Microsoft at ICML 2020
Location: Virtual/Online
Tuesday, July 14
07:00 – 07:45 PDT
2nd session: 20:00 – 20:45 PDT
NGBoost: Natural Gradient Boosting for Probabilistic Prediction
Tony Duan, Anand Avati, Daisy Ding, Khanh K. Thai, Sanjay Basu, Andrew Ng, Alejandro Schuler
07:00 – 07:45 PDT
2nd session: 18:00 – 18:45 PDT
Online Learning for Active Cache Synchronization
Andrey Kolobov, Sebastien Bubeck, Julian Zimmert
07:00 – 07:45 PDT
2nd session: 19:00 – 19:45 PDT
Randomized Smoothing of All Shapes and Sizes
Greg Yang, Tony Duan, J. Edward Hu, Hadi Salman, Ilya Razenshteyn, Jerry Li
07:00 – 07:45 PDT
2nd session: 20:00 – 20:45 PDT
Private Reinforcement Learning with PAC and Regret Guarantees
Giuseppe Vietri, Borja de Balle Pigem, Akshay Krishnamurthy, Steven Wu
07:00 – 07:45 PDT
2nd session: 18:00 – 18:45 PDT
Scalable Nearest Neighbor Search for Optimal Transport
Arturs Backurs, Yihe Dong, Piotr Indyk, Ilya Razenshteyn, Tal Wagner
07:00 – 07:45 PDT
2nd session: 19:00 – 19:45 PDT
Combinatorial Pure Exploration for Dueling Bandit
Wei Chen, Yihan Du, Longbo Huang, Haoyu Zhao
07:00 – 07:45 PDT
2nd session: 19:00 – 19:45 PDT
Distance Metric Learning with Joint Representation Diversification
Xu Chu, Yang Lin, Xiting Wang, Xin Gao, Qi Tong, Hailong Yu, Yasha Wang
07:00 – 07:45 PDT
2nd session: 19:00 – 19:45 PDT
Efficient Domain Generalization via Common-Specific Low-Rank Decomposition
Vihari Piratla, Praneeth Netrapalli, Sunita Sarawagi
07:00 – 07:45 PDT
2nd session: 18:00 – 18:45 PDT
Faster Graph Embeddings via Coarsening
Matthew Fahrbach, Gramoz Goranci, Sushant Sachdeva, Richard Peng, Chi Wang
07:00 – 07:45 PDT
2nd session: 18:00 – 18:45 PDT
What is Local Optimality in Nonconvex-Nonconcave Minimax Optimization?
Chi Jin, Praneeth Netrapalli, Michael Jordan
08:00 – 08:45 PDT
2nd session: 19:00 – 19:45 PDT
An end-to-end approach for the verification problem: learning the right distance
Joao Monteiro, Isabela Albuquerque, Jahangir Alam, R Devon Hjelm, Tiago Falk
08:00 – 08:45 PDT
2nd session: 21:00 – 21:45 PDT
Working Memory Graphs
Ricky Loynd, Roland Fernandez, Asli Celikyilmaz, Adith Swaminathan, Matthew Hausknecht
08:00 – 08:45 PDT
2nd session: 19:00 – 19:45 PDT
Informative Dropout for Robust Representation Learning: A Shape-bias Perspective
Baifeng Shi, Dinghuai Zhang, Qi Dai, Jingdong Wang, Zhanxing Zhu, Yadong Mu
08:00 – 08:45 PDT
2nd session: 21:00 – 21:45 PDT
Near-optimal Sample Complexity Bounds for Learning Latent k−polytopes and applications to Ad-Mixtures
Chiranjib Bhattacharyya, Ravindran Kannan
08:00 – 08:45 PDT
2nd session: 19:00 – 19:45 PDT
Differentially Private Set Union
Pankaj Gulhane, Sivakanth Gopi, Janardhan Kulkarni, Judy Hanwen Shen, Milad Shokouhi, Sergey Yekhanin
08:00 – 08:45 PDT
2nd session: 21:00 – 21:45 PDT
Discount Factor as a Regularizer in Reinforcement Learning
Ron Amit, Kamil Ciosek, Ron Meir
08:00 – 08:45 PDT
2nd session: 21:00 – 21:45 PDT
DROCC: Deep Robust One-Class Classification
Sachin Goyal, Aditi Raghunathan, Moksh Jain, Harsha Vardhan Simhadri, Prateek Jain
09:00 – 09:45 PDT
2nd session: 20:00 – 20:45 PDT
Feature Quantization Improves GAN Training
Yang Zhao, Chunyuan Li, Ping Yu, Jianfeng Gao, Changyou Chen
09:00 – 09:45 PDT
2nd session: 22:00 – 22:45 PDT
How Good is the Bayes Posterior in Deep Neural Networks Really
Florian Wenzel, Kevin Roth, Bastiaan S. Veeling, Jakub Swiatkowski, Linh Tran, Stephan Mandt, Jasper Snoek, Tim Salimans, Rodolphe Jenatton, Sebastian Nowozin
11:00 – 11:45 PDT
2nd session: 22:00 – 22:45 PDT
Optimization and Analysis of the pAp@k Metric for Recommender Systems
Gaurush Hiranandani, Warut Vijitbenjaronk, Sanmi Koyejo, Prateek Jain
11:00 – 11:45 PDT
2nd session: 22:00 – 22:45 PDT
Bandits with Adversarial Scaling
Thodoris Lykouris, Vahab Mirrokni, Renato Leme
12:00 – 12:45 PDT
2nd session: July 15 | 01:00 – 01:45 PDT
TaskNorm: Rethinking Batch Normalization for Meta-Learning
John Bronskill, Jonathan Gordon, James Requeima, Sebastian Nowozin, Richard E. Turner
13:00 – 13:45 PDT
2nd session: July 15 | 01:00 – 01:45 PDT
GNN-FiLM: Graph Neural Networks with Feature-wise Linear Modulation
Marc Brockschmidt
18:00 – 18:45 PDT
Online Learning for Active Cache Synchronization
Andrey Kolobov, Sebastien Bubeck, Julian Zimmert
18:00 – 18:45 PDT
Scalable Nearest Neighbor Search for Optimal Transport
Arturs Backurs, Yihe Dong, Piotr Indyk, Ilya Razenshteyn, Tal Wagner
18:00 – 18:45 PDT
Faster Graph Embeddings via Coarsening
Matthew Fahrbach, Gramoz Goranci, Sushant Sachdeva, Richard Peng, Chi Wang
18:00 – 18:45 PDT
What is Local Optimality in Nonconvex-Nonconcave Minimax Optimization?
Chi Jin, Praneeth Netrapalli, Michael Jordan
19:00 – 19:45 PDT
Randomized Smoothing of All Shapes and Sizes
Greg Yang, Tony Duan, J. Edward Hu, Hadi Salman, Ilya Razenshteyn, Jerry Li
19:00 – 19:45 PDT
An end-to-end approach for the verification problem: learning the right distance
Joao Monteiro, Isabela Albuquerque, Jahangir Alam, R Devon Hjelm, Tiago Falk
19:00 – 19:45 PDT
Combinatorial Pure Exploration for Dueling Bandit
Wei Chen, Yihan Du, Longbo Huang, Haoyu Zhao
19:00 – 19:45 PDT
Distance Metric Learning with Joint Representation Diversification
Xu Chu, Yang Lin, Xiting Wang, Xin Gao, Qi Tong, Hailong Yu, Yasha Wang
19:00 – 19:45 PDT
Efficient Domain Generalization via Common-Specific Low-Rank Decomposition
Vihari Piratla, Praneeth Netrapalli, Sunita Sarawagi
19:00 – 19:45 PDT
Informative Dropout for Robust Representation Learning: A Shape-bias Perspective
Baifeng Shi, Dinghuai Zhang, Qi Dai, Jingdong Wang, Zhanxing Zhu, Yadong Mu
19:00 – 19:45 PDT
Differentially Private Set Union
Pankaj Gulhane, Sivakanth Gopi, Janardhan Kulkarni, Judy Hanwen Shen, Milad Shokouhi, Sergey Yekhanin
20:00 – 20:45 PDT
NGBoost: Natural Gradient Boosting for Probabilistic Prediction
Tony Duan, Anand Avati, Daisy Ding, Khanh K. Thai, Sanjay Basu, Andrew Ng, Alejandro Schuler
20:00 – 20:45 PDT
Private Reinforcement Learning with PAC and Regret Guarantees
Giuseppe Vietri, Borja de Balle Pigem, Akshay Krishnamurthy, Steven Wu
20:00 – 20:45 PDT
Feature Quantization Improves GAN Training
Yang Zhao, Chunyuan Li, Ping Yu, Jianfeng Gao, Changyou Chen
21:00 – 21:45 PDT
Working Memory Graphs
Ricky Loynd, Roland Fernandez, Asli Celikyilmaz, Adith Swaminathan, Matthew Hausknecht
21:00 – 21:45 PDT
Near-optimal Sample Complexity Bounds for Learning Latent k−polytopes and applications to Ad-Mixtures
Chiranjib Bhattacharyya, Ravindran Kannan
21:00 – 21:45 PDT
Discount Factor as a Regularizer in Reinforcement Learning
Ron Amit, Kamil Ciosek, Ron Meir
21:00 – 21:45 PDT
DROCC: Deep Robust One-Class Classification
Sachin Goyal, Aditi Raghunathan, Moksh Jain, Harsha Vardhan Simhadri, Prateek Jain
22:00 – 22:45 PDT
Optimization and Analysis of the pAp@k Metric for Recommender Systems
Gaurush Hiranandani, Warut Vijitbenjaronk, Sanmi Koyejo, Prateek Jain
22:00 – 22:45 PDT
Bandits with Adversarial Scaling
Thodoris Lykouris, Vahab Mirrokni, Renato Leme
22:00 – 22:45 PDT
How Good is the Bayes Posterior in Deep Neural Networks Really
Florian Wenzel, Kevin Roth, Bastiaan S. Veeling, Jakub Swiatkowski, Linh Tran, Stephan Mandt, Jasper Snoek, Tim Salimans, Rodolphe Jenatton, Sebastian Nowozin
Wednesday, July 15
01:00 – 01:45 PDT
GNN-FiLM: Graph Neural Networks with Feature-wise Linear Modulation
Marc Brockschmidt
01:00 – 01:45 PDT
TaskNorm: Rethinking Batch Normalization for Meta-Learning
John Bronskill, Jonathan Gordon, James Requeima, Sebastian Nowozin, Richard E. Turner
05:00 – 05:45 PDT
2nd session: 16:00 – 16:45 PDT
Adaptive Estimator Selection for Off-Policy Evaluation
Yi Su, Pavithra Srinath, Akshay Krishnamurthy
05:00 – 05:45 PDT
2nd session: 16:00 – 16:45 PDT
Privately Learning Markov Random Fields
Gautam Kamath, Janardhan Kulkarni, Steven Wu, Huanyu Zhang
08:00 – 08:45 PDT
2nd session: 21:00 – 21:45 PDT
The Non-IID Data Quagmire of Decentralized Machine Learning
Kevin Hsieh, Amar Phanishayee, Onur Mutlu, Phillip Gibbons
08:00 – 08:45 PDT
2nd session: 21:00 – 21:45 PDT
Alleviating Privacy Attacks via Causal Learning
Shruti Tople, Amit Sharma, Aditya Nori
08:00 – 08:45 PDT
2nd session: 21:00 – 21:45 PDT
(Locally) Differentially Private Combinatorial Semi-Bandits
Xiaoyu Chen, Kai Zheng, Zixin Zhou, Yunchang Yang, Wei Chen, Liwei Wang
08:00 – 08:45 PDT
2nd session: 20:00 – 20:45 PDT
The Usual Suspects? Reassessing Blame for VAE Posterior Collapse
Bin Dai, Ziyu Wang, David Wipf
10:00 – 10:45 PDT
2nd session: 21:00 – 21:45 PDT
Single Point Transductive Prediction
Nilesh Tripuraneni, Lester Mackey
10:00 – 10:45 PDT
2nd session: 21:00 – 21:45 PDT
Learning Calibratable Policies using Programmatic Style-Consistency
Eric Zhan, Albert Tseng, Yisong Yue, Adith Swaminathan, Matthew Hausknecht
11:00 – 11:45 PDT
2nd session: 22:00 – 22:45 PDT
Statistically Preconditioned Accelerated Gradient Method for Distributed Optimization
Hadrien Hendrikx, Lin Xiao, Sebastien Bubeck, Francis Bach, Laurent Massoulié
12:00 – 12:45 PDT
2nd session: July 16 | 01:00 – 01:45 PDT
Neuro-Symbolic Visual Reasoning: Disentangling “Visual” from “Reasoning”
Saeed Amizadeh, Hamid Palangi, Oleksandr Polozov, Yichen Huang, Kazuhito Koishida
16:00 – 16:45 PDT
2nd session: July 16 | 03:00 – 03:45 PDT
Optimization from Structured Samples for Coverage Functions
Wei Chen, Xiaoming Sun, Jialin Zhang, Zhijie Zhang
16:00 – 16:45 PDT
Adaptive Estimator Selection for Off-Policy Evaluation
Yi Su, Pavithra Srinath, Akshay Krishnamurthy
16:00 – 16:45 PDT
Privately Learning Markov Random Fields
Gautam Kamath, Janardhan Kulkarni, Steven Wu, Huanyu Zhang
20:00 – 20:45 PDT
The Usual Suspects? Reassessing Blame for VAE Posterior Collapse
Bin Dai, Ziyu Wang, David Wipf
21:00 – 21:45 PDT
The Non-IID Data Quagmire of Decentralized Machine Learning
Kevin Hsieh, Amar Phanishayee, Onur Mutlu, Phillip Gibbons
21:00 – 21:45 PDT
Single Point Transductive Prediction
Nilesh Tripuraneni, Lester Mackey
21:00 – 21:45 PDT
Alleviating Privacy Attacks via Causal Learning
Shruti Tople, Amit Sharma, Aditya Nori
21:00 – 21:45 PDT
(Locally) Differentially Private Combinatorial Semi-Bandits
Xiaoyu Chen, Kai Zheng, Zixin Zhou, Yunchang Yang, Wei Chen, Liwei Wang
21:00 – 21:45 PDT
Learning Calibratable Policies using Programmatic Style-Consistency
Eric Zhan, Albert Tseng, Yisong Yue, Adith Swaminathan, Matthew Hausknecht
22:00 – 22:45 PDT
Statistically Preconditioned Accelerated Gradient Method for Distributed Optimization
Hadrien Hendrikx, Lin Xiao, Sebastien Bubeck, Francis Bach, Laurent Massoulié
Thursday, July 16
01:00 – 01:45 PDT
Neuro-Symbolic Visual Reasoning: Disentangling “Visual” from “Reasoning”
Saeed Amizadeh, Hamid Palangi, Oleksandr Polozov, Yichen Huang, Kazuhito Koishida
03:00 – 03:45 PDT
Optimization from Structured Samples for Coverage Functions
Wei Chen, Xiaoming Sun, Jialin Zhang, Zhijie Zhang
06:00 – 06:45 PDT
2nd session: July 17 | 18:00 – 18:45 PDT
Mapping Natural-language Problems to Formal-language Solutions Using Structured Neural Representations
Kezhen Chen, Qiuyuan Huang, Hamid Palangi, Paul Smolensky, Ken Forbus, Jianfeng Gao
06:00 – 06:45 PDT
2nd session: 17:00 – 17:45 PDT
BINOCULARS for efficient, nonmyopic sequential experimental design
Shali Jiang, Henry Chai, Javier Gonzalez, Roman Garnett
06:00 – 06:45 PDT
2nd session: 18:00 – 18:45 PDT
Black-Box Methods for Restoring Monotonicity
Evangelia Gergatsouli, Brendan Lucier, Christos Tzamos
06:00 – 06:45 PDT
2nd session: 17:00 – 17:45 PDT
CLUB: A Contrastive Log-ratio Upper Bound of Mutual Information
Pengyu Cheng, Weituo Hao, Shuyang Dai, Jiachang Liu, Zhe Gan, Lawrence Carin
06:00 – 06:45 PDT
2nd session: 17:00 – 17:45 PDT
Neural Datalog Through Time: Informed Temporal Modeling via Logical Specification
Hongyuan Mei, Guanghui Qin, Minjie Xu, Jason Eisner
06:00 – 06:45 PDT
2nd session: 19:00 – 19:45 PDT
Provably Efficient Model-based Policy Adaptation
Yuda Song, Aditi Mavalankar, Wen Sun, Sicun Gao
06:00 – 06:45 PDT
2nd session: 18:00 – 18:45 PDT
Sequence Generation with Mixed Representations
Lijun Wu, Shufang Xie, Yingce Xia, Yang Fan, Jian-Huang Lai, Tao Qin, Tie-Yan Liu
06:00 – 06:45 PDT
2nd session: 17:00 – 17:45 PDT
Reward-Free Exploration for Reinforcement Learning
Chi Jin, Akshay Krishnamurthy, Max Simchowitz, Tiancheng Yu
07:00 – 07:45 PDT
2nd session: 18:00 – 18:45 PDT
No-Regret and Incentive-Compatible Online Learning
Rupert Freeman, David Pennock, Charikleia Podimata, Jennifer Wortman Vaughan
07:00 – 07:45 PDT
2nd session: 18:00 – 18:45 PDT
Graph Optimal Transport for Cross-Domain Alignment
Liqun Chen, Zhe Gan, Yu Cheng, Linjie Li, Lawrence Carin, Jingjing Liu
07:00 – 07:45 PDT
2nd session: 20:00 – 20:45 PDT
Doubly Robust Off-policy Evaluation with Shrinkage
Yi Su, Maria Dimakopoulou, Akshay Krishnamurthy, Miroslav Dudik
07:00 – 07:45 PDT
2nd session: 18:00 – 18:45 PDT
Variance Reduction and Quasi-Newton for Particle-Based Variational Inference Michael Zhu, Chang Liu, Jun Zhu
07:00 – 07:45 PDT
2nd session: 20:00 – 20:45 PDT
Kinematic State Abstraction and Provably Efficient Rich-Observation Reinforcement Learning
Dipendra Misra, Mikael Henaff, Akshay Krishnamurthy, John Langford
08:00 – 08:45 PDT
2nd session: 19:00 – 19:45 PDT
UniLMv2: Pseudo-Masked Language Models for Unified Language Model Pre-Training
Hangbo Bao, Li Dong, Furu Wei, Wenhui Wang, Nan Yang, Xiaodong Liu, Yu Wang, Jianfeng Gao, Songhao Piao, Ming Zhou, Hsiao-Wuen Hon
09:00 – 09:45 PDT
2nd session: 23:00 – 23:45 PDT
Bounding the fairness and accuracy of classifiers from population statistics
Sivan Sabato, Elad Yom-Tov
12:00 – 12:45 PDT
2nd session: July 17 | 00:00 – 00:45 PDT
Soft Threshold Weight Reparameterization for Learnable Sparsity
Aditya Kusupati, Vivek Ramanujan, Raghav Somani, Mitchell Wortsman, Prateek Jain, Sham Kakade, Ali Farhadi
12:00 – 12:45 PDT
2nd session: July 17 | 01:00 – 01:45 PDT
The k-tied Normal Distribution: A Compact Parameterization of Gaussian Mean Field Posteriors in Bayesian Neural Networks
Jakub Swiatkowski, Kevin Roth, Bastiaan S. Veeling, Linh Tran, Joshua V. Dillon, Stephan Mandt, Jasper Snoek, Tim Salimans, Rodolphe Jenatton, Sebastian Nowozin
17:00 – 17:45 PDT
BINOCULARS for efficient, nonmyopic sequential experimental design
Shali Jiang, Henry Chai, Javier Gonzalez, Roman Garnett
17:00 – 17:45 PDT
CLUB: A Contrastive Log-ratio Upper Bound of Mutual Information
Pengyu Cheng, Weituo Hao, Shuyang Dai, Jiachang Liu, Zhe Gan, Lawrence Carin
17:00 – 17:45 PDT
Neural Datalog Through Time: Informed Temporal Modeling via Logical Specification
Hongyuan Mei, Guanghui Qin, Minjie Xu, Jason Eisner
17:00 – 17:45 PDT
Reward-Free Exploration for Reinforcement Learning
Chi Jin, Akshay Krishnamurthy, Max Simchowitz, Tiancheng Yu
18:00 – 18:45 PDT
Mapping Natural-language Problems to Formal-language Solutions Using Structured Neural Representations
Kezhen Chen, Qiuyuan Huang, Hamid Palangi, Paul Smolensky, Ken Forbus, Jianfeng Gao
18:00 – 18:45 PDT
No-Regret and Incentive-Compatible Online Learning
Rupert Freeman, David Pennock, Charikleia Podimata, Jennifer Wortman Vaughan
18:00 – 18:45 PDT
2nd session: July 17 | 04:00 – 04:45 PDT
On Layer Normalization in the Transformer Architecture
Ruibin Xiong, Yunchang Yang, Di He, Kai Zheng, Shuxin Zheng, Chen Xing, Huishuai Zhang, Yanyan Lan, Liwei Wang, Tie-Yan Liu
18:00 – 18:45 PDT
Black-Box Methods for Restoring Monotonicity
Evangelia Gergatsouli, Brendan Lucier, Christos Tzamos
18:00 – 18:45 PDT
Graph Optimal Transport for Cross-Domain Alignment
Liqun Chen, Zhe Gan, Yu Cheng, Linjie Li, Lawrence Carin, Jingjing Liu
18:00 – 18:45 PDT
Variance Reduction and Quasi-Newton for Particle-Based Variational Inference Michael Zhu, Chang Liu, Jun Zhu
18:00 – 18:45 PDT
Sequence Generation with Mixed Representations
Lijun Wu, Shufang Xie, Yingce Xia, Yang Fan, Jian-Huang Lai, Tao Qin, Tie-Yan Liu
19:00 – 19:45 PDT
UniLMv2: Pseudo-Masked Language Models for Unified Language Model Pre-Training
Hangbo Bao, Li Dong, Furu Wei, Wenhui Wang, Nan Yang, Xiaodong Liu, Yu Wang, Jianfeng Gao, Songhao Piao, Ming Zhou, Hsiao-Wuen Hon
19:00 – 19:45 PDT
Provably Efficient Model-based Policy Adaptation
Yuda Song, Aditi Mavalankar, Wen Sun, Sicun Gao
20:00 – 20:45 PDT
Doubly Robust Off-policy Evaluation with Shrinkage
Yi Su, Maria Dimakopoulou, Akshay Krishnamurthy, Miroslav Dudik
20:00 – 20:45 PDT
Kinematic State Abstraction and Provably Efficient Rich-Observation Reinforcement Learning
Dipendra Misra, Mikael Henaff, Akshay Krishnamurthy, John Langford
23:00 – 23:45 PDT
Bounding the fairness and accuracy of classifiers from population statistics
Sivan Sabato, Elad Yom-Tov
Friday, July 17
00:00 – 00:45 PDT
Soft Threshold Weight Reparameterization for Learnable Sparsity
Aditya Kusupati, Vivek Ramanujan, Raghav Somani, Mitchell Wortsman, Prateek Jain, Sham Kakade, Ali Farhadi
01:00 – 01:45 PDT
The k-tied Normal Distribution: A Compact Parameterization of Gaussian Mean Field Posteriors in Bayesian Neural Networks
Jakub Swiatkowski, Kevin Roth, Bastiaan S. Veeling, Linh Tran, Joshua V. Dillon, Stephan Mandt, Jasper Snoek, Tim Salimans, Rodolphe Jenatton, Sebastian Nowozin
04:00 – 04:45 PDT
On Layer Normalization in the Transformer Architecture
Ruibin Xiong, Yunchang Yang, Di He, Kai Zheng, Shuxin Zheng, Chen Xing, Huishuai Zhang, Yanyan Lan, Liwei Wang, Tie-Yan Liu