{"id":670011,"date":"2020-06-26T14:10:27","date_gmt":"2020-06-26T21:10:27","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/?post_type=msr-event&p=670011"},"modified":"2025-08-06T11:52:43","modified_gmt":"2025-08-06T18:52:43","slug":"icml-2020","status":"publish","type":"msr-event","link":"https:\/\/www.microsoft.com\/en-us\/research\/event\/icml-2020\/","title":{"rendered":"Microsoft at ICML 2020"},"content":{"rendered":"\n\n

Website:<\/strong> ICML 2020 (opens in new tab)<\/span><\/a>Opens in a new tab<\/span><\/p>\n

Microsoft is proud to be a Gold sponsor of the 37th International Conference on Machine Learning (opens in new tab)<\/span><\/a> (ICML), as well as Diamond sponsors at the 1st Women in Machine Learning Un-Workshop (opens in new tab)<\/span><\/a> and Platinum sponsors of the 4th Queer in AI Workshop (opens in new tab)<\/span><\/a>. We have over 50 papers accepted to the conference, and you can find details of our publications on the Accepted papers<\/a> and Workshops<\/a> tabs.<\/p>\n

Committee chairs<\/h2>\n

ICML President: John Langford<\/a>
\nICML Board Members: Hal Daum\u00e9 III<\/a>, Hanna Wallach<\/a>
\nProgram Co-chair: Hal Daum\u00e9 III<\/a><\/p>\n

Invited speaker<\/h2>\n

Tuesday, July 14<\/h3>\n

05:00 \u2013 06:45 PDT & 16:00 \u2013 17:45 PDT
\nDoing Some Good with Machine Learning<\/strong>
\nInvited Speaker: Lester Mackey<\/a>Opens in a new tab<\/span><\/p>\n

Tuesday, July 14<\/h2>\n

07:00 \u2013 07:45 PDT
\n2nd session: 20:00 \u2013 20:45 PDT
\nNGBoost: Natural Gradient Boosting for Probabilistic Prediction<\/strong><\/a>
\nTony Duan<\/strong>, Anand Avati, Daisy Ding, Khanh K. Thai, Sanjay Basu, Andrew Ng, Alejandro Schuler<\/p>\n

07:00 \u2013 07:45 PDT
\n2nd session: 18:00 \u2013 18:45 PDT
\nOnline Learning for Active Cache Synchronization<\/strong><\/a>
\nAndrey Kolobov<\/a>, Sebastien Bubeck<\/a>, Julian Zimmert<\/p>\n

07:00 \u2013 07:45 PDT
\n2nd session: 19:00 \u2013 19:45 PDT
\nRandomized Smoothing of All Shapes and Sizes<\/strong><\/a>
\nGreg Yang<\/a>, Tony Duan<\/strong>, J. Edward Hu<\/strong>, Hadi Salman<\/strong>, Ilya Razenshteyn<\/a>, Jerry Li<\/a><\/p>\n

07:00 \u2013 07:45 PDT
\n2nd session: 20:00 \u2013 20:45 PDT
\nPrivate Reinforcement Learning with PAC and Regret Guarantees<\/strong><\/a>
\nGiuseppe Vietri, Borja de Balle Pigem, Akshay Krishnamurthy<\/a>, Steven Wu<\/p>\n

07:00 \u2013 07:45 PDT
\n2nd session: 18:00 \u2013 18:45 PDT
\nScalable Nearest Neighbor Search for Optimal Transport<\/strong><\/a>
\nArturs Backurs, Yihe Dong<\/strong>, Piotr Indyk, Ilya Razenshteyn<\/a>, Tal Wagner<\/p>\n

07:00 \u2013 07:45 PDT
\n2nd session: 19:00 \u2013 19:45 PDT
\nCombinatorial Pure Exploration for Dueling Bandit<\/strong><\/a>
\nWei Chen<\/a>, Yihan Du, Longbo Huang, Haoyu Zhao<\/p>\n

07:00 \u2013 07:45 PDT
\n2nd session: 19:00 \u2013 19:45 PDT
\nDistance Metric Learning with Joint Representation Diversification<\/strong><\/a>
\nXu Chu, Yang Lin, Xiting Wang<\/a>, Xin Gao, Qi Tong, Hailong Yu, Yasha Wang<\/p>\n

07:00 \u2013 07:45 PDT
\n2nd session: 19:00 \u2013 19:45 PDT
\nEfficient Domain Generalization via Common-Specific Low-Rank Decomposition<\/strong><\/a>
\nVihari Piratla<\/strong>, Praneeth Netrapalli<\/a>, Sunita Sarawagi<\/p>\n

07:00 \u2013 07:45 PDT
\n2nd session: 18:00 \u2013 18:45 PDT
\nFaster Graph Embeddings via Coarsening<\/strong><\/a>
\nMatthew Fahrbach, Gramoz Goranci, Sushant Sachdeva, Richard Peng, Chi Wang<\/a><\/p>\n

07:00 \u2013 07:45 PDT
\n2nd session: 18:00 \u2013 18:45 PDT
\nWhat is Local Optimality in Nonconvex-Nonconcave Minimax Optimization?<\/strong><\/a>
\nChi Jin, Praneeth Netrapalli<\/a>, Michael Jordan<\/p>\n

08:00 \u2013 08:45 PDT
\n2nd session: 19:00 \u2013 19:45 PDT
\nAn end-to-end approach for the verification problem: learning the right distance<\/strong><\/a>
\nJoao Monteiro, Isabela Albuquerque, Jahangir Alam, R Devon Hjelm<\/a>, Tiago Falk<\/p>\n

08:00 \u2013 08:45 PDT
\n2nd session: 21:00 \u2013 21:45 PDT
\nWorking Memory Graphs<\/strong><\/a>
\nRicky Loynd<\/a>, Roland Fernandez<\/a>, Asli Celikyilmaz<\/a>, Adith Swaminathan<\/a>, Matthew Hausknecht<\/a><\/p>\n

08:00 \u2013 08:45 PDT
\n2nd session: 19:00 \u2013 19:45 PDT
\nInformative Dropout for Robust Representation Learning: A Shape-bias Perspective<\/strong><\/a>
\nBaifeng Shi, Dinghuai Zhang, Qi Dai<\/a>, Jingdong Wang<\/a>, Zhanxing Zhu, Yadong Mu<\/p>\n

08:00 \u2013 08:45 PDT
\n2nd session: 21:00 \u2013 21:45 PDT
\nNear-optimal Sample Complexity Bounds for Learning Latent\u00a0k\u2212polytopes and applications to Ad-Mixtures<\/strong><\/a>
\nChiranjib Bhattacharyya, Ravindran Kannan<\/a><\/p>\n

08:00 \u2013 08:45 PDT
\n2nd session: 19:00 \u2013 19:45 PDT
\nDifferentially Private Set Union<\/strong><\/a>
\nPankaj Gulhane<\/strong>, Sivakanth Gopi<\/a>, Janardhan Kulkarni<\/a>, Judy Hanwen Shen<\/strong>, Milad Shokouhi<\/a>, Sergey Yekhanin<\/a><\/p>\n

08:00 \u2013 08:45 PDT
\n2nd session: 21:00 \u2013 21:45 PDT
\nDiscount Factor as a Regularizer in Reinforcement Learning<\/strong><\/a>
\nRon Amit, Kamil Ciosek<\/a>, Ron Meir<\/p>\n

08:00 \u2013 08:45 PDT
\n2nd session: 21:00 \u2013 21:45 PDT
\nDROCC: Deep Robust One-Class Classification<\/strong><\/a>
\nSachin Goyal<\/strong>, Aditi Raghunathan, Moksh Jain, Harsha Vardhan Simhadri<\/a>, Prateek Jain<\/a><\/p>\n

09:00 \u2013 09:45 PDT
\n2nd session: 20:00 \u2013 20:45 PDT
\nFeature Quantization Improves GAN Training<\/strong><\/a>
\nYang Zhao, Chunyuan Li<\/a>, Ping Yu, Jianfeng Gao<\/a>, Changyou Chen<\/p>\n

09:00 \u2013 09:45 PDT
\n2nd session: 22:00 \u2013 22:45 PDT
\nHow Good is the Bayes Posterior in Deep Neural Networks Really<\/strong><\/a>
\nFlorian Wenzel, Kevin Roth, Bastiaan S. Veeling, Jakub Swiatkowski, Linh Tran, Stephan Mandt, Jasper Snoek, Tim Salimans, Rodolphe Jenatton, Sebastian Nowozin<\/a><\/p>\n

11:00 \u2013 11:45 PDT
\n2nd session: 22:00 \u2013 22:45 PDT
\nOptimization and Analysis of the pAp@k Metric for Recommender Systems<\/strong><\/a>
\nGaurush Hiranandani, Warut Vijitbenjaronk, Sanmi Koyejo, Prateek Jain<\/a><\/p>\n

11:00 \u2013 11:45 PDT
\n2nd session: 22:00 \u2013 22:45 PDT
\nBandits with Adversarial Scaling<\/strong><\/a>
\nThodoris Lykouris<\/a>, Vahab Mirrokni, Renato Leme<\/p>\n

12:00 \u2013 12:45 PDT
\n2nd session: July 15 | 01:00 \u2013 01:45 PDT
\nTaskNorm: Rethinking Batch Normalization for Meta-Learning<\/strong><\/a>
\nJohn Bronskill, Jonathan Gordon, James Requeima, Sebastian Nowozin<\/a>, Richard E. Turner<\/p>\n

13:00 \u2013 13:45 PDT
\n2nd session: July 15 | 01:00 \u2013 01:45 PDT
\nGNN-FiLM: Graph Neural Networks with Feature-wise Linear Modulation<\/strong><\/a>
\nMarc Brockschmidt<\/a><\/p>\n

18:00 \u2013 18:45 PDT
\nOnline Learning for Active Cache Synchronization<\/strong><\/a>
\nAndrey Kolobov<\/a>, Sebastien Bubeck<\/a>, Julian Zimmert<\/p>\n

18:00 \u2013 18:45 PDT
\nScalable Nearest Neighbor Search for Optimal Transport<\/strong><\/a>
\nArturs Backurs, Yihe Dong<\/strong>, Piotr Indyk, Ilya Razenshteyn<\/a>, Tal Wagner<\/p>\n

18:00 \u2013 18:45 PDT
\nFaster Graph Embeddings via Coarsening<\/strong><\/a>
\nMatthew Fahrbach, Gramoz Goranci, Sushant Sachdeva, Richard Peng, Chi Wang<\/a><\/p>\n

18:00 \u2013 18:45 PDT
\nWhat is Local Optimality in Nonconvex-Nonconcave Minimax Optimization?<\/strong><\/a>
\nChi Jin, Praneeth Netrapalli<\/a>, Michael Jordan<\/p>\n

19:00 \u2013 19:45 PDT
\nRandomized Smoothing of All Shapes and Sizes<\/strong><\/a>
\nGreg Yang<\/a>, Tony Duan<\/strong>, J. Edward Hu<\/strong>, Hadi Salman<\/strong>, Ilya Razenshteyn<\/a>, Jerry Li<\/a><\/p>\n

19:00 \u2013 19:45 PDT
\nAn end-to-end approach for the verification problem: learning the right distance<\/strong><\/a>
\nJoao Monteiro, Isabela Albuquerque, Jahangir Alam, R Devon Hjelm<\/a>, Tiago Falk<\/p>\n

19:00 \u2013 19:45 PDT
\nCombinatorial Pure Exploration for Dueling Bandit<\/strong><\/a>
\nWei Chen<\/a>, Yihan Du, Longbo Huang, Haoyu Zhao<\/p>\n

19:00 \u2013 19:45 PDT
\nDistance Metric Learning with Joint Representation Diversification<\/strong><\/a>
\nXu Chu, Yang Lin, Xiting Wang<\/a>, Xin Gao, Qi Tong, Hailong Yu, Yasha Wang<\/p>\n

19:00 \u2013 19:45 PDT
\nEfficient Domain Generalization via Common-Specific Low-Rank Decomposition<\/strong><\/a>
\nVihari Piratla<\/strong>, Praneeth Netrapalli<\/a>, Sunita Sarawagi<\/p>\n

19:00 \u2013 19:45 PDT
\nInformative Dropout for Robust Representation Learning: A Shape-bias Perspective<\/strong><\/a>
\nBaifeng Shi, Dinghuai Zhang, Qi Dai<\/a>, Jingdong Wang<\/a>, Zhanxing Zhu, Yadong Mu<\/p>\n

19:00 \u2013 19:45 PDT
\nDifferentially Private Set Union<\/strong><\/a>
\nPankaj Gulhane<\/strong>, Sivakanth Gopi<\/a>, Janardhan Kulkarni<\/a>, Judy Hanwen Shen<\/strong>, Milad Shokouhi<\/a>, Sergey Yekhanin<\/a><\/p>\n

20:00 \u2013 20:45 PDT
\nNGBoost: Natural Gradient Boosting for Probabilistic Prediction<\/strong><\/a>
\nTony Duan<\/strong>, Anand Avati, Daisy Ding, Khanh K. Thai, Sanjay Basu, Andrew Ng, Alejandro Schuler<\/p>\n

20:00 \u2013 20:45 PDT
\nPrivate Reinforcement Learning with PAC and Regret Guarantees<\/strong><\/a>
\nGiuseppe Vietri, Borja de Balle Pigem, Akshay Krishnamurthy<\/a>, Steven Wu<\/p>\n

20:00 \u2013 20:45 PDT
\nFeature Quantization Improves GAN Training<\/strong><\/a>
\nYang Zhao, Chunyuan Li<\/a>, Ping Yu, Jianfeng Gao<\/a>, Changyou Chen<\/p>\n

21:00 \u2013 21:45 PDT
\nWorking Memory Graphs<\/strong><\/a>
\nRicky Loynd<\/a>, Roland Fernandez<\/a>, Asli Celikyilmaz<\/a>, Adith Swaminathan<\/a>, Matthew Hausknecht<\/a><\/p>\n

21:00 \u2013 21:45 PDT
\nNear-optimal Sample Complexity Bounds for Learning Latent\u00a0k\u2212polytopes and applications to Ad-Mixtures<\/strong><\/a>
\nChiranjib Bhattacharyya, Ravindran Kannan<\/a><\/p>\n

21:00 \u2013 21:45 PDT
\nDiscount Factor as a Regularizer in Reinforcement Learning<\/strong><\/a>
\nRon Amit, Kamil Ciosek<\/a>, Ron Meir<\/p>\n

21:00 \u2013 21:45 PDT
\nDROCC: Deep Robust One-Class Classification<\/strong><\/a>
\nSachin Goyal<\/strong>, Aditi Raghunathan, Moksh Jain, Harsha Vardhan Simhadri<\/a>, Prateek Jain<\/a><\/p>\n

22:00 \u2013 22:45 PDT
\nOptimization and Analysis of the pAp@k Metric for Recommender Systems<\/strong><\/a>
\nGaurush Hiranandani, Warut Vijitbenjaronk, Sanmi Koyejo, Prateek Jain<\/a><\/p>\n

22:00 \u2013 22:45 PDT
\nBandits with Adversarial Scaling<\/strong><\/a>
\nThodoris Lykouris<\/a>, Vahab Mirrokni, Renato Leme<\/p>\n

22:00 \u2013 22:45 PDT
\nHow Good is the Bayes Posterior in Deep Neural Networks Really<\/strong><\/a>
\nFlorian Wenzel, Kevin Roth, Bastiaan S. Veeling, Jakub Swiatkowski, Linh Tran, Stephan Mandt, Jasper Snoek, Tim Salimans, Rodolphe Jenatton, Sebastian Nowozin<\/a><\/p>\n

\n

Wednesday, July 15<\/h2>\n

01:00 \u2013 01:45 PDT
\nGNN-FiLM: Graph Neural Networks with Feature-wise Linear Modulation<\/strong><\/a>
\nMarc Brockschmidt<\/a><\/p>\n

01:00 \u2013 01:45 PDT
\nTaskNorm: Rethinking Batch Normalization for Meta-Learning<\/strong><\/a>
\nJohn Bronskill, Jonathan Gordon, James Requeima, Sebastian Nowozin<\/a>, Richard E. Turner<\/p>\n

05:00 \u2013 05:45 PDT
\n2nd session: 16:00 \u2013 16:45 PDT
\nAdaptive Estimator Selection for Off-Policy Evaluation<\/strong><\/a>
\nYi Su, Pavithra Srinath<\/a>, Akshay Krishnamurthy<\/a><\/p>\n

05:00 \u2013 05:45 PDT
\n2nd session: 16:00 \u2013 16:45 PDT
\nPrivately Learning Markov Random Fields<\/strong><\/a>
\nGautam Kamath, Janardhan Kulkarni<\/a>, Steven Wu, Huanyu Zhang<\/p>\n

08:00 \u2013 08:45 PDT
\n2nd session: 21:00 \u2013 21:45 PDT
\nThe Non-IID Data Quagmire of Decentralized Machine Learning<\/strong><\/a>
\nKevin Hsieh<\/strong>, Amar Phanishayee<\/a>, Onur Mutlu, Phillip Gibbons<\/p>\n

08:00 \u2013 08:45 PDT
\n2nd session: 21:00 \u2013 21:45 PDT
\nAlleviating Privacy Attacks via Causal Learning<\/strong><\/a>
\nShruti Tople<\/a>, Amit Sharma<\/a>, Aditya Nori<\/a><\/p>\n

08:00 \u2013 08:45 PDT
\n2nd session: 21:00 \u2013 21:45 PDT
\n(Locally) Differentially Private Combinatorial Semi-Bandits<\/strong><\/a>
\nXiaoyu Chen, Kai Zheng, Zixin Zhou, Yunchang Yang, Wei Chen<\/a>, Liwei Wang<\/p>\n

08:00 \u2013 08:45 PDT
\n2nd session: 20:00 \u2013 20:45 PDT
\nThe Usual Suspects? Reassessing Blame for VAE Posterior Collapse<\/strong><\/a>
\nBin Dai, Ziyu Wang, David Wipf<\/strong><\/p>\n

10:00 \u2013 10:45 PDT
\n2nd session: 21:00 \u2013 21:45 PDT
\nSingle Point Transductive Prediction<\/strong><\/a>
\nNilesh Tripuraneni, Lester Mackey<\/a><\/p>\n

10:00 \u2013 10:45 PDT
\n2nd session: 21:00 \u2013 21:45 PDT
\nLearning Calibratable Policies using Programmatic Style-Consistency<\/strong><\/a>
\nEric Zhan, Albert Tseng, Yisong Yue, Adith Swaminathan<\/a>, Matthew Hausknecht<\/a><\/p>\n

11:00 \u2013 11:45 PDT
\n2nd session: 22:00 \u2013 22:45 PDT
\nStatistically Preconditioned Accelerated Gradient Method for Distributed Optimization<\/strong><\/a>
\nHadrien Hendrikx, Lin Xiao<\/a>, Sebastien Bubeck<\/a>, Francis Bach, Laurent Massouli\u00e9<\/strong><\/p>\n

12:00 \u2013 12:45 PDT
\n2nd session: July 16 | 01:00 \u2013 01:45 PDT
\nNeuro-Symbolic Visual Reasoning: Disentangling “Visual” from “Reasoning”<\/strong><\/a>
\nSaeed Amizadeh<\/strong>, Hamid Palangi<\/a>, Oleksandr Polozov<\/a>, Yichen Huang<\/strong>, Kazuhito Koishida<\/a><\/p>\n

16:00 \u2013 16:45 PDT
\n2nd session: July 16 | 03:00 \u2013 03:45 PDT
\nOptimization from Structured Samples for Coverage Functions<\/strong><\/a>
\nWei Chen<\/a>, Xiaoming Sun, Jialin Zhang, Zhijie Zhang<\/p>\n

16:00 \u2013 16:45 PDT
\nAdaptive Estimator Selection for Off-Policy Evaluation<\/strong><\/a>
\nYi Su, Pavithra Srinath<\/a>, Akshay Krishnamurthy<\/a><\/p>\n

16:00 \u2013 16:45 PDT
\nPrivately Learning Markov Random Fields<\/strong><\/a>
\nGautam Kamath, Janardhan Kulkarni<\/a>, Steven Wu, Huanyu Zhang<\/p>\n

20:00 \u2013 20:45 PDT
\nThe Usual Suspects? Reassessing Blame for VAE Posterior Collapse<\/strong><\/a>
\nBin Dai, Ziyu Wang, David Wipf<\/strong><\/p>\n

21:00 \u2013 21:45 PDT
\nThe Non-IID Data Quagmire of Decentralized Machine Learning<\/strong><\/a>
\nKevin Hsieh<\/strong>, Amar Phanishayee<\/a>, Onur Mutlu, Phillip Gibbons<\/p>\n

21:00 \u2013 21:45 PDT
\nSingle Point Transductive Prediction<\/strong><\/a>
\nNilesh Tripuraneni, Lester Mackey<\/a><\/p>\n

21:00 \u2013 21:45 PDT
\nAlleviating Privacy Attacks via Causal Learning<\/strong><\/a>
\nShruti Tople<\/a>, Amit Sharma<\/a>, Aditya Nori<\/a><\/p>\n

21:00 \u2013 21:45 PDT
\n(Locally) Differentially Private Combinatorial Semi-Bandits<\/strong><\/a>
\nXiaoyu Chen, Kai Zheng, Zixin Zhou, Yunchang Yang, Wei Chen<\/a>, Liwei Wang<\/p>\n

21:00 \u2013 21:45 PDT
\nLearning Calibratable Policies using Programmatic Style-Consistency<\/strong><\/a>
\nEric Zhan, Albert Tseng, Yisong Yue, Adith Swaminathan<\/a>, Matthew Hausknecht<\/a><\/p>\n

22:00 \u2013 22:45 PDT
\nStatistically Preconditioned Accelerated Gradient Method for Distributed Optimization<\/strong><\/a>
\nHadrien Hendrikx, Lin Xiao<\/a>, Sebastien Bubeck<\/a>, Francis Bach, Laurent Massouli\u00e9<\/strong><\/p>\n

\n

Thursday, July 16<\/h2>\n

01:00 \u2013 01:45 PDT
\nNeuro-Symbolic Visual Reasoning: Disentangling “Visual” from “Reasoning”<\/strong><\/a>
\nSaeed Amizadeh<\/strong>, Hamid Palangi<\/a>, Oleksandr Polozov<\/a>, Yichen Huang<\/strong>, Kazuhito Koishida<\/a><\/p>\n

03:00 \u2013 03:45 PDT
\nOptimization from Structured Samples for Coverage Functions<\/strong><\/a>
\nWei Chen<\/a>, Xiaoming Sun, Jialin Zhang, Zhijie Zhang<\/p>\n

06:00 \u2013 06:45 PDT
\n2nd session: July 17 | 18:00 \u2013 18:45 PDT
\nMapping Natural-language Problems to Formal-language Solutions Using Structured Neural Representations<\/strong><\/a>
\nKezhen Chen, Qiuyuan Huang<\/a>, Hamid Palangi<\/a>, Paul Smolensky<\/a>, Ken Forbus, Jianfeng Gao<\/a><\/p>\n

06:00 \u2013 06:45 PDT
\n2nd session: 17:00 \u2013 17:45 PDT
\nBINOCULARS for efficient, nonmyopic sequential experimental design<\/strong><\/a>
\nShali Jiang, Henry Chai, Javier Gonzalez<\/a>, Roman Garnett<\/p>\n

06:00 \u2013 06:45 PDT
\n2nd session: 18:00 \u2013 18:45 PDT
\nBlack-Box Methods for Restoring Monotonicity<\/strong><\/a>
\nEvangelia Gergatsouli, Brendan Lucier<\/a>, Christos Tzamos<\/p>\n

06:00 \u2013 06:45 PDT
\n2nd session: 17:00 \u2013 17:45 PDT
\nCLUB: A Contrastive Log-ratio Upper Bound of Mutual Information<\/strong><\/a>
\nPengyu Cheng, Weituo Hao, Shuyang Dai, Jiachang Liu, Zhe Gan<\/strong>, Lawrence Carin<\/p>\n

06:00 \u2013 06:45 PDT
\n2nd session: 17:00 \u2013 17:45 PDT
\nNeural Datalog Through Time: Informed Temporal Modeling via Logical Specification<\/strong><\/a>
\nHongyuan Mei, Guanghui Qin, Minjie Xu, Jason Eisner<\/strong><\/p>\n

06:00 \u2013 06:45 PDT
\n2nd session: 19:00 \u2013 19:45 PDT
\nProvably Efficient Model-based Policy Adaptation<\/strong><\/a>
\nYuda Song, Aditi Mavalankar, Wen Sun<\/strong>, Sicun Gao<\/p>\n

06:00 \u2013 06:45 PDT
\n2nd session: 18:00 \u2013 18:45 PDT
\nSequence Generation with Mixed Representations<\/strong><\/a>
\nLijun Wu<\/strong>, Shufang Xie<\/strong>, Yingce Xia, Yang Fan, Jian-Huang Lai, Tao Qin<\/a>, Tie-Yan Liu<\/a><\/p>\n

06:00 \u2013 06:45 PDT
\n2nd session: 17:00 \u2013 17:45 PDT
\nReward-Free Exploration for Reinforcement Learning<\/strong><\/a>
\nChi Jin, Akshay Krishnamurthy<\/a>, Max Simchowitz, Tiancheng Yu<\/p>\n

07:00 \u2013 07:45 PDT
\n2nd session: 18:00 \u2013 18:45 PDT
\nNo-Regret and Incentive-Compatible Online Learning<\/strong><\/a>
\nRupert Freeman<\/a>, David Pennock, Charikleia Podimata, Jennifer Wortman Vaughan<\/a><\/p>\n

07:00 \u2013 07:45 PDT
\n2nd session: 18:00 \u2013 18:45 PDT
\nGraph Optimal Transport for Cross-Domain Alignment<\/strong><\/a>
\nLiqun Chen, Zhe Gan<\/strong>, Yu Cheng<\/strong>, Linjie Li<\/strong>, Lawrence Carin, Jingjing Liu<\/a><\/p>\n

07:00 \u2013 07:45 PDT
\n2nd session: 20:00 \u2013 20:45 PDT
\nDoubly Robust Off-policy Evaluation with Shrinkage<\/strong><\/a>
\nYi Su, Maria Dimakopoulou, Akshay Krishnamurthy<\/a>, Miroslav Dudik<\/a><\/p>\n

07:00 \u2013 07:45 PDT
\n2nd session: 18:00 \u2013 18:45 PDT
\nVariance Reduction and Quasi-Newton for Particle-Based Variational Inference<\/strong><\/a> Michael Zhu, Chang Liu<\/strong>, Jun Zhu<\/p>\n

07:00 \u2013 07:45 PDT
\n2nd session: 20:00 \u2013 20:45 PDT
\nKinematic State Abstraction and Provably Efficient Rich-Observation Reinforcement Learning<\/strong><\/a>
\nDipendra Misra<\/a>, Mikael Henaff<\/a>, Akshay Krishnamurthy<\/a>, John Langford<\/a><\/p>\n

08:00 \u2013 08:45 PDT
\n2nd session: 19:00 \u2013 19:45 PDT
\nUniLMv2: Pseudo-Masked Language Models for Unified Language Model Pre-Training<\/strong><\/a>
\nHangbo Bao, Li Dong<\/a>, Furu Wei<\/a>, Wenhui Wang<\/strong>, Nan Yang<\/a>, Xiaodong Liu<\/a>, Yu Wang<\/strong>, Jianfeng Gao<\/a>, Songhao Piao, Ming Zhou<\/a>, Hsiao-Wuen Hon<\/a><\/p>\n

09:00 \u2013 09:45 PDT
\n2nd session: 23:00 \u2013 23:45 PDT
\nBounding the fairness and accuracy of classifiers from population statistics<\/strong><\/a>
\nSivan Sabato<\/strong>, Elad Yom-Tov<\/a><\/p>\n

12:00 \u2013 12:45 PDT
\n2nd session: July 17 | 00:00 \u2013 00:45 PDT
\nSoft Threshold Weight Reparameterization for Learnable Sparsity<\/strong><\/a>
\nAditya Kusupati, Vivek Ramanujan, Raghav Somani, Mitchell Wortsman, Prateek Jain<\/a>, Sham Kakade, Ali Farhadi<\/p>\n

12:00 \u2013 12:45 PDT
\n2nd session: July 17 | 01:00 \u2013 01:45 PDT
\nThe k-tied Normal Distribution: A Compact Parameterization of Gaussian Mean Field Posteriors in Bayesian Neural Networks<\/strong><\/a>
\nJakub Swiatkowski, Kevin Roth, Bastiaan S. Veeling, Linh Tran, Joshua V. Dillon, Stephan Mandt, Jasper Snoek, Tim Salimans, Rodolphe Jenatton, Sebastian Nowozin<\/a><\/p>\n

17:00 \u2013 17:45 PDT
\nBINOCULARS for efficient, nonmyopic sequential experimental design<\/strong><\/a>
\nShali Jiang, Henry Chai, Javier Gonzalez<\/a>, Roman Garnett<\/p>\n

17:00 \u2013 17:45 PDT
\nCLUB: A Contrastive Log-ratio Upper Bound of Mutual Information<\/strong><\/a>
\nPengyu Cheng, Weituo Hao, Shuyang Dai, Jiachang Liu, Zhe Gan<\/strong>, Lawrence Carin<\/p>\n

17:00 \u2013 17:45 PDT
\nNeural Datalog Through Time: Informed Temporal Modeling via Logical Specification<\/strong><\/a>
\nHongyuan Mei, Guanghui Qin, Minjie Xu, Jason Eisner<\/strong><\/p>\n

17:00 \u2013 17:45 PDT
\nReward-Free Exploration for Reinforcement Learning<\/strong><\/a>
\nChi Jin, Akshay Krishnamurthy<\/a>, Max Simchowitz, Tiancheng Yu<\/p>\n

18:00 \u2013 18:45 PDT
\nMapping Natural-language Problems to Formal-language Solutions Using Structured Neural Representations<\/strong><\/a>
\nKezhen Chen, Qiuyuan Huang<\/a>, Hamid Palangi<\/a>, Paul Smolensky<\/a>, Ken Forbus, Jianfeng Gao<\/a><\/p>\n

18:00 \u2013 18:45 PDT
\nNo-Regret and Incentive-Compatible Online Learning<\/strong><\/a>
\nRupert Freeman<\/a>, David Pennock, Charikleia Podimata, Jennifer Wortman Vaughan<\/a><\/p>\n

18:00 \u2013 18:45 PDT
\n2nd session: July 17 | 04:00 \u2013 04:45 PDT
\nOn Layer Normalization in the Transformer Architecture<\/strong><\/a>
\nRuibin Xiong, Yunchang Yang, Di He, Kai Zheng, Shuxin Zheng<\/a>, Chen Xing, Huishuai Zhang<\/a>, Yanyan Lan, Liwei Wang, Tie-Yan Liu<\/a><\/p>\n

18:00 \u2013 18:45 PDT
\nBlack-Box Methods for Restoring Monotonicity<\/strong><\/a>
\nEvangelia Gergatsouli, Brendan Lucier<\/a>, Christos Tzamos<\/p>\n

18:00 \u2013 18:45 PDT
\nGraph Optimal Transport for Cross-Domain Alignment<\/strong><\/a>
\nLiqun Chen, Zhe Gan<\/strong>, Yu Cheng<\/strong>, Linjie Li<\/strong>, Lawrence Carin, Jingjing Liu<\/a><\/p>\n

18:00 \u2013 18:45 PDT
\nVariance Reduction and Quasi-Newton for Particle-Based Variational Inference<\/strong><\/a> Michael Zhu, Chang Liu<\/strong>, Jun Zhu<\/p>\n

18:00 \u2013 18:45 PDT
\nSequence Generation with Mixed Representations<\/strong><\/a>
\nLijun Wu<\/strong>, Shufang Xie<\/strong>, Yingce Xia, Yang Fan, Jian-Huang Lai, Tao Qin<\/a>, Tie-Yan Liu<\/a><\/p>\n

19:00 \u2013 19:45 PDT
\nUniLMv2: Pseudo-Masked Language Models for Unified Language Model Pre-Training<\/strong><\/a>
\nHangbo Bao, Li Dong<\/a>, Furu Wei<\/a>, Wenhui Wang<\/strong>, Nan Yang<\/a>, Xiaodong Liu<\/a>, Yu Wang<\/strong>, Jianfeng Gao<\/a>, Songhao Piao, Ming Zhou<\/a>, Hsiao-Wuen Hon<\/a><\/p>\n

19:00 \u2013 19:45 PDT
\nProvably Efficient Model-based Policy Adaptation<\/strong><\/a>
\nYuda Song, Aditi Mavalankar, Wen Sun<\/strong>, Sicun Gao<\/p>\n

20:00 \u2013 20:45 PDT
\nDoubly Robust Off-policy Evaluation with Shrinkage<\/strong><\/a>
\nYi Su, Maria Dimakopoulou, Akshay Krishnamurthy<\/a>, Miroslav Dudik<\/a><\/p>\n

20:00 \u2013 20:45 PDT
\nKinematic State Abstraction and Provably Efficient Rich-Observation Reinforcement Learning<\/strong><\/a>
\nDipendra Misra<\/a>, Mikael Henaff<\/a>, Akshay Krishnamurthy<\/a>, John Langford<\/a><\/p>\n

23:00 \u2013 23:45 PDT
\nBounding the fairness and accuracy of classifiers from population statistics<\/strong><\/a>
\nSivan Sabato<\/strong>, Elad Yom-Tov<\/a><\/p>\n

\n

Friday, July 17<\/h2>\n

00:00 \u2013 00:45 PDT
\nSoft Threshold Weight Reparameterization for Learnable Sparsity<\/strong><\/a>
\nAditya Kusupati, Vivek Ramanujan, Raghav Somani, Mitchell Wortsman, Prateek Jain<\/a>, Sham Kakade, Ali Farhadi<\/p>\n

01:00 \u2013 01:45 PDT
\nThe k-tied Normal Distribution: A Compact Parameterization of Gaussian Mean Field Posteriors in Bayesian Neural Networks<\/strong><\/a>
\nJakub Swiatkowski, Kevin Roth, Bastiaan S. Veeling, Linh Tran, Joshua V. Dillon, Stephan Mandt, Jasper Snoek, Tim Salimans, Rodolphe Jenatton, Sebastian Nowozin<\/a><\/p>\n

04:00 \u2013 04:45 PDT
\nOn Layer Normalization in the Transformer Architecture<\/strong><\/a>
\nRuibin Xiong, Yunchang Yang, Di He, Kai Zheng, Shuxin Zheng<\/a>, Chen Xing, Huishuai Zhang<\/a>, Yanyan Lan, Liwei Wang, Tie-Yan Liu<\/a>Opens in a new tab<\/span><\/p>\n

July 13 \u2013 18<\/h2>\n

Queer in AI<\/strong> (opens in new tab)<\/span><\/a>
\nCo-organizer: Andrew McNamara<\/a><\/p>\n

Friday, July 17<\/h2>\n

Beyond first order methods in machine learning systems<\/strong> (opens in new tab)<\/span><\/a>
\nInvited Speaker: Lin Xiao<\/a><\/p>\n

Healthcare Systems, Population Health, and the role of health-tech<\/strong> (opens in new tab)<\/span><\/a>
\nCo-organizer: Konstantina Palla<\/a><\/p>\n

Self-supervision in Audio and Speech<\/strong> (opens in new tab)<\/span><\/a>
\nCo-organizer: R Devon Hjelm<\/a><\/p>\n

Theoretical Foundations of Reinforcement Learning<\/strong> (opens in new tab)<\/span><\/a>
\nCo-organizers: Thodoris Lykouris<\/a>
\nInvited Speaker: Akshay Krishnamurthy<\/a><\/p>\n

Workshop on eXtreme Classification: Theory and Applications<\/strong> (opens in new tab)<\/span><\/a>
\nCo-organizers: John Langford<\/a>, Yashoteja Prabhu
\nInvited Speaker: Manik Varma<\/a><\/p>\n

Saturday, July 18<\/h2>\n

1st Workshop on Language in Reinforcement Learning (LaReL)<\/strong> (opens in new tab)<\/span><\/a>
\nInvited Speaker: Marc-Alexandre C\u00f4t\u00e9<\/a><\/p>\n

Machine Learning for Global Health<\/strong> (opens in new tab)<\/span><\/a>
\nCo-organizers: Danielle Belgrave<\/a>, Stephanie Hyland<\/a><\/p>\n

Workshop on Learning in Artificial Open Worlds<\/strong> (opens in new tab)<\/span><\/a>
\nCo-organizers: Katja Hofmann<\/a>, Noboru Kuno<\/a>Opens in a new tab<\/span><\/p>\n

Microsoft Booth Schedule at ICML<\/h2>\n

Talk to our experts and learn more about our research and open opportunities.<\/p>\n

Sunday, July 12<\/h3>\n

Live Chat<\/h4>\n\n\n\n\n
11:15 \u2013 12:15 PDT<\/td>\nRicky Loynd, RL<\/td>\n<\/tr>\n
13:45 \u2013 14:45 PDT<\/td>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

Monday, July 13<\/h3>\n

Live Chat<\/h4>\n\n\n\n\n
04:00 \u2013 05:00 PDT<\/td>\nAmit Sharma: Causality, ML explanations<\/td>\n<\/tr>\n
14:00 \u2013 15:00 PDT<\/td>\nAmy Siebenthaler, University\/PhD Recruiting<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

Tuesday, July 14<\/h3>\n

Live Chat<\/h4>\n\n\n\n\n\n\n\n
07:45 \u2013 08:45 PDT<\/td>\nMarc Brockschmidt, GNNs and ML 4 Programming
\nVikas Gosain, University\/PhD Recruiting<\/td>\n<\/tr>\n
10:45 \u2013 11:45 PDT<\/td>\nEdward Tiong, DS\/ML in Microsoft AI Rotation Program
\nVikas Gosain, University\/PhD Recruiting<\/td>\n<\/tr>\n
13:45 \u2013 14:45 PDT<\/td>\nEdward Tiong, DS\/ML in Microsoft AI Rotation Program
\nAkshay Krishnamurthy, RL and learning theory
\nAmy Siebenthaler, University\/PhD Recruiting<\/td>\n<\/tr>\n
17:45 \u2013 18:45 PDT<\/td>\nYang He, DS\/ML in Microsoft AI Rotation Program
\nKevin Hsieh, federated learning and AutoML<\/td>\n<\/tr>\n
20:45 \u2013 21:45 PDT<\/td>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

Wednesday, July 15<\/h3>\n

Live Demos<\/h4>\n\n\n\n\n
04:45 \u2013 05:45 PDT<\/td>\nToolkit for building generalizable and robust ML models
\nAmit Sharma<\/a>, Divyat Mahajan (opens in new tab)<\/span><\/a>, Shruti Tople<\/a><\/td>\n<\/tr>\n
10:45 \u2013 11:45 PDT<\/td>\nLearning calibratable policies using programmatic style-consistency
\nAdith Swaminathan<\/a><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

Live Chat<\/h4>\n\n\n\n\n\n\n\n\n\n
00:45 \u2013 01:45 PDT<\/td>\n<\/td>\n<\/tr>\n
04:45 \u2013 05:45 PDT<\/td>\nElad Yom-Tov, ML and IR for healthcare
\nJavier Gonzalez, Bayesian optimization, probabilistic modeling, causality<\/td>\n<\/tr>\n
07:45 \u2013 08:45 PDT<\/td>\nKevin Yang, computational biology
\nVikas Gosain, University\/PhD Recruiting<\/td>\n<\/tr>\n
10:45 \u2013 11:45 PDT<\/td>\nAdith Swaminathan, RL
\nAmy Siebenthaler, University\/PhD Recruiting<\/td>\n<\/tr>\n
13:45 \u2013 14:45 PDT<\/td>\nSahitya Mantravadi, DS\/ML in Microsoft AI Rotation Program
\nMegha Srivastava, AI Residency Program<\/td>\n<\/tr>\n
17:45 \u2013 18:45 PDT<\/td>\nJason Eisner, MLP & structured prediction<\/td>\n<\/tr>\n
20:45 \u2013 21:45 PDT<\/td>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

Thursday, July 16<\/h3>\n

Live Demos<\/h4>\n\n\n\n
7:45 \u2013 8:45 PDT<\/td>\nToolkit for building generalizable and robust ML models
\nAmit Sharma<\/a>, Divyat Mahajan (opens in new tab)<\/span><\/a>, Shruti Tople<\/a><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

Live Chat<\/h4>\n\n\n\n\n\n\n\n
00:45 \u2013 01:45 PDT<\/td>\nMarc Brockschmidt, GNNs and ML 4 Programming<\/td>\n<\/tr>\n
04:45 \u2013 05:45 PDT<\/td>\nJudy Hanwen Shen, AI Residency Program<\/td>\n<\/tr>\n
07:45 \u2013 08:45 PDT<\/td>\nEdward Tiong, DS\/ML in Microsoft AI Rotation Program
\nAmit Gupte, Program Management in Microsoft AI Rotation Program
\nJason Eisner, NLP & structured prediction
\nVikas Gosain, University\/PhD Recruiting<\/td>\n<\/tr>\n
10:45 \u2013 11:45 PDT<\/td>\nShuo Li, DS\/ML in Microsoft AI Rotation Program
\nYuze Zhang, DS\/ML in Microsoft AI Rotation Program
\nVikas Gosain, University\/PhD Recruiting<\/td>\n<\/tr>\n
13:45 \u2013 14:45 PDT<\/td>\nSahitya Mantravadi, DS\/ML in Microsoft AI Rotation Program<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

Opens in a new tab<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"

Website: ICML 2020 (opens in new tab)Opens in a new tab Microsoft is proud to be a Gold sponsor of the 37th International Conference on Machine Learning (opens in new tab) (ICML), as well as Diamond sponsors at the 1st Women in Machine Learning Un-Workshop (opens in new tab) and Platinum sponsors of the 4th […]<\/p>\n","protected":false},"featured_media":392255,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"_classifai_error":"","msr_startdate":"2020-07-12","msr_enddate":"2020-07-18","msr_location":"Virtual\/Online","msr_expirationdate":"","msr_event_recording_link":"","msr_event_link":"","msr_event_link_redirect":false,"msr_event_time":"","msr_hide_region":false,"msr_private_event":false,"msr_hide_image_in_river":0,"footnotes":""},"research-area":[13556],"msr-region":[256048,197900],"msr-event-type":[197941],"msr-video-type":[],"msr-locale":[268875],"msr-program-audience":[],"msr-post-option":[],"msr-impact-theme":[],"class_list":["post-670011","msr-event","type-msr-event","status-publish","has-post-thumbnail","hentry","msr-research-area-artificial-intelligence","msr-region-global","msr-region-north-america","msr-event-type-conferences","msr-locale-en_us"],"msr_about":"\n\n

Website:<\/strong> ICML 2020 (opens in new tab)<\/span><\/a>Opens in a new tab<\/span><\/p>\n

Microsoft is proud to be a Gold sponsor of the 37th International Conference on Machine Learning<\/a> (ICML), as well as Diamond sponsors at the 1st Women in Machine Learning Un-Workshop<\/a> and Platinum sponsors of the 4th Queer in AI Workshop<\/a>. We have over 50 papers accepted to the conference, and you can find details of our publications on the Accepted papers<\/a> and Workshops<\/a> tabs.<\/p>\n

Committee chairs<\/h2>\n

ICML President: John Langford<\/a>
\nICML Board Members: Hal Daum\u00e9 III<\/a>, Hanna Wallach<\/a>
\nProgram Co-chair: Hal Daum\u00e9 III<\/a><\/p>\n

Invited speaker<\/h2>\n

Tuesday, July 14<\/h3>\n

05:00 \u2013 06:45 PDT & 16:00 \u2013 17:45 PDT
\nDoing Some Good with Machine Learning<\/strong>
\nInvited Speaker: Lester Mackey<\/a>Opens in a new tab<\/span><\/p>\n

Tuesday, July 14<\/h2>\n

07:00 \u2013 07:45 PDT
\n2nd session: 20:00 \u2013 20:45 PDT
\nNGBoost: Natural Gradient Boosting for Probabilistic Prediction<\/strong><\/a>
\nTony Duan<\/strong>, Anand Avati, Daisy Ding, Khanh K. Thai, Sanjay Basu, Andrew Ng, Alejandro Schuler<\/p>\n

07:00 \u2013 07:45 PDT
\n2nd session: 18:00 \u2013 18:45 PDT
\nOnline Learning for Active Cache Synchronization<\/strong><\/a>
\nAndrey Kolobov<\/a>, Sebastien Bubeck<\/a>, Julian Zimmert<\/p>\n

07:00 \u2013 07:45 PDT
\n2nd session: 19:00 \u2013 19:45 PDT
\nRandomized Smoothing of All Shapes and Sizes<\/strong><\/a>
\nGreg Yang<\/a>, Tony Duan<\/strong>, J. Edward Hu<\/strong>, Hadi Salman<\/strong>, Ilya Razenshteyn<\/a>, Jerry Li<\/a><\/p>\n

07:00 \u2013 07:45 PDT
\n2nd session: 20:00 \u2013 20:45 PDT
\nPrivate Reinforcement Learning with PAC and Regret Guarantees<\/strong><\/a>
\nGiuseppe Vietri, Borja de Balle Pigem, Akshay Krishnamurthy<\/a>, Steven Wu<\/p>\n

07:00 \u2013 07:45 PDT
\n2nd session: 18:00 \u2013 18:45 PDT
\nScalable Nearest Neighbor Search for Optimal Transport<\/strong><\/a>
\nArturs Backurs, Yihe Dong<\/strong>, Piotr Indyk, Ilya Razenshteyn<\/a>, Tal Wagner<\/p>\n

07:00 \u2013 07:45 PDT
\n2nd session: 19:00 \u2013 19:45 PDT
\nCombinatorial Pure Exploration for Dueling Bandit<\/strong><\/a>
\nWei Chen<\/a>, Yihan Du, Longbo Huang, Haoyu Zhao<\/p>\n

07:00 \u2013 07:45 PDT
\n2nd session: 19:00 \u2013 19:45 PDT
\nDistance Metric Learning with Joint Representation Diversification<\/strong><\/a>
\nXu Chu, Yang Lin, Xiting Wang<\/a>, Xin Gao, Qi Tong, Hailong Yu, Yasha Wang<\/p>\n

07:00 \u2013 07:45 PDT
\n2nd session: 19:00 \u2013 19:45 PDT
\nEfficient Domain Generalization via Common-Specific Low-Rank Decomposition<\/strong><\/a>
\nVihari Piratla<\/strong>, Praneeth Netrapalli<\/a>, Sunita Sarawagi<\/p>\n

07:00 \u2013 07:45 PDT
\n2nd session: 18:00 \u2013 18:45 PDT
\nFaster Graph Embeddings via Coarsening<\/strong><\/a>
\nMatthew Fahrbach, Gramoz Goranci, Sushant Sachdeva, Richard Peng, Chi Wang<\/a><\/p>\n

07:00 \u2013 07:45 PDT
\n2nd session: 18:00 \u2013 18:45 PDT
\nWhat is Local Optimality in Nonconvex-Nonconcave Minimax Optimization?<\/strong><\/a>
\nChi Jin, Praneeth Netrapalli<\/a>, Michael Jordan<\/p>\n

08:00 \u2013 08:45 PDT
\n2nd session: 19:00 \u2013 19:45 PDT
\nAn end-to-end approach for the verification problem: learning the right distance<\/strong><\/a>
\nJoao Monteiro, Isabela Albuquerque, Jahangir Alam, R Devon Hjelm<\/a>, Tiago Falk<\/p>\n

08:00 \u2013 08:45 PDT
\n2nd session: 21:00 \u2013 21:45 PDT
\nWorking Memory Graphs<\/strong><\/a>
\nRicky Loynd<\/a>, Roland Fernandez<\/a>, Asli Celikyilmaz<\/a>, Adith Swaminathan<\/a>, Matthew Hausknecht<\/a><\/p>\n

08:00 \u2013 08:45 PDT
\n2nd session: 19:00 \u2013 19:45 PDT
\nInformative Dropout for Robust Representation Learning: A Shape-bias Perspective<\/strong><\/a>
\nBaifeng Shi, Dinghuai Zhang, Qi Dai<\/a>, Jingdong Wang<\/a>, Zhanxing Zhu, Yadong Mu<\/p>\n

08:00 \u2013 08:45 PDT
\n2nd session: 21:00 \u2013 21:45 PDT
\nNear-optimal Sample Complexity Bounds for Learning Latent\u00a0k\u2212polytopes and applications to Ad-Mixtures<\/strong><\/a>
\nChiranjib Bhattacharyya, Ravindran Kannan<\/a><\/p>\n

08:00 \u2013 08:45 PDT
\n2nd session: 19:00 \u2013 19:45 PDT
\nDifferentially Private Set Union<\/strong><\/a>
\nPankaj Gulhane<\/strong>, Sivakanth Gopi<\/a>, Janardhan Kulkarni<\/a>, Judy Hanwen Shen<\/strong>, Milad Shokouhi<\/a>, Sergey Yekhanin<\/a><\/p>\n

08:00 \u2013 08:45 PDT
\n2nd session: 21:00 \u2013 21:45 PDT
\nDiscount Factor as a Regularizer in Reinforcement Learning<\/strong><\/a>
\nRon Amit, Kamil Ciosek<\/a>, Ron Meir<\/p>\n

08:00 \u2013 08:45 PDT
\n2nd session: 21:00 \u2013 21:45 PDT
\nDROCC: Deep Robust One-Class Classification<\/strong><\/a>
\nSachin Goyal<\/strong>, Aditi Raghunathan, Moksh Jain, Harsha Vardhan Simhadri<\/a>, Prateek Jain<\/a><\/p>\n

09:00 \u2013 09:45 PDT
\n2nd session: 20:00 \u2013 20:45 PDT
\nFeature Quantization Improves GAN Training<\/strong><\/a>
\nYang Zhao, Chunyuan Li<\/a>, Ping Yu, Jianfeng Gao<\/a>, Changyou Chen<\/p>\n

09:00 \u2013 09:45 PDT
\n2nd session: 22:00 \u2013 22:45 PDT
\nHow Good is the Bayes Posterior in Deep Neural Networks Really<\/strong><\/a>
\nFlorian Wenzel, Kevin Roth, Bastiaan S. Veeling, Jakub Swiatkowski, Linh Tran, Stephan Mandt, Jasper Snoek, Tim Salimans, Rodolphe Jenatton, Sebastian Nowozin<\/a><\/p>\n

11:00 \u2013 11:45 PDT
\n2nd session: 22:00 \u2013 22:45 PDT
\nOptimization and Analysis of the pAp@k Metric for Recommender Systems<\/strong><\/a>
\nGaurush Hiranandani, Warut Vijitbenjaronk, Sanmi Koyejo, Prateek Jain<\/a><\/p>\n

11:00 \u2013 11:45 PDT
\n2nd session: 22:00 \u2013 22:45 PDT
\nBandits with Adversarial Scaling<\/strong><\/a>
\nThodoris Lykouris<\/a>, Vahab Mirrokni, Renato Leme<\/p>\n

12:00 \u2013 12:45 PDT
\n2nd session: July 15 | 01:00 \u2013 01:45 PDT
\nTaskNorm: Rethinking Batch Normalization for Meta-Learning<\/strong><\/a>
\nJohn Bronskill, Jonathan Gordon, James Requeima, Sebastian Nowozin<\/a>, Richard E. Turner<\/p>\n

13:00 \u2013 13:45 PDT
\n2nd session: July 15 | 01:00 \u2013 01:45 PDT
\nGNN-FiLM: Graph Neural Networks with Feature-wise Linear Modulation<\/strong><\/a>
\nMarc Brockschmidt<\/a><\/p>\n

18:00 \u2013 18:45 PDT
\nOnline Learning for Active Cache Synchronization<\/strong><\/a>
\nAndrey Kolobov<\/a>, Sebastien Bubeck<\/a>, Julian Zimmert<\/p>\n

18:00 \u2013 18:45 PDT
\nScalable Nearest Neighbor Search for Optimal Transport<\/strong><\/a>
\nArturs Backurs, Yihe Dong<\/strong>, Piotr Indyk, Ilya Razenshteyn<\/a>, Tal Wagner<\/p>\n

18:00 \u2013 18:45 PDT
\nFaster Graph Embeddings via Coarsening<\/strong><\/a>
\nMatthew Fahrbach, Gramoz Goranci, Sushant Sachdeva, Richard Peng, Chi Wang<\/a><\/p>\n

18:00 \u2013 18:45 PDT
\nWhat is Local Optimality in Nonconvex-Nonconcave Minimax Optimization?<\/strong><\/a>
\nChi Jin, Praneeth Netrapalli<\/a>, Michael Jordan<\/p>\n

19:00 \u2013 19:45 PDT
\nRandomized Smoothing of All Shapes and Sizes<\/strong><\/a>
\nGreg Yang<\/a>, Tony Duan<\/strong>, J. Edward Hu<\/strong>, Hadi Salman<\/strong>, Ilya Razenshteyn<\/a>, Jerry Li<\/a><\/p>\n

19:00 \u2013 19:45 PDT
\nAn end-to-end approach for the verification problem: learning the right distance<\/strong><\/a>
\nJoao Monteiro, Isabela Albuquerque, Jahangir Alam, R Devon Hjelm<\/a>, Tiago Falk<\/p>\n

19:00 \u2013 19:45 PDT
\nCombinatorial Pure Exploration for Dueling Bandit<\/strong><\/a>
\nWei Chen<\/a>, Yihan Du, Longbo Huang, Haoyu Zhao<\/p>\n

19:00 \u2013 19:45 PDT
\nDistance Metric Learning with Joint Representation Diversification<\/strong><\/a>
\nXu Chu, Yang Lin, Xiting Wang<\/a>, Xin Gao, Qi Tong, Hailong Yu, Yasha Wang<\/p>\n

19:00 \u2013 19:45 PDT
\nEfficient Domain Generalization via Common-Specific Low-Rank Decomposition<\/strong><\/a>
\nVihari Piratla<\/strong>, Praneeth Netrapalli<\/a>, Sunita Sarawagi<\/p>\n

19:00 \u2013 19:45 PDT
\nInformative Dropout for Robust Representation Learning: A Shape-bias Perspective<\/strong><\/a>
\nBaifeng Shi, Dinghuai Zhang, Qi Dai<\/a>, Jingdong Wang<\/a>, Zhanxing Zhu, Yadong Mu<\/p>\n

19:00 \u2013 19:45 PDT
\nDifferentially Private Set Union<\/strong><\/a>
\nPankaj Gulhane<\/strong>, Sivakanth Gopi<\/a>, Janardhan Kulkarni<\/a>, Judy Hanwen Shen<\/strong>, Milad Shokouhi<\/a>, Sergey Yekhanin<\/a><\/p>\n

20:00 \u2013 20:45 PDT
\nNGBoost: Natural Gradient Boosting for Probabilistic Prediction<\/strong><\/a>
\nTony Duan<\/strong>, Anand Avati, Daisy Ding, Khanh K. Thai, Sanjay Basu, Andrew Ng, Alejandro Schuler<\/p>\n

20:00 \u2013 20:45 PDT
\nPrivate Reinforcement Learning with PAC and Regret Guarantees<\/strong><\/a>
\nGiuseppe Vietri, Borja de Balle Pigem, Akshay Krishnamurthy<\/a>, Steven Wu<\/p>\n

20:00 \u2013 20:45 PDT
\nFeature Quantization Improves GAN Training<\/strong><\/a>
\nYang Zhao, Chunyuan Li<\/a>, Ping Yu, Jianfeng Gao<\/a>, Changyou Chen<\/p>\n

21:00 \u2013 21:45 PDT
\nWorking Memory Graphs<\/strong><\/a>
\nRicky Loynd<\/a>, Roland Fernandez<\/a>, Asli Celikyilmaz<\/a>, Adith Swaminathan<\/a>, Matthew Hausknecht<\/a><\/p>\n

21:00 \u2013 21:45 PDT
\nNear-optimal Sample Complexity Bounds for Learning Latent\u00a0k\u2212polytopes and applications to Ad-Mixtures<\/strong><\/a>
\nChiranjib Bhattacharyya, Ravindran Kannan<\/a><\/p>\n

21:00 \u2013 21:45 PDT
\nDiscount Factor as a Regularizer in Reinforcement Learning<\/strong><\/a>
\nRon Amit, Kamil Ciosek<\/a>, Ron Meir<\/p>\n

21:00 \u2013 21:45 PDT
\nDROCC: Deep Robust One-Class Classification<\/strong><\/a>
\nSachin Goyal<\/strong>, Aditi Raghunathan, Moksh Jain, Harsha Vardhan Simhadri<\/a>, Prateek Jain<\/a><\/p>\n

22:00 \u2013 22:45 PDT
\nOptimization and Analysis of the pAp@k Metric for Recommender Systems<\/strong><\/a>
\nGaurush Hiranandani, Warut Vijitbenjaronk, Sanmi Koyejo, Prateek Jain<\/a><\/p>\n

22:00 \u2013 22:45 PDT
\nBandits with Adversarial Scaling<\/strong><\/a>
\nThodoris Lykouris<\/a>, Vahab Mirrokni, Renato Leme<\/p>\n

22:00 \u2013 22:45 PDT
\nHow Good is the Bayes Posterior in Deep Neural Networks Really<\/strong><\/a>
\nFlorian Wenzel, Kevin Roth, Bastiaan S. Veeling, Jakub Swiatkowski, Linh Tran, Stephan Mandt, Jasper Snoek, Tim Salimans, Rodolphe Jenatton, Sebastian Nowozin<\/a><\/p>\n

\n

Wednesday, July 15<\/h2>\n

01:00 \u2013 01:45 PDT
\nGNN-FiLM: Graph Neural Networks with Feature-wise Linear Modulation<\/strong><\/a>
\nMarc Brockschmidt<\/a><\/p>\n

01:00 \u2013 01:45 PDT
\nTaskNorm: Rethinking Batch Normalization for Meta-Learning<\/strong><\/a>
\nJohn Bronskill, Jonathan Gordon, James Requeima, Sebastian Nowozin<\/a>, Richard E. Turner<\/p>\n

05:00 \u2013 05:45 PDT
\n2nd session: 16:00 \u2013 16:45 PDT
\nAdaptive Estimator Selection for Off-Policy Evaluation<\/strong><\/a>
\nYi Su, Pavithra Srinath<\/a>, Akshay Krishnamurthy<\/a><\/p>\n

05:00 \u2013 05:45 PDT
\n2nd session: 16:00 \u2013 16:45 PDT
\nPrivately Learning Markov Random Fields<\/strong><\/a>
\nGautam Kamath, Janardhan Kulkarni<\/a>, Steven Wu, Huanyu Zhang<\/p>\n

08:00 \u2013 08:45 PDT
\n2nd session: 21:00 \u2013 21:45 PDT
\nThe Non-IID Data Quagmire of Decentralized Machine Learning<\/strong><\/a>
\nKevin Hsieh<\/strong>, Amar Phanishayee<\/a>, Onur Mutlu, Phillip Gibbons<\/p>\n

08:00 \u2013 08:45 PDT
\n2nd session: 21:00 \u2013 21:45 PDT
\nAlleviating Privacy Attacks via Causal Learning<\/strong><\/a>
\nShruti Tople<\/a>, Amit Sharma<\/a>, Aditya Nori<\/a><\/p>\n

08:00 \u2013 08:45 PDT
\n2nd session: 21:00 \u2013 21:45 PDT
\n(Locally) Differentially Private Combinatorial Semi-Bandits<\/strong><\/a>
\nXiaoyu Chen, Kai Zheng, Zixin Zhou, Yunchang Yang, Wei Chen<\/a>, Liwei Wang<\/p>\n

08:00 \u2013 08:45 PDT
\n2nd session: 20:00 \u2013 20:45 PDT
\nThe Usual Suspects? Reassessing Blame for VAE Posterior Collapse<\/strong><\/a>
\nBin Dai, Ziyu Wang, David Wipf<\/strong><\/p>\n

10:00 \u2013 10:45 PDT
\n2nd session: 21:00 \u2013 21:45 PDT
\nSingle Point Transductive Prediction<\/strong><\/a>
\nNilesh Tripuraneni, Lester Mackey<\/a><\/p>\n

10:00 \u2013 10:45 PDT
\n2nd session: 21:00 \u2013 21:45 PDT
\nLearning Calibratable Policies using Programmatic Style-Consistency<\/strong><\/a>
\nEric Zhan, Albert Tseng, Yisong Yue, Adith Swaminathan<\/a>, Matthew Hausknecht<\/a><\/p>\n

11:00 \u2013 11:45 PDT
\n2nd session: 22:00 \u2013 22:45 PDT
\nStatistically Preconditioned Accelerated Gradient Method for Distributed Optimization<\/strong><\/a>
\nHadrien Hendrikx, Lin Xiao<\/a>, Sebastien Bubeck<\/a>, Francis Bach, Laurent Massouli\u00e9<\/strong><\/p>\n

12:00 \u2013 12:45 PDT
\n2nd session: July 16 | 01:00 \u2013 01:45 PDT
\nNeuro-Symbolic Visual Reasoning: Disentangling “Visual” from “Reasoning”<\/strong><\/a>
\nSaeed Amizadeh<\/strong>, Hamid Palangi<\/a>, Oleksandr Polozov<\/a>, Yichen Huang<\/strong>, Kazuhito Koishida<\/a><\/p>\n

16:00 \u2013 16:45 PDT
\n2nd session: July 16 | 03:00 \u2013 03:45 PDT
\nOptimization from Structured Samples for Coverage Functions<\/strong><\/a>
\nWei Chen<\/a>, Xiaoming Sun, Jialin Zhang, Zhijie Zhang<\/p>\n

16:00 \u2013 16:45 PDT
\nAdaptive Estimator Selection for Off-Policy Evaluation<\/strong><\/a>
\nYi Su, Pavithra Srinath<\/a>, Akshay Krishnamurthy<\/a><\/p>\n

16:00 \u2013 16:45 PDT
\nPrivately Learning Markov Random Fields<\/strong><\/a>
\nGautam Kamath, Janardhan Kulkarni<\/a>, Steven Wu, Huanyu Zhang<\/p>\n

20:00 \u2013 20:45 PDT
\nThe Usual Suspects? Reassessing Blame for VAE Posterior Collapse<\/strong><\/a>
\nBin Dai, Ziyu Wang, David Wipf<\/strong><\/p>\n

21:00 \u2013 21:45 PDT
\nThe Non-IID Data Quagmire of Decentralized Machine Learning<\/strong><\/a>
\nKevin Hsieh<\/strong>, Amar Phanishayee<\/a>, Onur Mutlu, Phillip Gibbons<\/p>\n

21:00 \u2013 21:45 PDT
\nSingle Point Transductive Prediction<\/strong><\/a>
\nNilesh Tripuraneni, Lester Mackey<\/a><\/p>\n

21:00 \u2013 21:45 PDT
\nAlleviating Privacy Attacks via Causal Learning<\/strong><\/a>
\nShruti Tople<\/a>, Amit Sharma<\/a>, Aditya Nori<\/a><\/p>\n

21:00 \u2013 21:45 PDT
\n(Locally) Differentially Private Combinatorial Semi-Bandits<\/strong><\/a>
\nXiaoyu Chen, Kai Zheng, Zixin Zhou, Yunchang Yang, Wei Chen<\/a>, Liwei Wang<\/p>\n

21:00 \u2013 21:45 PDT
\nLearning Calibratable Policies using Programmatic Style-Consistency<\/strong><\/a>
\nEric Zhan, Albert Tseng, Yisong Yue, Adith Swaminathan<\/a>, Matthew Hausknecht<\/a><\/p>\n

22:00 \u2013 22:45 PDT
\nStatistically Preconditioned Accelerated Gradient Method for Distributed Optimization<\/strong><\/a>
\nHadrien Hendrikx, Lin Xiao<\/a>, Sebastien Bubeck<\/a>, Francis Bach, Laurent Massouli\u00e9<\/strong><\/p>\n

\n

Thursday, July 16<\/h2>\n

01:00 \u2013 01:45 PDT
\nNeuro-Symbolic Visual Reasoning: Disentangling “Visual” from “Reasoning”<\/strong><\/a>
\nSaeed Amizadeh<\/strong>, Hamid Palangi<\/a>, Oleksandr Polozov<\/a>, Yichen Huang<\/strong>, Kazuhito Koishida<\/a><\/p>\n

03:00 \u2013 03:45 PDT
\nOptimization from Structured Samples for Coverage Functions<\/strong><\/a>
\nWei Chen<\/a>, Xiaoming Sun, Jialin Zhang, Zhijie Zhang<\/p>\n

06:00 \u2013 06:45 PDT
\n2nd session: July 17 | 18:00 \u2013 18:45 PDT
\nMapping Natural-language Problems to Formal-language Solutions Using Structured Neural Representations<\/strong><\/a>
\nKezhen Chen, Qiuyuan Huang<\/a>, Hamid Palangi<\/a>, Paul Smolensky<\/a>, Ken Forbus, Jianfeng Gao<\/a><\/p>\n

06:00 \u2013 06:45 PDT
\n2nd session: 17:00 \u2013 17:45 PDT
\nBINOCULARS for efficient, nonmyopic sequential experimental design<\/strong><\/a>
\nShali Jiang, Henry Chai, Javier Gonzalez<\/a>, Roman Garnett<\/p>\n

06:00 \u2013 06:45 PDT
\n2nd session: 18:00 \u2013 18:45 PDT
\nBlack-Box Methods for Restoring Monotonicity<\/strong><\/a>
\nEvangelia Gergatsouli, Brendan Lucier<\/a>, Christos Tzamos<\/p>\n

06:00 \u2013 06:45 PDT
\n2nd session: 17:00 \u2013 17:45 PDT
\nCLUB: A Contrastive Log-ratio Upper Bound of Mutual Information<\/strong><\/a>
\nPengyu Cheng, Weituo Hao, Shuyang Dai, Jiachang Liu, Zhe Gan<\/strong>, Lawrence Carin<\/p>\n

06:00 \u2013 06:45 PDT
\n2nd session: 17:00 \u2013 17:45 PDT
\nNeural Datalog Through Time: Informed Temporal Modeling via Logical Specification<\/strong><\/a>
\nHongyuan Mei, Guanghui Qin, Minjie Xu, Jason Eisner<\/strong><\/p>\n

06:00 \u2013 06:45 PDT
\n2nd session: 19:00 \u2013 19:45 PDT
\nProvably Efficient Model-based Policy Adaptation<\/strong><\/a>
\nYuda Song, Aditi Mavalankar, Wen Sun<\/strong>, Sicun Gao<\/p>\n

06:00 \u2013 06:45 PDT
\n2nd session: 18:00 \u2013 18:45 PDT
\nSequence Generation with Mixed Representations<\/strong><\/a>
\nLijun Wu<\/strong>, Shufang Xie<\/strong>, Yingce Xia, Yang Fan, Jian-Huang Lai, Tao Qin<\/a>, Tie-Yan Liu<\/a><\/p>\n

06:00 \u2013 06:45 PDT
\n2nd session: 17:00 \u2013 17:45 PDT
\nReward-Free Exploration for Reinforcement Learning<\/strong><\/a>
\nChi Jin, Akshay Krishnamurthy<\/a>, Max Simchowitz, Tiancheng Yu<\/p>\n

07:00 \u2013 07:45 PDT
\n2nd session: 18:00 \u2013 18:45 PDT
\nNo-Regret and Incentive-Compatible Online Learning<\/strong><\/a>
\nRupert Freeman<\/a>, David Pennock, Charikleia Podimata, Jennifer Wortman Vaughan<\/a><\/p>\n

07:00 \u2013 07:45 PDT
\n2nd session: 18:00 \u2013 18:45 PDT
\nGraph Optimal Transport for Cross-Domain Alignment<\/strong><\/a>
\nLiqun Chen, Zhe Gan<\/strong>, Yu Cheng<\/strong>, Linjie Li<\/strong>, Lawrence Carin, Jingjing Liu<\/a><\/p>\n

07:00 \u2013 07:45 PDT
\n2nd session: 20:00 \u2013 20:45 PDT
\nDoubly Robust Off-policy Evaluation with Shrinkage<\/strong><\/a>
\nYi Su, Maria Dimakopoulou, Akshay Krishnamurthy<\/a>, Miroslav Dudik<\/a><\/p>\n

07:00 \u2013 07:45 PDT
\n2nd session: 18:00 \u2013 18:45 PDT
\nVariance Reduction and Quasi-Newton for Particle-Based Variational Inference<\/strong><\/a> Michael Zhu, Chang Liu<\/strong>, Jun Zhu<\/p>\n

07:00 \u2013 07:45 PDT
\n2nd session: 20:00 \u2013 20:45 PDT
\nKinematic State Abstraction and Provably Efficient Rich-Observation Reinforcement Learning<\/strong><\/a>
\nDipendra Misra<\/a>, Mikael Henaff<\/a>, Akshay Krishnamurthy<\/a>, John Langford<\/a><\/p>\n

08:00 \u2013 08:45 PDT
\n2nd session: 19:00 \u2013 19:45 PDT
\nUniLMv2: Pseudo-Masked Language Models for Unified Language Model Pre-Training<\/strong><\/a>
\nHangbo Bao, Li Dong<\/a>, Furu Wei<\/a>, Wenhui Wang<\/strong>, Nan Yang<\/a>, Xiaodong Liu<\/a>, Yu Wang<\/strong>, Jianfeng Gao<\/a>, Songhao Piao, Ming Zhou<\/a>, Hsiao-Wuen Hon<\/a><\/p>\n

09:00 \u2013 09:45 PDT
\n2nd session: 23:00 \u2013 23:45 PDT
\nBounding the fairness and accuracy of classifiers from population statistics<\/strong><\/a>
\nSivan Sabato<\/strong>, Elad Yom-Tov<\/a><\/p>\n

12:00 \u2013 12:45 PDT
\n2nd session: July 17 | 00:00 \u2013 00:45 PDT
\nSoft Threshold Weight Reparameterization for Learnable Sparsity<\/strong><\/a>
\nAditya Kusupati, Vivek Ramanujan, Raghav Somani, Mitchell Wortsman, Prateek Jain<\/a>, Sham Kakade, Ali Farhadi<\/p>\n

12:00 \u2013 12:45 PDT
\n2nd session: July 17 | 01:00 \u2013 01:45 PDT
\nThe k-tied Normal Distribution: A Compact Parameterization of Gaussian Mean Field Posteriors in Bayesian Neural Networks<\/strong><\/a>
\nJakub Swiatkowski, Kevin Roth, Bastiaan S. Veeling, Linh Tran, Joshua V. Dillon, Stephan Mandt, Jasper Snoek, Tim Salimans, Rodolphe Jenatton, Sebastian Nowozin<\/a><\/p>\n

17:00 \u2013 17:45 PDT
\nBINOCULARS for efficient, nonmyopic sequential experimental design<\/strong><\/a>
\nShali Jiang, Henry Chai, Javier Gonzalez<\/a>, Roman Garnett<\/p>\n

17:00 \u2013 17:45 PDT
\nCLUB: A Contrastive Log-ratio Upper Bound of Mutual Information<\/strong><\/a>
\nPengyu Cheng, Weituo Hao, Shuyang Dai, Jiachang Liu, Zhe Gan<\/strong>, Lawrence Carin<\/p>\n

17:00 \u2013 17:45 PDT
\nNeural Datalog Through Time: Informed Temporal Modeling via Logical Specification<\/strong><\/a>
\nHongyuan Mei, Guanghui Qin, Minjie Xu, Jason Eisner<\/strong><\/p>\n

17:00 \u2013 17:45 PDT
\nReward-Free Exploration for Reinforcement Learning<\/strong><\/a>
\nChi Jin, Akshay Krishnamurthy<\/a>, Max Simchowitz, Tiancheng Yu<\/p>\n

18:00 \u2013 18:45 PDT
\nMapping Natural-language Problems to Formal-language Solutions Using Structured Neural Representations<\/strong><\/a>
\nKezhen Chen, Qiuyuan Huang<\/a>, Hamid Palangi<\/a>, Paul Smolensky<\/a>, Ken Forbus, Jianfeng Gao<\/a><\/p>\n

18:00 \u2013 18:45 PDT
\nNo-Regret and Incentive-Compatible Online Learning<\/strong><\/a>
\nRupert Freeman<\/a>, David Pennock, Charikleia Podimata, Jennifer Wortman Vaughan<\/a><\/p>\n

18:00 \u2013 18:45 PDT
\n2nd session: July 17 | 04:00 \u2013 04:45 PDT
\nOn Layer Normalization in the Transformer Architecture<\/strong><\/a>
\nRuibin Xiong, Yunchang Yang, Di He, Kai Zheng, Shuxin Zheng<\/a>, Chen Xing, Huishuai Zhang<\/a>, Yanyan Lan, Liwei Wang, Tie-Yan Liu<\/a><\/p>\n

18:00 \u2013 18:45 PDT
\nBlack-Box Methods for Restoring Monotonicity<\/strong><\/a>
\nEvangelia Gergatsouli, Brendan Lucier<\/a>, Christos Tzamos<\/p>\n

18:00 \u2013 18:45 PDT
\nGraph Optimal Transport for Cross-Domain Alignment<\/strong><\/a>
\nLiqun Chen, Zhe Gan<\/strong>, Yu Cheng<\/strong>, Linjie Li<\/strong>, Lawrence Carin, Jingjing Liu<\/a><\/p>\n

18:00 \u2013 18:45 PDT
\nVariance Reduction and Quasi-Newton for Particle-Based Variational Inference<\/strong><\/a> Michael Zhu, Chang Liu<\/strong>, Jun Zhu<\/p>\n

18:00 \u2013 18:45 PDT
\nSequence Generation with Mixed Representations<\/strong><\/a>
\nLijun Wu<\/strong>, Shufang Xie<\/strong>, Yingce Xia, Yang Fan, Jian-Huang Lai, Tao Qin<\/a>, Tie-Yan Liu<\/a><\/p>\n

19:00 \u2013 19:45 PDT
\nUniLMv2: Pseudo-Masked Language Models for Unified Language Model Pre-Training<\/strong><\/a>
\nHangbo Bao, Li Dong<\/a>, Furu Wei<\/a>, Wenhui Wang<\/strong>, Nan Yang<\/a>, Xiaodong Liu<\/a>, Yu Wang<\/strong>, Jianfeng Gao<\/a>, Songhao Piao, Ming Zhou<\/a>, Hsiao-Wuen Hon<\/a><\/p>\n

19:00 \u2013 19:45 PDT
\nProvably Efficient Model-based Policy Adaptation<\/strong><\/a>
\nYuda Song, Aditi Mavalankar, Wen Sun<\/strong>, Sicun Gao<\/p>\n

20:00 \u2013 20:45 PDT
\nDoubly Robust Off-policy Evaluation with Shrinkage<\/strong><\/a>
\nYi Su, Maria Dimakopoulou, Akshay Krishnamurthy<\/a>, Miroslav Dudik<\/a><\/p>\n

20:00 \u2013 20:45 PDT
\nKinematic State Abstraction and Provably Efficient Rich-Observation Reinforcement Learning<\/strong><\/a>
\nDipendra Misra<\/a>, Mikael Henaff<\/a>, Akshay Krishnamurthy<\/a>, John Langford<\/a><\/p>\n

23:00 \u2013 23:45 PDT
\nBounding the fairness and accuracy of classifiers from population statistics<\/strong><\/a>
\nSivan Sabato<\/strong>, Elad Yom-Tov<\/a><\/p>\n

\n

Friday, July 17<\/h2>\n

00:00 \u2013 00:45 PDT
\nSoft Threshold Weight Reparameterization for Learnable Sparsity<\/strong><\/a>
\nAditya Kusupati, Vivek Ramanujan, Raghav Somani, Mitchell Wortsman, Prateek Jain<\/a>, Sham Kakade, Ali Farhadi<\/p>\n

01:00 \u2013 01:45 PDT
\nThe k-tied Normal Distribution: A Compact Parameterization of Gaussian Mean Field Posteriors in Bayesian Neural Networks<\/strong><\/a>
\nJakub Swiatkowski, Kevin Roth, Bastiaan S. Veeling, Linh Tran, Joshua V. Dillon, Stephan Mandt, Jasper Snoek, Tim Salimans, Rodolphe Jenatton, Sebastian Nowozin<\/a><\/p>\n

04:00 \u2013 04:45 PDT
\nOn Layer Normalization in the Transformer Architecture<\/strong><\/a>
\nRuibin Xiong, Yunchang Yang, Di He, Kai Zheng, Shuxin Zheng<\/a>, Chen Xing, Huishuai Zhang<\/a>, Yanyan Lan, Liwei Wang, Tie-Yan Liu<\/a>Opens in a new tab<\/span><\/p>\n

July 13 \u2013 18<\/h2>\n

Queer in AI<\/strong><\/a>
\nCo-organizer: Andrew McNamara<\/a><\/p>\n

Friday, July 17<\/h2>\n

Beyond first order methods in machine learning systems<\/strong><\/a>
\nInvited Speaker: Lin Xiao<\/a><\/p>\n

Healthcare Systems, Population Health, and the role of health-tech<\/strong><\/a>
\nCo-organizer: Konstantina Palla<\/a><\/p>\n

Self-supervision in Audio and Speech<\/strong><\/a>
\nCo-organizer: R Devon Hjelm<\/a><\/p>\n

Theoretical Foundations of Reinforcement Learning<\/strong><\/a>
\nCo-organizers: Thodoris Lykouris<\/a>
\nInvited Speaker: Akshay Krishnamurthy<\/a><\/p>\n

Workshop on eXtreme Classification: Theory and Applications<\/strong><\/a>
\nCo-organizers: John Langford<\/a>, Yashoteja Prabhu
\nInvited Speaker: Manik Varma<\/a><\/p>\n

Saturday, July 18<\/h2>\n

1st Workshop on Language in Reinforcement Learning (LaReL)<\/strong><\/a>
\nInvited Speaker: Marc-Alexandre C\u00f4t\u00e9<\/a><\/p>\n

Machine Learning for Global Health<\/strong><\/a>
\nCo-organizers: Danielle Belgrave<\/a>, Stephanie Hyland<\/a><\/p>\n

Workshop on Learning in Artificial Open Worlds<\/strong><\/a>
\nCo-organizers: Katja Hofmann<\/a>, Noboru Kuno<\/a>Opens in a new tab<\/span><\/p>\n

Microsoft Booth Schedule at ICML<\/h2>\n

Talk to our experts and learn more about our research and open opportunities.<\/p>\n

Sunday, July 12<\/h3>\n

Live Chat<\/h4>\n\n\n\n\n
11:15 \u2013 12:15 PDT<\/td>\nRicky Loynd, RL<\/td>\n<\/tr>\n
13:45 \u2013 14:45 PDT<\/td>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

Monday, July 13<\/h3>\n

Live Chat<\/h4>\n\n\n\n\n
04:00 \u2013 05:00 PDT<\/td>\nAmit Sharma: Causality, ML explanations<\/td>\n<\/tr>\n
14:00 \u2013 15:00 PDT<\/td>\nAmy Siebenthaler, University\/PhD Recruiting<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

Tuesday, July 14<\/h3>\n

Live Chat<\/h4>\n\n\n\n\n\n\n\n
07:45 \u2013 08:45 PDT<\/td>\nMarc Brockschmidt, GNNs and ML 4 Programming
\nVikas Gosain, University\/PhD Recruiting<\/td>\n<\/tr>\n
10:45 \u2013 11:45 PDT<\/td>\nEdward Tiong, DS\/ML in Microsoft AI Rotation Program
\nVikas Gosain, University\/PhD Recruiting<\/td>\n<\/tr>\n
13:45 \u2013 14:45 PDT<\/td>\nEdward Tiong, DS\/ML in Microsoft AI Rotation Program
\nAkshay Krishnamurthy, RL and learning theory
\nAmy Siebenthaler, University\/PhD Recruiting<\/td>\n<\/tr>\n
17:45 \u2013 18:45 PDT<\/td>\nYang He, DS\/ML in Microsoft AI Rotation Program
\nKevin Hsieh, federated learning and AutoML<\/td>\n<\/tr>\n
20:45 \u2013 21:45 PDT<\/td>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

Wednesday, July 15<\/h3>\n

Live Demos<\/h4>\n\n\n\n\n
04:45 \u2013 05:45 PDT<\/td>\nToolkit for building generalizable and robust ML models
\nAmit Sharma<\/a>, Divyat Mahajan<\/a>, Shruti Tople<\/a><\/td>\n<\/tr>\n
10:45 \u2013 11:45 PDT<\/td>\nLearning calibratable policies using programmatic style-consistency
\nAdith Swaminathan<\/a><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

Live Chat<\/h4>\n\n\n\n\n\n\n\n\n\n
00:45 \u2013 01:45 PDT<\/td>\n<\/td>\n<\/tr>\n
04:45 \u2013 05:45 PDT<\/td>\nElad Yom-Tov, ML and IR for healthcare
\nJavier Gonzalez, Bayesian optimization, probabilistic modeling, causality<\/td>\n<\/tr>\n
07:45 \u2013 08:45 PDT<\/td>\nKevin Yang, computational biology
\nVikas Gosain, University\/PhD Recruiting<\/td>\n<\/tr>\n
10:45 \u2013 11:45 PDT<\/td>\nAdith Swaminathan, RL
\nAmy Siebenthaler, University\/PhD Recruiting<\/td>\n<\/tr>\n
13:45 \u2013 14:45 PDT<\/td>\nSahitya Mantravadi, DS\/ML in Microsoft AI Rotation Program
\nMegha Srivastava, AI Residency Program<\/td>\n<\/tr>\n
17:45 \u2013 18:45 PDT<\/td>\nJason Eisner, MLP & structured prediction<\/td>\n<\/tr>\n
20:45 \u2013 21:45 PDT<\/td>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

Thursday, July 16<\/h3>\n

Live Demos<\/h4>\n\n\n\n
7:45 \u2013 8:45 PDT<\/td>\nToolkit for building generalizable and robust ML models
\nAmit Sharma<\/a>, Divyat Mahajan<\/a>, Shruti Tople<\/a><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

Live Chat<\/h4>\n\n\n\n\n\n\n\n
00:45 \u2013 01:45 PDT<\/td>\nMarc Brockschmidt, GNNs and ML 4 Programming<\/td>\n<\/tr>\n
04:45 \u2013 05:45 PDT<\/td>\nJudy Hanwen Shen, AI Residency Program<\/td>\n<\/tr>\n
07:45 \u2013 08:45 PDT<\/td>\nEdward Tiong, DS\/ML in Microsoft AI Rotation Program
\nAmit Gupte, Program Management in Microsoft AI Rotation Program
\nJason Eisner, NLP & structured prediction
\nVikas Gosain, University\/PhD Recruiting<\/td>\n<\/tr>\n
10:45 \u2013 11:45 PDT<\/td>\nShuo Li, DS\/ML in Microsoft AI Rotation Program
\nYuze Zhang, DS\/ML in Microsoft AI Rotation Program
\nVikas Gosain, University\/PhD Recruiting<\/td>\n<\/tr>\n
13:45 \u2013 14:45 PDT<\/td>\nSahitya Mantravadi, DS\/ML in Microsoft AI Rotation Program<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

Opens in a new tab<\/span><\/p>\n","tab-content":[{"id":0,"name":"About","content":"Microsoft is proud to be a Gold sponsor of the 37th International Conference on Machine Learning<\/a> (ICML), as well as Diamond sponsors at the 1st Women in Machine Learning Un-Workshop<\/a> and Platinum sponsors of the 4th Queer in AI Workshop<\/a>. We have over 50 papers accepted to the conference, and you can find details of our publications on the Accepted papers<\/a> and Workshops<\/a> tabs.\r\n

Committee chairs<\/h2>\r\nICML President: John Langford<\/a>\r\nICML Board Members: Hal Daum\u00e9 III<\/a>, Hanna Wallach<\/a>\r\nProgram Co-chair: Hal Daum\u00e9 III<\/a>\r\n

Invited speaker<\/h2>\r\n

Tuesday, July 14<\/h3>\r\n05:00 \u2013 06:45 PDT & 16:00 \u2013 17:45 PDT\r\nDoing Some Good with Machine Learning<\/strong>\r\nInvited Speaker: Lester Mackey<\/a>"},{"id":1,"name":"Sessions","content":"

Tuesday, July 14<\/h2>\r\n07:00 \u2013 07:45 PDT\r\n2nd session: 20:00 \u2013 20:45 PDT\r\nNGBoost: Natural Gradient Boosting for Probabilistic Prediction<\/strong><\/a>\r\nTony Duan<\/strong>, Anand Avati, Daisy Ding, Khanh K. Thai, Sanjay Basu, Andrew Ng, Alejandro Schuler\r\n\r\n07:00 \u2013 07:45 PDT\r\n2nd session: 18:00 \u2013 18:45 PDT\r\nOnline Learning for Active Cache Synchronization<\/strong><\/a>\r\nAndrey Kolobov<\/a>, Sebastien Bubeck<\/a>, Julian Zimmert\r\n\r\n07:00 \u2013 07:45 PDT\r\n2nd session: 19:00 \u2013 19:45 PDT\r\nRandomized Smoothing of All Shapes and Sizes<\/strong><\/a>\r\nGreg Yang<\/a>, Tony Duan<\/strong>, J. Edward Hu<\/strong>, Hadi Salman<\/strong>, Ilya Razenshteyn<\/a>, Jerry Li<\/a>\r\n\r\n07:00 \u2013 07:45 PDT\r\n2nd session: 20:00 \u2013 20:45 PDT\r\nPrivate Reinforcement Learning with PAC and Regret Guarantees<\/strong><\/a>\r\nGiuseppe Vietri, Borja de Balle Pigem, Akshay Krishnamurthy<\/a>, Steven Wu\r\n\r\n07:00 \u2013 07:45 PDT\r\n2nd session: 18:00 \u2013 18:45 PDT\r\nScalable Nearest Neighbor Search for Optimal Transport<\/strong><\/a>\r\nArturs Backurs, Yihe Dong<\/strong>, Piotr Indyk, Ilya Razenshteyn<\/a>, Tal Wagner\r\n\r\n07:00 \u2013 07:45 PDT\r\n2nd session: 19:00 \u2013 19:45 PDT\r\nCombinatorial Pure Exploration for Dueling Bandit<\/strong><\/a>\r\nWei Chen<\/a>, Yihan Du, Longbo Huang, Haoyu Zhao\r\n\r\n07:00 \u2013 07:45 PDT\r\n2nd session: 19:00 \u2013 19:45 PDT\r\nDistance Metric Learning with Joint Representation Diversification<\/strong><\/a>\r\nXu Chu, Yang Lin, Xiting Wang<\/a>, Xin Gao, Qi Tong, Hailong Yu, Yasha Wang\r\n\r\n07:00 \u2013 07:45 PDT\r\n2nd session: 19:00 \u2013 19:45 PDT\r\nEfficient Domain Generalization via Common-Specific Low-Rank Decomposition<\/strong><\/a>\r\nVihari Piratla<\/strong>, Praneeth Netrapalli<\/a>, Sunita Sarawagi\r\n\r\n07:00 \u2013 07:45 PDT\r\n2nd session: 18:00 \u2013 18:45 PDT\r\nFaster Graph Embeddings via Coarsening<\/strong><\/a>\r\nMatthew Fahrbach, Gramoz Goranci, Sushant Sachdeva, Richard Peng, Chi Wang<\/a>\r\n\r\n07:00 \u2013 07:45 PDT\r\n2nd session: 18:00 \u2013 18:45 PDT\r\nWhat is Local Optimality in Nonconvex-Nonconcave Minimax Optimization?<\/strong><\/a>\r\nChi Jin, Praneeth Netrapalli<\/a>, Michael Jordan\r\n\r\n08:00 \u2013 08:45 PDT\r\n2nd session: 19:00 \u2013 19:45 PDT\r\nAn end-to-end approach for the verification problem: learning the right distance<\/strong><\/a>\r\nJoao Monteiro, Isabela Albuquerque, Jahangir Alam, R Devon Hjelm<\/a>, Tiago Falk\r\n\r\n08:00 \u2013 08:45 PDT\r\n2nd session: 21:00 \u2013 21:45 PDT\r\nWorking Memory Graphs<\/strong><\/a>\r\nRicky Loynd<\/a>, Roland Fernandez<\/a>, Asli Celikyilmaz<\/a>, Adith Swaminathan<\/a>, Matthew Hausknecht<\/a>\r\n\r\n08:00 \u2013 08:45 PDT\r\n2nd session: 19:00 \u2013 19:45 PDT\r\nInformative Dropout for Robust Representation Learning: A Shape-bias Perspective<\/strong><\/a>\r\nBaifeng Shi, Dinghuai Zhang, Qi Dai<\/a>, Jingdong Wang<\/a>, Zhanxing Zhu, Yadong Mu\r\n\r\n08:00 \u2013 08:45 PDT\r\n2nd session: 21:00 \u2013 21:45 PDT\r\nNear-optimal Sample Complexity Bounds for Learning Latent\u00a0k\u2212polytopes and applications to Ad-Mixtures<\/strong><\/a>\r\nChiranjib Bhattacharyya, Ravindran Kannan<\/a>\r\n\r\n08:00 \u2013 08:45 PDT\r\n2nd session: 19:00 \u2013 19:45 PDT\r\nDifferentially Private Set Union<\/strong><\/a>\r\nPankaj Gulhane<\/strong>, Sivakanth Gopi<\/a>, Janardhan Kulkarni<\/a>, Judy Hanwen Shen<\/strong>, Milad Shokouhi<\/a>, Sergey Yekhanin<\/a>\r\n\r\n08:00 \u2013 08:45 PDT\r\n2nd session: 21:00 \u2013 21:45 PDT\r\nDiscount Factor as a Regularizer in Reinforcement Learning<\/strong><\/a>\r\nRon Amit, Kamil Ciosek<\/a>, Ron Meir\r\n\r\n08:00 \u2013 08:45 PDT\r\n2nd session: 21:00 \u2013 21:45 PDT\r\nDROCC: Deep Robust One-Class Classification<\/strong><\/a>\r\nSachin Goyal<\/strong>, Aditi Raghunathan, Moksh Jain, Harsha Vardhan Simhadri<\/a>, Prateek Jain<\/a>\r\n\r\n09:00 \u2013 09:45 PDT\r\n2nd session: 20:00 \u2013 20:45 PDT\r\nFeature Quantization Improves GAN Training<\/strong><\/a>\r\nYang Zhao, Chunyuan Li<\/a>, Ping Yu, Jianfeng Gao<\/a>, Changyou Chen\r\n\r\n09:00 \u2013 09:45 PDT\r\n2nd session: 22:00 \u2013 22:45 PDT\r\nHow Good is the Bayes Posterior in Deep Neural Networks Really<\/strong><\/a>\r\nFlorian Wenzel, Kevin Roth, Bastiaan S. Veeling, Jakub Swiatkowski, Linh Tran, Stephan Mandt, Jasper Snoek, Tim Salimans, Rodolphe Jenatton, Sebastian Nowozin<\/a>\r\n\r\n11:00 \u2013 11:45 PDT\r\n2nd session: 22:00 \u2013 22:45 PDT\r\nOptimization and Analysis of the pAp@k Metric for Recommender Systems<\/strong><\/a>\r\nGaurush Hiranandani, Warut Vijitbenjaronk, Sanmi Koyejo, Prateek Jain<\/a>\r\n\r\n11:00 \u2013 11:45 PDT\r\n2nd session: 22:00 \u2013 22:45 PDT\r\nBandits with Adversarial Scaling<\/strong><\/a>\r\nThodoris Lykouris<\/a>, Vahab Mirrokni, Renato Leme\r\n\r\n12:00 \u2013 12:45 PDT\r\n2nd session: July 15 | 01:00 \u2013 01:45 PDT\r\nTaskNorm: Rethinking Batch Normalization for Meta-Learning<\/strong><\/a>\r\nJohn Bronskill, Jonathan Gordon, James Requeima, Sebastian Nowozin<\/a>, Richard E. Turner\r\n\r\n13:00 \u2013 13:45 PDT\r\n2nd session: July 15 | 01:00 \u2013 01:45 PDT\r\nGNN-FiLM: Graph Neural Networks with Feature-wise Linear Modulation<\/strong><\/a>\r\nMarc Brockschmidt<\/a>\r\n\r\n18:00 \u2013 18:45 PDT\r\nOnline Learning for Active Cache Synchronization<\/strong><\/a>\r\nAndrey Kolobov<\/a>, Sebastien Bubeck<\/a>, Julian Zimmert\r\n\r\n18:00 \u2013 18:45 PDT\r\nScalable Nearest Neighbor Search for Optimal Transport<\/strong><\/a>\r\nArturs Backurs, Yihe Dong<\/strong>, Piotr Indyk, Ilya Razenshteyn<\/a>, Tal Wagner\r\n\r\n18:00 \u2013 18:45 PDT\r\nFaster Graph Embeddings via Coarsening<\/strong><\/a>\r\nMatthew Fahrbach, Gramoz Goranci, Sushant Sachdeva, Richard Peng, Chi Wang<\/a>\r\n\r\n18:00 \u2013 18:45 PDT\r\nWhat is Local Optimality in Nonconvex-Nonconcave Minimax Optimization?<\/strong><\/a>\r\nChi Jin, Praneeth Netrapalli<\/a>, Michael Jordan\r\n\r\n19:00 \u2013 19:45 PDT\r\nRandomized Smoothing of All Shapes and Sizes<\/strong><\/a>\r\nGreg Yang<\/a>, Tony Duan<\/strong>, J. Edward Hu<\/strong>, Hadi Salman<\/strong>, Ilya Razenshteyn<\/a>, Jerry Li<\/a>\r\n\r\n19:00 \u2013 19:45 PDT\r\nAn end-to-end approach for the verification problem: learning the right distance<\/strong><\/a>\r\nJoao Monteiro, Isabela Albuquerque, Jahangir Alam, R Devon Hjelm<\/a>, Tiago Falk\r\n\r\n19:00 \u2013 19:45 PDT\r\nCombinatorial Pure Exploration for Dueling Bandit<\/strong><\/a>\r\nWei Chen<\/a>, Yihan Du, Longbo Huang, Haoyu Zhao\r\n\r\n19:00 \u2013 19:45 PDT\r\nDistance Metric Learning with Joint Representation Diversification<\/strong><\/a>\r\nXu Chu, Yang Lin, Xiting Wang<\/a>, Xin Gao, Qi Tong, Hailong Yu, Yasha Wang\r\n\r\n19:00 \u2013 19:45 PDT\r\nEfficient Domain Generalization via Common-Specific Low-Rank Decomposition<\/strong><\/a>\r\nVihari Piratla<\/strong>, Praneeth Netrapalli<\/a>, Sunita Sarawagi\r\n\r\n19:00 \u2013 19:45 PDT\r\nInformative Dropout for Robust Representation Learning: A Shape-bias Perspective<\/strong><\/a>\r\nBaifeng Shi, Dinghuai Zhang, Qi Dai<\/a>, Jingdong Wang<\/a>, Zhanxing Zhu, Yadong Mu\r\n\r\n19:00 \u2013 19:45 PDT\r\nDifferentially Private Set Union<\/strong><\/a>\r\nPankaj Gulhane<\/strong>, Sivakanth Gopi<\/a>, Janardhan Kulkarni<\/a>, Judy Hanwen Shen<\/strong>, Milad Shokouhi<\/a>, Sergey Yekhanin<\/a>\r\n\r\n20:00 \u2013 20:45 PDT\r\nNGBoost: Natural Gradient Boosting for Probabilistic Prediction<\/strong><\/a>\r\nTony Duan<\/strong>, Anand Avati, Daisy Ding, Khanh K. Thai, Sanjay Basu, Andrew Ng, Alejandro Schuler\r\n\r\n20:00 \u2013 20:45 PDT\r\nPrivate Reinforcement Learning with PAC and Regret Guarantees<\/strong><\/a>\r\nGiuseppe Vietri, Borja de Balle Pigem, Akshay Krishnamurthy<\/a>, Steven Wu\r\n\r\n20:00 \u2013 20:45 PDT\r\nFeature Quantization Improves GAN Training<\/strong><\/a>\r\nYang Zhao, Chunyuan Li<\/a>, Ping Yu, Jianfeng Gao<\/a>, Changyou Chen\r\n\r\n21:00 \u2013 21:45 PDT\r\nWorking Memory Graphs<\/strong><\/a>\r\nRicky Loynd<\/a>, Roland Fernandez<\/a>, Asli Celikyilmaz<\/a>, Adith Swaminathan<\/a>, Matthew Hausknecht<\/a>\r\n\r\n21:00 \u2013 21:45 PDT\r\nNear-optimal Sample Complexity Bounds for Learning Latent\u00a0k\u2212polytopes and applications to Ad-Mixtures<\/strong><\/a>\r\nChiranjib Bhattacharyya, Ravindran Kannan<\/a>\r\n\r\n21:00 \u2013 21:45 PDT\r\nDiscount Factor as a Regularizer in Reinforcement Learning<\/strong><\/a>\r\nRon Amit, Kamil Ciosek<\/a>, Ron Meir\r\n\r\n21:00 \u2013 21:45 PDT\r\nDROCC: Deep Robust One-Class Classification<\/strong><\/a>\r\nSachin Goyal<\/strong>, Aditi Raghunathan, Moksh Jain, Harsha Vardhan Simhadri<\/a>, Prateek Jain<\/a>\r\n\r\n22:00 \u2013 22:45 PDT\r\nOptimization and Analysis of the pAp@k Metric for Recommender Systems<\/strong><\/a>\r\nGaurush Hiranandani, Warut Vijitbenjaronk, Sanmi Koyejo, Prateek Jain<\/a>\r\n\r\n22:00 \u2013 22:45 PDT\r\nBandits with Adversarial Scaling<\/strong><\/a>\r\nThodoris Lykouris<\/a>, Vahab Mirrokni, Renato Leme\r\n\r\n22:00 \u2013 22:45 PDT\r\nHow Good is the Bayes Posterior in Deep Neural Networks Really<\/strong><\/a>\r\nFlorian Wenzel, Kevin Roth, Bastiaan S. Veeling, Jakub Swiatkowski, Linh Tran, Stephan Mandt, Jasper Snoek, Tim Salimans, Rodolphe Jenatton, Sebastian Nowozin<\/a>\r\n\r\n
\r\n\r\n

Wednesday, July 15<\/h2>\r\n01:00 \u2013 01:45 PDT\r\nGNN-FiLM: Graph Neural Networks with Feature-wise Linear Modulation<\/strong><\/a>\r\nMarc Brockschmidt<\/a>\r\n\r\n01:00 \u2013 01:45 PDT\r\nTaskNorm: Rethinking Batch Normalization for Meta-Learning<\/strong><\/a>\r\nJohn Bronskill, Jonathan Gordon, James Requeima, Sebastian Nowozin<\/a>, Richard E. Turner\r\n\r\n05:00 \u2013 05:45 PDT\r\n2nd session: 16:00 \u2013 16:45 PDT\r\nAdaptive Estimator Selection for Off-Policy Evaluation<\/strong><\/a>\r\nYi Su, Pavithra Srinath<\/a>, Akshay Krishnamurthy<\/a>\r\n\r\n05:00 \u2013 05:45 PDT\r\n2nd session: 16:00 \u2013 16:45 PDT\r\nPrivately Learning Markov Random Fields<\/strong><\/a>\r\nGautam Kamath, Janardhan Kulkarni<\/a>, Steven Wu, Huanyu Zhang\r\n\r\n08:00 \u2013 08:45 PDT\r\n2nd session: 21:00 \u2013 21:45 PDT\r\nThe Non-IID Data Quagmire of Decentralized Machine Learning<\/strong><\/a>\r\nKevin Hsieh<\/strong>, Amar Phanishayee<\/a>, Onur Mutlu, Phillip Gibbons\r\n\r\n08:00 \u2013 08:45 PDT\r\n2nd session: 21:00 \u2013 21:45 PDT\r\nAlleviating Privacy Attacks via Causal Learning<\/strong><\/a>\r\nShruti Tople<\/a>, Amit Sharma<\/a>, Aditya Nori<\/a>\r\n\r\n08:00 \u2013 08:45 PDT\r\n2nd session: 21:00 \u2013 21:45 PDT\r\n(Locally) Differentially Private Combinatorial Semi-Bandits<\/strong><\/a>\r\nXiaoyu Chen, Kai Zheng, Zixin Zhou, Yunchang Yang, Wei Chen<\/a>, Liwei Wang\r\n\r\n08:00 \u2013 08:45 PDT\r\n2nd session: 20:00 \u2013 20:45 PDT\r\nThe Usual Suspects? Reassessing Blame for VAE Posterior Collapse<\/strong><\/a>\r\nBin Dai, Ziyu Wang, David Wipf<\/strong>\r\n\r\n10:00 \u2013 10:45 PDT\r\n2nd session: 21:00 \u2013 21:45 PDT\r\nSingle Point Transductive Prediction<\/strong><\/a>\r\nNilesh Tripuraneni, Lester Mackey<\/a>\r\n\r\n10:00 \u2013 10:45 PDT\r\n2nd session: 21:00 \u2013 21:45 PDT\r\nLearning Calibratable Policies using Programmatic Style-Consistency<\/strong><\/a>\r\nEric Zhan, Albert Tseng, Yisong Yue, Adith Swaminathan<\/a>, Matthew Hausknecht<\/a>\r\n\r\n11:00 \u2013 11:45 PDT\r\n2nd session: 22:00 \u2013 22:45 PDT\r\nStatistically Preconditioned Accelerated Gradient Method for Distributed Optimization<\/strong><\/a>\r\nHadrien Hendrikx, Lin Xiao<\/a>, Sebastien Bubeck<\/a>, Francis Bach, Laurent Massouli\u00e9<\/strong>\r\n\r\n12:00 \u2013 12:45 PDT\r\n2nd session: July 16 | 01:00 \u2013 01:45 PDT\r\nNeuro-Symbolic Visual Reasoning: Disentangling \"Visual\" from \"Reasoning\"<\/strong><\/a>\r\nSaeed Amizadeh<\/strong>, Hamid Palangi<\/a>, Oleksandr Polozov<\/a>, Yichen Huang<\/strong>, Kazuhito Koishida<\/a>\r\n\r\n16:00 \u2013 16:45 PDT\r\n2nd session: July 16 | 03:00 \u2013 03:45 PDT\r\nOptimization from Structured Samples for Coverage Functions<\/strong><\/a>\r\nWei Chen<\/a>, Xiaoming Sun, Jialin Zhang, Zhijie Zhang\r\n\r\n16:00 \u2013 16:45 PDT\r\nAdaptive Estimator Selection for Off-Policy Evaluation<\/strong><\/a>\r\nYi Su, Pavithra Srinath<\/a>, Akshay Krishnamurthy<\/a>\r\n\r\n16:00 \u2013 16:45 PDT\r\nPrivately Learning Markov Random Fields<\/strong><\/a>\r\nGautam Kamath, Janardhan Kulkarni<\/a>, Steven Wu, Huanyu Zhang\r\n\r\n20:00 \u2013 20:45 PDT\r\nThe Usual Suspects? Reassessing Blame for VAE Posterior Collapse<\/strong><\/a>\r\nBin Dai, Ziyu Wang, David Wipf<\/strong>\r\n\r\n21:00 \u2013 21:45 PDT\r\nThe Non-IID Data Quagmire of Decentralized Machine Learning<\/strong><\/a>\r\nKevin Hsieh<\/strong>, Amar Phanishayee<\/a>, Onur Mutlu, Phillip Gibbons\r\n\r\n21:00 \u2013 21:45 PDT\r\nSingle Point Transductive Prediction<\/strong><\/a>\r\nNilesh Tripuraneni, Lester Mackey<\/a>\r\n\r\n21:00 \u2013 21:45 PDT\r\nAlleviating Privacy Attacks via Causal Learning<\/strong><\/a>\r\nShruti Tople<\/a>, Amit Sharma<\/a>, Aditya Nori<\/a>\r\n\r\n21:00 \u2013 21:45 PDT\r\n(Locally) Differentially Private Combinatorial Semi-Bandits<\/strong><\/a>\r\nXiaoyu Chen, Kai Zheng, Zixin Zhou, Yunchang Yang, Wei Chen<\/a>, Liwei Wang\r\n\r\n21:00 \u2013 21:45 PDT\r\nLearning Calibratable Policies using Programmatic Style-Consistency<\/strong><\/a>\r\nEric Zhan, Albert Tseng, Yisong Yue, Adith Swaminathan<\/a>, Matthew Hausknecht<\/a>\r\n\r\n22:00 \u2013 22:45 PDT\r\nStatistically Preconditioned Accelerated Gradient Method for Distributed Optimization<\/strong><\/a>\r\nHadrien Hendrikx, Lin Xiao<\/a>, Sebastien Bubeck<\/a>, Francis Bach, Laurent Massouli\u00e9<\/strong>\r\n\r\n
\r\n\r\n

Thursday, July 16<\/h2>\r\n01:00 \u2013 01:45 PDT\r\nNeuro-Symbolic Visual Reasoning: Disentangling \"Visual\" from \"Reasoning\"<\/strong><\/a>\r\nSaeed Amizadeh<\/strong>, Hamid Palangi<\/a>, Oleksandr Polozov<\/a>, Yichen Huang<\/strong>, Kazuhito Koishida<\/a>\r\n\r\n03:00 \u2013 03:45 PDT\r\nOptimization from Structured Samples for Coverage Functions<\/strong><\/a>\r\nWei Chen<\/a>, Xiaoming Sun, Jialin Zhang, Zhijie Zhang\r\n\r\n06:00 \u2013 06:45 PDT\r\n2nd session: July 17 | 18:00 \u2013 18:45 PDT\r\nMapping Natural-language Problems to Formal-language Solutions Using Structured Neural Representations<\/strong><\/a>\r\nKezhen Chen, Qiuyuan Huang<\/a>, Hamid Palangi<\/a>, Paul Smolensky<\/a>, Ken Forbus, Jianfeng Gao<\/a>\r\n\r\n06:00 \u2013 06:45 PDT\r\n2nd session: 17:00 \u2013 17:45 PDT\r\nBINOCULARS for efficient, nonmyopic sequential experimental design<\/strong><\/a>\r\nShali Jiang, Henry Chai, Javier Gonzalez<\/a>, Roman Garnett\r\n\r\n06:00 \u2013 06:45 PDT\r\n2nd session: 18:00 \u2013 18:45 PDT\r\nBlack-Box Methods for Restoring Monotonicity<\/strong><\/a>\r\nEvangelia Gergatsouli, Brendan Lucier<\/a>, Christos Tzamos\r\n\r\n06:00 \u2013 06:45 PDT\r\n2nd session: 17:00 \u2013 17:45 PDT\r\nCLUB: A Contrastive Log-ratio Upper Bound of Mutual Information<\/strong><\/a>\r\nPengyu Cheng, Weituo Hao, Shuyang Dai, Jiachang Liu, Zhe Gan<\/strong>, Lawrence Carin\r\n\r\n06:00 \u2013 06:45 PDT\r\n2nd session: 17:00 \u2013 17:45 PDT\r\nNeural Datalog Through Time: Informed Temporal Modeling via Logical Specification<\/strong><\/a>\r\nHongyuan Mei, Guanghui Qin, Minjie Xu, Jason Eisner<\/strong>\r\n\r\n06:00 \u2013 06:45 PDT\r\n2nd session: 19:00 \u2013 19:45 PDT\r\nProvably Efficient Model-based Policy Adaptation<\/strong><\/a>\r\nYuda Song, Aditi Mavalankar, Wen Sun<\/strong>, Sicun Gao\r\n\r\n06:00 \u2013 06:45 PDT\r\n2nd session: 18:00 \u2013 18:45 PDT\r\nSequence Generation with Mixed Representations<\/strong><\/a>\r\nLijun Wu<\/strong>, Shufang Xie<\/strong>, Yingce Xia, Yang Fan, Jian-Huang Lai, Tao Qin<\/a>, Tie-Yan Liu<\/a>\r\n\r\n06:00 \u2013 06:45 PDT\r\n2nd session: 17:00 \u2013 17:45 PDT\r\nReward-Free Exploration for Reinforcement Learning<\/strong><\/a>\r\nChi Jin, Akshay Krishnamurthy<\/a>, Max Simchowitz, Tiancheng Yu\r\n\r\n07:00 \u2013 07:45 PDT\r\n2nd session: 18:00 \u2013 18:45 PDT\r\nNo-Regret and Incentive-Compatible Online Learning<\/strong><\/a>\r\nRupert Freeman<\/a>, David Pennock, Charikleia Podimata, Jennifer Wortman Vaughan<\/a>\r\n\r\n07:00 \u2013 07:45 PDT\r\n2nd session: 18:00 \u2013 18:45 PDT\r\nGraph Optimal Transport for Cross-Domain Alignment<\/strong><\/a>\r\nLiqun Chen, Zhe Gan<\/strong>, Yu Cheng<\/strong>, Linjie Li<\/strong>, Lawrence Carin, Jingjing Liu<\/a>\r\n\r\n07:00 \u2013 07:45 PDT\r\n2nd session: 20:00 \u2013 20:45 PDT\r\nDoubly Robust Off-policy Evaluation with Shrinkage<\/strong><\/a>\r\nYi Su, Maria Dimakopoulou, Akshay Krishnamurthy<\/a>, Miroslav Dudik<\/a>\r\n\r\n07:00 \u2013 07:45 PDT\r\n2nd session: 18:00 \u2013 18:45 PDT\r\nVariance Reduction and Quasi-Newton for Particle-Based Variational Inference<\/strong><\/a> Michael Zhu, Chang Liu<\/strong>, Jun Zhu\r\n\r\n07:00 \u2013 07:45 PDT\r\n2nd session: 20:00 \u2013 20:45 PDT\r\nKinematic State Abstraction and Provably Efficient Rich-Observation Reinforcement Learning<\/strong><\/a>\r\nDipendra Misra<\/a>, Mikael Henaff<\/a>, Akshay Krishnamurthy<\/a>, John Langford<\/a>\r\n\r\n08:00 \u2013 08:45 PDT\r\n2nd session: 19:00 \u2013 19:45 PDT\r\nUniLMv2: Pseudo-Masked Language Models for Unified Language Model Pre-Training<\/strong><\/a>\r\nHangbo Bao, Li Dong<\/a>, Furu Wei<\/a>, Wenhui Wang<\/strong>, Nan Yang<\/a>, Xiaodong Liu<\/a>, Yu Wang<\/strong>, Jianfeng Gao<\/a>, Songhao Piao, Ming Zhou<\/a>, Hsiao-Wuen Hon<\/a>\r\n\r\n09:00 \u2013 09:45 PDT\r\n2nd session: 23:00 \u2013 23:45 PDT\r\nBounding the fairness and accuracy of classifiers from population statistics<\/strong><\/a>\r\nSivan Sabato<\/strong>, Elad Yom-Tov<\/a>\r\n\r\n12:00 \u2013 12:45 PDT\r\n2nd session: July 17 | 00:00 \u2013 00:45 PDT\r\nSoft Threshold Weight Reparameterization for Learnable Sparsity<\/strong><\/a>\r\nAditya Kusupati, Vivek Ramanujan, Raghav Somani, Mitchell Wortsman, Prateek Jain<\/a>, Sham Kakade, Ali Farhadi\r\n\r\n12:00 \u2013 12:45 PDT\r\n2nd session: July 17 | 01:00 \u2013 01:45 PDT\r\nThe k-tied Normal Distribution: A Compact Parameterization of Gaussian Mean Field Posteriors in Bayesian Neural Networks<\/strong><\/a>\r\nJakub Swiatkowski, Kevin Roth, Bastiaan S. Veeling, Linh Tran, Joshua V. Dillon, Stephan Mandt, Jasper Snoek, Tim Salimans, Rodolphe Jenatton, Sebastian Nowozin<\/a>\r\n\r\n17:00 \u2013 17:45 PDT\r\nBINOCULARS for efficient, nonmyopic sequential experimental design<\/strong><\/a>\r\nShali Jiang, Henry Chai, Javier Gonzalez<\/a>, Roman Garnett\r\n\r\n17:00 \u2013 17:45 PDT\r\nCLUB: A Contrastive Log-ratio Upper Bound of Mutual Information<\/strong><\/a>\r\nPengyu Cheng, Weituo Hao, Shuyang Dai, Jiachang Liu, Zhe Gan<\/strong>, Lawrence Carin\r\n\r\n17:00 \u2013 17:45 PDT\r\nNeural Datalog Through Time: Informed Temporal Modeling via Logical Specification<\/strong><\/a>\r\nHongyuan Mei, Guanghui Qin, Minjie Xu, Jason Eisner<\/strong>\r\n\r\n17:00 \u2013 17:45 PDT\r\nReward-Free Exploration for Reinforcement Learning<\/strong><\/a>\r\nChi Jin, Akshay Krishnamurthy<\/a>, Max Simchowitz, Tiancheng Yu\r\n\r\n18:00 \u2013 18:45 PDT\r\nMapping Natural-language Problems to Formal-language Solutions Using Structured Neural Representations<\/strong><\/a>\r\nKezhen Chen, Qiuyuan Huang<\/a>, Hamid Palangi<\/a>, Paul Smolensky<\/a>, Ken Forbus, Jianfeng Gao<\/a>\r\n\r\n18:00 \u2013 18:45 PDT\r\nNo-Regret and Incentive-Compatible Online Learning<\/strong><\/a>\r\nRupert Freeman<\/a>, David Pennock, Charikleia Podimata, Jennifer Wortman Vaughan<\/a>\r\n\r\n18:00 \u2013 18:45 PDT\r\n2nd session: July 17 | 04:00 \u2013 04:45 PDT\r\nOn Layer Normalization in the Transformer Architecture<\/strong><\/a>\r\nRuibin Xiong, Yunchang Yang, Di He, Kai Zheng, Shuxin Zheng<\/a>, Chen Xing, Huishuai Zhang<\/a>, Yanyan Lan, Liwei Wang, Tie-Yan Liu<\/a>\r\n\r\n18:00 \u2013 18:45 PDT\r\nBlack-Box Methods for Restoring Monotonicity<\/strong><\/a>\r\nEvangelia Gergatsouli, Brendan Lucier<\/a>, Christos Tzamos\r\n\r\n18:00 \u2013 18:45 PDT\r\nGraph Optimal Transport for Cross-Domain Alignment<\/strong><\/a>\r\nLiqun Chen, Zhe Gan<\/strong>, Yu Cheng<\/strong>, Linjie Li<\/strong>, Lawrence Carin, Jingjing Liu<\/a>\r\n\r\n18:00 \u2013 18:45 PDT\r\nVariance Reduction and Quasi-Newton for Particle-Based Variational Inference<\/strong><\/a> Michael Zhu, Chang Liu<\/strong>, Jun Zhu\r\n\r\n18:00 \u2013 18:45 PDT\r\nSequence Generation with Mixed Representations<\/strong><\/a>\r\nLijun Wu<\/strong>, Shufang Xie<\/strong>, Yingce Xia, Yang Fan, Jian-Huang Lai, Tao Qin<\/a>, Tie-Yan Liu<\/a>\r\n\r\n19:00 \u2013 19:45 PDT\r\nUniLMv2: Pseudo-Masked Language Models for Unified Language Model Pre-Training<\/strong><\/a>\r\nHangbo Bao, Li Dong<\/a>, Furu Wei<\/a>, Wenhui Wang<\/strong>, Nan Yang<\/a>, Xiaodong Liu<\/a>, Yu Wang<\/strong>, Jianfeng Gao<\/a>, Songhao Piao, Ming Zhou<\/a>, Hsiao-Wuen Hon<\/a>\r\n\r\n19:00 \u2013 19:45 PDT\r\nProvably Efficient Model-based Policy Adaptation<\/strong><\/a>\r\nYuda Song, Aditi Mavalankar, Wen Sun<\/strong>, Sicun Gao\r\n\r\n20:00 \u2013 20:45 PDT\r\nDoubly Robust Off-policy Evaluation with Shrinkage<\/strong><\/a>\r\nYi Su, Maria Dimakopoulou, Akshay Krishnamurthy<\/a>, Miroslav Dudik<\/a>\r\n\r\n20:00 \u2013 20:45 PDT\r\nKinematic State Abstraction and Provably Efficient Rich-Observation Reinforcement Learning<\/strong><\/a>\r\nDipendra Misra<\/a>, Mikael Henaff<\/a>, Akshay Krishnamurthy<\/a>, John Langford<\/a>\r\n\r\n23:00 \u2013 23:45 PDT\r\nBounding the fairness and accuracy of classifiers from population statistics<\/strong><\/a>\r\nSivan Sabato<\/strong>, Elad Yom-Tov<\/a>\r\n\r\n
\r\n\r\n

Friday, July 17<\/h2>\r\n00:00 \u2013 00:45 PDT\r\nSoft Threshold Weight Reparameterization for Learnable Sparsity<\/strong><\/a>\r\nAditya Kusupati, Vivek Ramanujan, Raghav Somani, Mitchell Wortsman, Prateek Jain<\/a>, Sham Kakade, Ali Farhadi\r\n\r\n01:00 \u2013 01:45 PDT\r\nThe k-tied Normal Distribution: A Compact Parameterization of Gaussian Mean Field Posteriors in Bayesian Neural Networks<\/strong><\/a>\r\nJakub Swiatkowski, Kevin Roth, Bastiaan S. Veeling, Linh Tran, Joshua V. Dillon, Stephan Mandt, Jasper Snoek, Tim Salimans, Rodolphe Jenatton, Sebastian Nowozin<\/a>\r\n\r\n04:00 \u2013 04:45 PDT\r\nOn Layer Normalization in the Transformer Architecture<\/strong><\/a>\r\nRuibin Xiong, Yunchang Yang, Di He, Kai Zheng, Shuxin Zheng<\/a>, Chen Xing, Huishuai Zhang<\/a>, Yanyan Lan, Liwei Wang, Tie-Yan Liu<\/a>"},{"id":2,"name":"Workshops","content":"

July 13 \u2013 18<\/h2>\r\nQueer in AI<\/strong><\/a>\r\nCo-organizer: Andrew McNamara<\/a>\r\n

Friday, July 17<\/h2>\r\nBeyond first order methods in machine learning systems<\/strong><\/a>\r\nInvited Speaker: Lin Xiao<\/a>\r\n\r\nHealthcare Systems, Population Health, and the role of health-tech<\/strong><\/a>\r\nCo-organizer: Konstantina Palla<\/a>\r\n\r\nSelf-supervision in Audio and Speech<\/strong><\/a>\r\nCo-organizer: R Devon Hjelm<\/a>\r\n\r\nTheoretical Foundations of Reinforcement Learning<\/strong><\/a>\r\nCo-organizers: Thodoris Lykouris<\/a>\r\nInvited Speaker: Akshay Krishnamurthy<\/a>\r\n\r\nWorkshop on eXtreme Classification: Theory and Applications<\/strong><\/a>\r\nCo-organizers: John Langford<\/a>, Yashoteja Prabhu\r\nInvited Speaker: Manik Varma<\/a>\r\n

Saturday, July 18<\/h2>\r\n1st Workshop on Language in Reinforcement Learning (LaReL)<\/strong><\/a>\r\nInvited Speaker: Marc-Alexandre C\u00f4t\u00e9<\/a>\r\n\r\nMachine Learning for Global Health<\/strong><\/a>\r\nCo-organizers: Danielle Belgrave<\/a>, Stephanie Hyland<\/a>\r\n\r\nWorkshop on Learning in Artificial Open Worlds<\/strong><\/a>\r\nCo-organizers: Katja Hofmann<\/a>, Noboru Kuno<\/a>"},{"id":3,"name":"Booth schedule","content":"

Microsoft Booth Schedule at ICML<\/h2>\r\nTalk to our experts and learn more about our research and open opportunities.\r\n

Sunday, July 12<\/h3>\r\n

Live Chat<\/h4>\r\n\r\n\r\n\r\n\r\n
11:15 \u2013 12:15 PDT<\/td>\r\nRicky Loynd, RL<\/td>\r\n<\/tr>\r\n
13:45 \u2013 14:45 PDT<\/td>\r\n<\/td>\r\n<\/tr>\r\n<\/tbody>\r\n<\/table>\r\n

Monday, July 13<\/h3>\r\n

Live Chat<\/h4>\r\n\r\n\r\n\r\n\r\n
04:00 \u2013 05:00 PDT<\/td>\r\nAmit Sharma: Causality, ML explanations<\/td>\r\n<\/tr>\r\n
14:00 \u2013 15:00 PDT<\/td>\r\nAmy Siebenthaler, University\/PhD Recruiting<\/td>\r\n<\/tr>\r\n<\/tbody>\r\n<\/table>\r\n

Tuesday, July 14<\/h3>\r\n

Live Chat<\/h4>\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n
07:45 \u2013 08:45 PDT<\/td>\r\nMarc Brockschmidt, GNNs and ML 4 Programming\r\nVikas Gosain, University\/PhD Recruiting<\/td>\r\n<\/tr>\r\n
10:45 \u2013 11:45 PDT<\/td>\r\nEdward Tiong, DS\/ML in Microsoft AI Rotation Program\r\nVikas Gosain, University\/PhD Recruiting<\/td>\r\n<\/tr>\r\n
13:45 \u2013 14:45 PDT<\/td>\r\nEdward Tiong, DS\/ML in Microsoft AI Rotation Program\r\nAkshay Krishnamurthy, RL and learning theory\r\nAmy Siebenthaler, University\/PhD Recruiting<\/td>\r\n<\/tr>\r\n
17:45 \u2013 18:45 PDT<\/td>\r\nYang He, DS\/ML in Microsoft AI Rotation Program\r\nKevin Hsieh, federated learning and AutoML<\/td>\r\n<\/tr>\r\n
20:45 \u2013 21:45 PDT<\/td>\r\n<\/td>\r\n<\/tr>\r\n<\/tbody>\r\n<\/table>\r\n

Wednesday, July 15<\/h3>\r\n

Live Demos<\/h4>\r\n\r\n\r\n\r\n\r\n
04:45 \u2013 05:45 PDT<\/td>\r\nToolkit for building generalizable and robust ML models\r\nAmit Sharma<\/a>, Divyat Mahajan<\/a>, Shruti Tople<\/a><\/td>\r\n<\/tr>\r\n
10:45 \u2013 11:45 PDT<\/td>\r\nLearning calibratable policies using programmatic style-consistency\r\nAdith Swaminathan<\/a><\/td>\r\n<\/tr>\r\n<\/tbody>\r\n<\/table>\r\n

Live Chat<\/h4>\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n
00:45 \u2013 01:45 PDT<\/td>\r\n<\/td>\r\n<\/tr>\r\n
04:45 \u2013 05:45 PDT<\/td>\r\nElad Yom-Tov, ML and IR for healthcare\r\nJavier Gonzalez, Bayesian optimization, probabilistic modeling, causality<\/td>\r\n<\/tr>\r\n
07:45 \u2013 08:45 PDT<\/td>\r\nKevin Yang, computational biology\r\nVikas Gosain, University\/PhD Recruiting<\/td>\r\n<\/tr>\r\n
10:45 \u2013 11:45 PDT<\/td>\r\nAdith Swaminathan, RL\r\nAmy Siebenthaler, University\/PhD Recruiting<\/td>\r\n<\/tr>\r\n
13:45 \u2013 14:45 PDT<\/td>\r\nSahitya Mantravadi, DS\/ML in Microsoft AI Rotation Program\r\nMegha Srivastava, AI Residency Program<\/td>\r\n<\/tr>\r\n
17:45 \u2013 18:45 PDT<\/td>\r\nJason Eisner, MLP & structured prediction<\/td>\r\n<\/tr>\r\n
20:45 \u2013 21:45 PDT<\/td>\r\n<\/td>\r\n<\/tr>\r\n<\/tbody>\r\n<\/table>\r\n

Thursday, July 16<\/h3>\r\n

Live Demos<\/h4>\r\n\r\n\r\n\r\n
7:45 \u2013 8:45 PDT<\/td>\r\nToolkit for building generalizable and robust ML models\r\nAmit Sharma<\/a>, Divyat Mahajan<\/a>, Shruti Tople<\/a><\/td>\r\n<\/tr>\r\n<\/tbody>\r\n<\/table>\r\n

Live Chat<\/h4>\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n
00:45 \u2013 01:45 PDT<\/td>\r\nMarc Brockschmidt, GNNs and ML 4 Programming<\/td>\r\n<\/tr>\r\n
04:45 \u2013 05:45 PDT<\/td>\r\nJudy Hanwen Shen, AI Residency Program<\/td>\r\n<\/tr>\r\n
07:45 \u2013 08:45 PDT<\/td>\r\nEdward Tiong, DS\/ML in Microsoft AI Rotation Program\r\nAmit Gupte, Program Management in Microsoft AI Rotation Program\r\nJason Eisner, NLP & structured prediction\r\nVikas Gosain, University\/PhD Recruiting<\/td>\r\n<\/tr>\r\n
10:45 \u2013 11:45 PDT<\/td>\r\nShuo Li, DS\/ML in Microsoft AI Rotation Program\r\nYuze Zhang, DS\/ML in Microsoft AI Rotation Program\r\nVikas Gosain, University\/PhD Recruiting<\/td>\r\n<\/tr>\r\n
13:45 \u2013 14:45 PDT<\/td>\r\nSahitya Mantravadi, DS\/ML in Microsoft AI Rotation Program<\/td>\r\n<\/tr>\r\n<\/tbody>\r\n<\/table>"}],"msr_startdate":"2020-07-12","msr_enddate":"2020-07-18","msr_event_time":"","msr_location":"Virtual\/Online","msr_event_link":"","msr_event_recording_link":"","msr_startdate_formatted":"July 12, 2020","msr_register_text":"Watch now","msr_cta_link":"","msr_cta_text":"","msr_cta_bi_name":"","featured_image_thumbnail":"\"Microsoft","event_excerpt":"Microsoft is proud to be a Gold sponsor of the 37th International Conference on Machine Learning (ICML), as well as Diamond sponsors at the 1st Women in Machine Learning Un-Workshop and Platinum sponsors of the 4th Queer in AI Workshop. We have over 50 papers accepted to the conference, and you can find details of our publications on the Accepted papers and Workshops tabs. Committee chairs ICML President: John Langford ICML Board Members: Hal Daum\u00e9…","msr_research_lab":[],"related-researchers":[],"msr_impact_theme":[],"related-academic-programs":[],"related-groups":[],"related-projects":[],"related-opportunities":[],"related-publications":[655842,663714,663825,672759,677127,684390,685089,685095],"related-videos":[],"related-posts":[680043],"_links":{"self":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-event\/670011","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-event"}],"about":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/types\/msr-event"}],"version-history":[{"count":3,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-event\/670011\/revisions"}],"predecessor-version":[{"id":1146953,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-event\/670011\/revisions\/1146953"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/media\/392255"}],"wp:attachment":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/media?parent=670011"}],"wp:term":[{"taxonomy":"msr-research-area","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/research-area?post=670011"},{"taxonomy":"msr-region","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-region?post=670011"},{"taxonomy":"msr-event-type","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-event-type?post=670011"},{"taxonomy":"msr-video-type","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-video-type?post=670011"},{"taxonomy":"msr-locale","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-locale?post=670011"},{"taxonomy":"msr-program-audience","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-program-audience?post=670011"},{"taxonomy":"msr-post-option","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-post-option?post=670011"},{"taxonomy":"msr-impact-theme","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-impact-theme?post=670011"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}