruichu Cai · Feng Xie · Clark Glymour · Zhifeng Hao · Kun Zhang
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #143
Using Embeddings to Correct for Unobserved Confounding in Networks
In Probabilistic Methods -- Causal Inference
Victor Veitch · Yixin Wang · David Blei
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #144
Robust Multi-agent Counterfactual Prediction
In Probabilistic Methods -- Distributed Inference
Alexander Peysakhovich · Christian Kroer · Adam Lerer
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #145
Statistical Model Aggregation via Parameter Matching
In Probabilistic Methods -- Distributed Inference
Mikhail Yurochkin · Mayank Agarwal · Soumya Ghosh · Kristjan Greenewald · Nghia Hoang
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #146
Implicit Posterior Variational Inference for Deep Gaussian Processes
In Probabilistic Methods -- Gaussian Processes
Haibin YU · Yizhou Chen · Bryan Kian Hsiang Low · Patrick Jaillet · Zhongxiang Dai
[ Paper]  [ Slides] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #147
Multivariate Sparse Coding of Nonstationary Covariances with Gaussian Processes
In Probabilistic Methods -- Gaussian Processes
Rui Li
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #148
Nonparametric Regressive Point Processes Based on Conditional Gaussian Processes
In Probabilistic Methods -- Gaussian Processes
Siqi Liu · Milos Hauskrecht
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #149
Offline Contextual Bayesian Optimization
In Probabilistic Methods -- Gaussian Processes
Ian Char · Youngseog Chung · Willie Neiswanger · Kirthevasan Kandasamy · Oak Nelson · Mark Boyer · Egemen Kolemen · Jeff Schneider
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #150
Scalable Bayesian dynamic covariance modeling with variational Wishart and inverse Wishart processes
In Probabilistic Methods -- Gaussian Processes
Creighton Heaukulani · Mark van der Wilk
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #151
Spatially Aggregated Gaussian Processes with Multivariate Areal Outputs
In Probabilistic Methods -- Gaussian Processes
Yusuke Tanaka · Toshiyuki Tanaka · Tomoharu Iwata · Takeshi Kurashima · Maya Okawa · Yasunori Akagi · Hiroyuki Toda
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #152
Uniform Error Bounds for Gaussian Process Regression with Application to Safe Control
In Probabilistic Methods -- Gaussian Processes
Armin Lederer · Jonas Umlauft · Sandra Hirche
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #153
Learning Hierarchical Priors in VAEs
In Probabilistic Methods -- Hierarchical Models
Alexej Klushyn · Nutan Chen · Richard Kurle · Botond Cseke · Patrick van der Smagt
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #154
Poisson-Randomized Gamma Dynamical Systems
In Probabilistic Methods -- Hierarchical Models
Aaron Schein · Scott Linderman · Mingyuan Zhou · David Blei · Hanna Wallach
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #155
Efficient Probabilistic Inference in the Quest for Physics Beyond the Standard Model
In Probabilistic Methods -- MCMC
Atilim Gunes Baydin · Lei Shao · Wahid Bhimji · Lukas Heinrich · Saeid Naderiparizi · Andreas Munk · Jialin Liu · Bradley Gram-Hansen · Gilles Louppe · Lawrence Meadows · Philip Torr · Victor Lee · Kyle Cranmer · Mr. Prabhat · Frank Wood
[ Paper]  [ Slides] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #156
Online sampling from log-concave distributions
In Probabilistic Methods -- MCMC
Holden Lee · Oren Mangoubi · Nisheeth Vishnoi
[ Paper]  [ Slides] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #157
Parameter elimination in particle Gibbs sampling
In Probabilistic Methods -- MCMC
Anna Wigren · Riccardo Sven Risuleo · Lawrence Murray · Fredrik Lindsten
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #158
Poisson-Minibatching for Gibbs Sampling with Convergence Rate Guarantees
In Probabilistic Methods -- MCMC
Ruqi Zhang · Christopher De Sa
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #159
Pseudo-Extended Markov chain Monte Carlo
In Probabilistic Methods -- MCMC
Christopher Nemeth · Fredrik Lindsten · Maurizio Filippone · James Hensman
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #160
Stochastic Gradient Hamiltonian Monte Carlo Methods with Recursive Variance Reduction
In Probabilistic Methods -- MCMC
Difan Zou · Pan Xu · Quanquan Gu
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #161
Stochastic Proximal Langevin Algorithm: Potential Splitting and Nonasymptotic Rates
In Probabilistic Methods -- MCMC
Adil Salim · Dmitry Kovalev · Peter Richtarik
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #162
Stochastic Runge-Kutta Accelerates Langevin Monte Carlo and Beyond
In Probabilistic Methods -- MCMC
Xuechen (Chen) Li · Denny Wu · Lester Mackey · Murat Erdogdu
[ Paper]  [ Slides] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #163
The Randomized Midpoint Method for Log-Concave Sampling
In Probabilistic Methods -- MCMC
Ruoqi Shen · Yin Tat Lee
[ Paper]  [ Slides] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #164
Approximate Inference Turns Deep Networks into Gaussian Processes
In Probabilistic Methods -- Variational Inference
Mohammad Emtiyaz Khan · Alexander Immer · Ehsan Abedi · Maciej Korzepa
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #165
Copula-like Variational Inference
In Probabilistic Methods -- Variational Inference
Marcel Hirt · Petros Dellaportas · Alain Durmus
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #166
Divide and Couple: Using Monte Carlo Variational Objectives for Posterior Approximation
In Probabilistic Methods -- Variational Inference
Justin Domke · Daniel Sheldon
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #167
Importance Weighted Hierarchical Variational Inference
In Probabilistic Methods -- Variational Inference
Artem Sobolev · Dmitry Vetrov
[ Paper]  [ Poster]  [ Slides] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #168
Practical Deep Learning with Bayesian Principles
In Probabilistic Methods -- Variational Inference
Kazuki Osawa · Siddharth Swaroop · Mohammad Emtiyaz Khan · Anirudh Jain · Runa Eschenhagen · Richard Turner · Rio Yokota
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #169
Scalable Structure Learning of Continuous-Time Bayesian Networks from Incomplete Data
In Probabilistic Methods -- Variational Inference
Dominik Linzner · Michael Schmidt · Heinz Koeppl
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #170
Universal Boosting Variational Inference
In Probabilistic Methods -- Variational Inference
Trevor Campbell · Xinglong Li
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #171
Variational Bayes under Model Misspecification
In Probabilistic Methods -- Variational Inference
Yixin Wang · David Blei
[ Paper]  [ Slides] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #172
Variational Bayesian Decision-making for Continuous Utilities
In Probabilistic Methods -- Variational Inference
Tomasz Kuśmierczyk · Joseph Sakaya · Arto Klami
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #173
Variational Bayesian Optimal Experimental Design
In Probabilistic Methods -- Variational Inference
Adam Foster · Martin Jankowiak · Elias Bingham · Paul Horsfall · Yee Whye Teh · Thomas Rainforth · Noah Goodman
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #174
Causal Confusion in Imitation Learning
In Reinforcement Learning and Planning -- Decision and Control
Pim de Haan · Dinesh Jayaraman · Sergey Levine
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #175
Hierarchical Decision Making by Generating and Following Natural Language Instructions
In Reinforcement Learning and Planning -- Decision and Control
Hengyuan Hu · Denis Yarats · Qucheng Gong · Yuandong Tian · Mike Lewis
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #176
Non-Cooperative Inverse Reinforcement Learning
In Reinforcement Learning and Planning -- Decision and Control
Xiangyuan Zhang · Kaiqing Zhang · Erik Miehling · Tamer Basar
[ Paper]  [ Slides] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #177
Robust exploration in linear quadratic reinforcement learning
In Reinforcement Learning and Planning -- Decision and Control
Jack Umenberger · Mina Ferizbegovic · Thomas Schön · Håkan Hjalmarsson
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #178
Almost Horizon-Free Structure-Aware Best Policy Identification with a Generative Model
In Reinforcement Learning and Planning -- Exploration
Andrea Zanette · Mykel J Kochenderfer · Emma Brunskill
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #179
Better Exploration with Optimistic Actor Critic
In Reinforcement Learning and Planning -- Exploration
Kamil Ciosek · Quan Vuong · Robert Loftin · Katja Hofmann
[ Paper]  [ Slides] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #180
Provably Efficient Q-learning with Function Approximation via Distribution Shift Error Checking Oracle
In Reinforcement Learning and Planning -- Exploration
Simon Du · Yuping Luo · Ruosong Wang · Hanrui Zhang
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #181
Explicit Planning for Efficient Exploration in Reinforcement Learning
In Reinforcement Learning and Planning -- Exploration
Liangpeng Zhang · Ke Tang · Xin Yao
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #182
Exploration Bonus for Regret Minimization in Discrete and Continuous Average Reward MDPs
In Reinforcement Learning and Planning -- Exploration
Jian QIAN · Ronan Fruit · Matteo Pirotta · Alessandro Lazaric
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #183
Information-Theoretic Confidence Bounds for Reinforcement Learning
In Reinforcement Learning and Planning -- Exploration
Xiuyuan Lu · Benjamin Van Roy
[ Paper]  [ Slides] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #184
Worst-Case Regret Bounds for Exploration via Randomized Value Functions
In Reinforcement Learning and Planning -- Exploration
Daniel Russo
[ Paper]  [ Slides] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #185
Beyond Confidence Regions: Tight Bayesian Ambiguity Sets for Robust MDPs
In Reinforcement Learning and Planning -- Model-Based RL
Marek Petrik · Reazul Hasan Russel
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #186
Correlation Priors for Reinforcement Learning
In Reinforcement Learning and Planning -- Model-Based RL
Bastian Alt · Adrian Šošić · Heinz Koeppl
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #187
Explicit Explore-Exploit Algorithms in Continuous State Spaces
In Reinforcement Learning and Planning -- Model-Based RL
Mikael Henaff
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #188
Learning to Predict Without Looking Ahead: World Models Without Forward Prediction
In Reinforcement Learning and Planning -- Model-Based RL
Daniel Freeman · David Ha · Luke Metz
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #189
Mapping State Space using Landmarks for Universal Goal Reaching
In Reinforcement Learning and Planning -- Model-Based RL
Zhiao Huang · Fangchen Liu · Hao Su
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #190
Regularizing Trajectory Optimization with Denoising Autoencoders
In Reinforcement Learning and Planning -- Model-Based RL
Rinu Boney · Norman Di Palo · Mathias Berglund · Alexander Ilin · Juho Kannala · Antti Rasmus · Harri Valpola
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #191
Tight Regret Bounds for Model-Based Reinforcement Learning with Greedy Policies
In Reinforcement Learning and Planning -- Model-Based RL
Yonathan Efroni · Nadav Merlis · Mohammad Ghavamzadeh · Shie Mannor
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #192
When to Trust Your Model: Model-Based Policy Optimization
In Reinforcement Learning and Planning -- Model-Based RL
Michael Janner · Justin Fu · Marvin Zhang · Sergey Levine
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #193
When to use parametric models in reinforcement learning?
In Reinforcement Learning and Planning -- Model-Based RL
Hado van Hasselt · Matteo Hessel · John Aslanides
[ Paper]  [ Slides] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #194
A Structured Prediction Approach for Generalization in Cooperative Multi-Agent Reinforcement Learning
In Reinforcement Learning and Planning -- Multi-Agent RL
Nicolas Carion · Nicolas Usunier · Gabriel Synnaeve · Alessandro Lazaric
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #195
Efficient Communication in Multi-Agent Reinforcement Learning via Variance Based Control
In Reinforcement Learning and Planning -- Multi-Agent RL
Sai Qian Zhang · Qi Zhang · Jieyu Lin
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #196
Learning Mean-Field Games
In Reinforcement Learning and Planning -- Multi-Agent RL
Xin Guo · Anran Hu · Renyuan Xu · Junzi Zhang
[ Paper]  [ Slides] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #197
Learning to Control Self-Assembling Morphologies: A Study of Generalization via Modularity
In Reinforcement Learning and Planning -- Multi-Agent RL
Deepak Pathak · Christopher Lu · Trevor Darrell · Phillip Isola · Alexei Efros
[ Paper] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #198
LIIR: Learning Individual Intrinsic Reward in Multi-Agent Reinforcement Learning
In Reinforcement Learning and Planning -- Multi-Agent RL
Yali Du · Lei Han · Meng Fang · Ji Liu · Tianhong Dai · Dacheng Tao
[ Paper]  [ Slides] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #199
On the Utility of Learning about Humans for Human-AI Coordination
In Reinforcement Learning and Planning -- Multi-Agent RL
Micah Carroll · Rohin Shah · Mark Ho · Tom Griffiths · Sanjit Seshia · Pieter Abbeel · Anca Dragan
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #200
Value Propagation for Decentralized Networked Deep Multi-agent Reinforcement Learning
In Reinforcement Learning and Planning -- Multi-Agent RL
Chao Qu · Shie Mannor · Huan Xu · Yuan Qi · Le Song · Junwu Xiong
[ Paper]  [ Slides] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #201
Convergent Policy Optimization for Safe Reinforcement Learning
In Reinforcement Learning and Planning -- Reinforcement Learning
Ming Yu · Zhuoran Yang · Mladen Kolar · Zhaoran Wang
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #202
Experience Replay for Continual Learning
In Reinforcement Learning and Planning -- Reinforcement Learning
David Rolnick · Arun Ahuja · Jonathan Richard Schwarz · Timothy Lillicrap · Gregory Wayne
[ Paper]  [ Slides] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #203
Exploration via Hindsight Goal Generation
In Reinforcement Learning and Planning -- Reinforcement Learning
Zhizhou Ren · Kefan Dong · Yuan Zhou · Qiang Liu · Jian Peng
[ Paper]  [ Slides] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #204
Hindsight Credit Assignment
In Reinforcement Learning and Planning -- Reinforcement Learning
Anna Harutyunyan · Will Dabney · Thomas Mesnard · Mohammad Gheshlaghi Azar · Bilal Piot · Nicolas Heess · Hado van Hasselt · Gregory Wayne · Satinder Singh · Doina Precup · Remi Munos
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #205
Imitation Learning from Observations by Minimizing Inverse Dynamics Disagreement
In Reinforcement Learning and Planning -- Reinforcement Learning
Chao Yang · Xiaojian Ma · Wenbing Huang · Fuchun Sun · Huaping Liu · Junzhou Huang · Chuang Gan
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #206
Importance Resampling for Off-policy Prediction
In Reinforcement Learning and Planning -- Reinforcement Learning
Matthew Schlegel · Wesley Chung · Daniel Graves · Jian Qian · Martha White
[ Paper]  [ Poster]  [ Slides] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #207
Learning Compositional Neural Programs with Recursive Tree Search and Planning
In Reinforcement Learning and Planning -- Reinforcement Learning
Thomas PIERROT · Guillaume Ligner · Scott Reed · Olivier Sigaud · Nicolas Perrin · Alexandre Laterre · David Kas · Karim Beguir · Nando de Freitas
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #208
Multi-View Reinforcement Learning
In Reinforcement Learning and Planning -- Reinforcement Learning
Minne Li · Lisheng Wu · Jun WANG · Haitham Bou Ammar
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #209
Real-Time Reinforcement Learning
In Reinforcement Learning and Planning -- Reinforcement Learning
Simon Ramstedt · Chris Pal
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #210
Reconciling λ-Returns with Experience Replay
In Reinforcement Learning and Planning -- Reinforcement Learning
Brett Daley · Christopher Amato
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #211
Regret Minimization for Reinforcement Learning by Evaluating the Optimal Bias Function
In Reinforcement Learning and Planning -- Reinforcement Learning
Zihan Zhang · Xiangyang Ji
[ Paper]  [ Slides] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #212
Sample-Efficient Deep Reinforcement Learning via Episodic Backward Update
In Reinforcement Learning and Planning -- Reinforcement Learning
Suyoung Lee · Sungik Choi · Sae-Young Chung
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #213
Staying up to Date with Online Content Changes Using Reinforcement Learning for Scheduling
In Reinforcement Learning and Planning -- Reinforcement Learning
Andrey Kolobov · Yuval Peres · Cheng Lu · Eric Horvitz
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #214
Trust Region-Guided Proximal Policy Optimization
In Reinforcement Learning and Planning -- Reinforcement Learning
Yuhui Wang · Hao He · Xiaoyang Tan · Yaozhong Gan
[ Paper]  [ Slides] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #215
Using a Logarithmic Mapping to Enable Lower Discount Factors in Reinforcement Learning
In Reinforcement Learning and Planning -- Reinforcement Learning
Harm Van Seijen · Mehdi Fatemi · Arash Tavakoli
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #216
Certainty Equivalence is Efficient for Linear Quadratic Control
In Theory -- Control Theory
Horia Mania · Stephen Tu · Benjamin Recht
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #217
A Polynomial Time Algorithm for Log-Concave Maximum Likelihood via Locally Exponential Families
In Theory -- Learning Theory
Brian Axelrod · Ilias Diakonikolas · Alistair Stewart · Anastasios Sidiropoulos · Gregory Valiant
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #218
Dichotomize and Generalize: PAC-Bayesian Binary Activated Deep Neural Networks
In Theory -- Learning Theory
Gaël Letarte · Pascal Germain · Benjamin Guedj · Francois Laviolette
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #219
Finite-time Analysis of Approximate Policy Iteration for the Linear Quadratic Regulator
In Theory -- Learning Theory
Karl Krauth · Stephen Tu · Benjamin Recht
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #220
Hypothesis Set Stability and Generalization
In Theory -- Learning Theory
Dylan Foster · Spencer Greenberg · Satyen Kale · Haipeng Luo · Mehryar Mohri · Karthik Sridharan
[ Paper]  [ Slides] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #221
Minimizers of the Empirical Risk and Risk Monotonicity
In Theory -- Learning Theory
Marco Loog · Tom Viering · Alexander Mey
[ Paper]  [ Slides] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #222
Multiclass Learning from Contradictions
In Theory -- Learning Theory
Sauptik Dhar · Vladimir Cherkassky · Mohak Shah
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #223
On the Correctness and Sample Complexity of Inverse Reinforcement Learning
In Theory -- Learning Theory
Abi Komanduru · Jean Honorio
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #224
On the Power and Limitations of Random Features for Understanding Neural Networks
In Theory -- Learning Theory
Gilad Yehudai · Ohad Shamir
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #225
Robustness to Adversarial Perturbations in Learning from Incomplete Data
In Theory -- Learning Theory
Amir Najafi · Shin-ichi Maeda · Masanori Koyama · Takeru Miyato
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #226
Stability of Graph Scattering Transforms
In Theory -- Learning Theory
Fernando Gama · Alejandro Ribeiro · Joan Bruna
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #227
State Aggregation Learning from Markov Transition Data
In Theory -- Learning Theory
Yaqi Duan · Zheng Tracy Ke · Mengdi Wang
[ Paper]  [ Poster] 
Poster
Tue Dec 10 05:30 PM -- 07:30 PM (PST) @ East Exhibition Hall B + C #228
Toward a Characterization of Loss Functions for Distribution Learning
In Theory -- Learning Theory
Nika Haghtalab · Cameron Musco · Bo Waggoner
[ Paper]  [ Poster]