{"id":708199,"date":"2020-11-25T13:56:40","date_gmt":"2020-11-25T21:56:40","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/?post_type=msr-event&p=708199"},"modified":"2021-03-08T06:40:40","modified_gmt":"2021-03-08T14:40:40","slug":"neurips-2020","status":"publish","type":"msr-event","link":"https:\/\/www.microsoft.com\/en-us\/research\/event\/neurips-2020\/","title":{"rendered":"Microsoft at NeurIPS 2020"},"content":{"rendered":"

Website:<\/strong> NeurIPS 2020 (opens in new tab)<\/span><\/a><\/p>\n","protected":false},"excerpt":{"rendered":"

Microsoft is delighted to sponsor and attend NeurIPS 2020, the largest machine learning conference of the year. Microsoft will showcase state-of-the-art research with over 100 co-authored papers, as well as participation in a variety of workshops, tutorials and competitions. If you are attending NeurIPS 2020, we encourage you to stop by our virtual booth to chat with our experts, see demos of our latest research, and find out about career opportunities with Microsoft. In addition to our participation in the main conference, Microsoft is also proud to sponsor and participate in the Black in AI, Queer in AI, and Women in Machine Learning Workshops.<\/p>\n","protected":false},"featured_media":706486,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"msr_startdate":"2020-12-06","msr_enddate":"2020-12-12","msr_location":"Virtual","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,"footnotes":""},"research-area":[13556],"msr-region":[256048],"msr-event-type":[197941],"msr-video-type":[],"msr-locale":[268875],"msr-program-audience":[],"msr-post-option":[],"msr-impact-theme":[],"class_list":["post-708199","msr-event","type-msr-event","status-publish","has-post-thumbnail","hentry","msr-research-area-artificial-intelligence","msr-region-global","msr-event-type-conferences","msr-locale-en_us"],"msr_about":"Website:<\/strong> NeurIPS 2020<\/a>","tab-content":[{"id":0,"name":"About","content":"Microsoft is delighted to sponsor and attend the 34th Annual Conference on Neural Information Processing System (NeurIPS 2020)<\/a>, the largest machine learning conference of the year. As a proud Platinum Sponsor of NeurIPS 2020, Microsoft will showcase state-of-the-art research with over 100 co-authored papers, as well as participation in a variety of workshops, tutorials and competitions. If you are attending NeurIPS 2020, we encourage you to stop by our virtual booth to chat with our experts, see demos of our latest research, and find out about career opportunities with Microsoft. In addition to our participation in the main conference, Microsoft is also proud to sponsor and participate in the Black in AI<\/a>, Queer in AI<\/a>, and Women in Machine Learning<\/a> Workshops.\r\n

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NeurIPS 2020 Invited talk<\/h3>\r\n

Watch Chris Bishop<\/a>'s Posner Lecture<\/span>\r\nThe Real AI Revolution<\/strong><\/a><\/p>\r\n<\/blockquote>\r\n<\/div>\r\n

<\/div>\r\n

Virtual Fireside Chat with Professor Yoshua Bengio & Dr. Chris Bishop<\/h3>\r\nhttps:\/\/youtu.be\/954inChlPxE\r\n
<\/div>\r\n

Organizing Committee members<\/h3>\r\nDanielle Belgrave<\/a>, Tutorial Co-Chair\r\nKatja Hofmann<\/a>, Demonstration and Competitions Co-Chair\r\nYale Song<\/a>, Expo Co-Chair\r\nLester Mackey<\/a>, Diversity and Inclusion Co-Chair\r\n

NeurIPS Foundation Board 2020<\/h3>\r\nHanna Wallach<\/a>, Board Member"},{"id":1,"name":"Booth schedule","content":"

Live chat with us<\/h2>\r\nJoin us in the Microsoft booth to chat with experts about our research and open opportunities with Microsoft. See below for our live chat and live demo schedules.\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n
Sunday, December 6<\/strong><\/td>\r\n<\/tr>\r\n
Time (PT)<\/strong><\/td>\r\nName, Title<\/strong><\/td>\r\n<\/tr>\r\n
19:00\u201320:00<\/td>\r\nVishak Gopal<\/a>, Principal Software Engineer<\/td>\r\n<\/tr>\r\n
Monday, December 7<\/strong><\/td>\r\n<\/tr>\r\n
Time (PT)<\/strong><\/td>\r\nName, Title<\/strong><\/td>\r\n<\/tr>\r\n
13:00\u201314:00<\/td>\r\nEdward Tiong, Data & Applied Scientist<\/td>\r\n<\/tr>\r\n
14:00\u201315:00<\/td>\r\nAkshay Krishnamurthy<\/a>, Researcher\r\nVikas Gosain, HR Team\/Recruiter<\/td>\r\n<\/tr>\r\n
15:00\u201316:00<\/td>\r\nAlekh Agarwal<\/a>, Researcher\r\nVikas Gosain, HR Team\/Recruiter<\/td>\r\n<\/tr>\r\n
16:00\u201317:00<\/td>\r\nJason Eisner, Researcher<\/td>\r\n<\/tr>\r\n
Tuesday, December 8<\/strong><\/td>\r\n<\/tr>\r\n
Time (PT)<\/strong><\/td>\r\nName, Title<\/strong><\/td>\r\n<\/tr>\r\n
04:00\u201305:00<\/td>\r\nCammy Vasquez, HR Team<\/td>\r\n<\/tr>\r\n
05:00\u201306:00<\/td>\r\nHannes Schulz<\/a>, Senior Researcher<\/td>\r\n<\/tr>\r\n
11:00\u201312:00<\/td>\r\nAkshay Krishnamurthy<\/a>, Researcher\r\nSubho Mukherjee<\/a>, Senior Scientist\r\nVikas Gosain, HR Team\/Recruiter<\/td>\r\n<\/tr>\r\n
12:00\u201313:00<\/td>\r\nArushi Jain, Data & Applied Scientist\r\nKevin Yang<\/a>, Researcher\r\nPaul Mineiro<\/a>, Research & Engineering<\/td>\r\n<\/tr>\r\n
13:00\u201314:00<\/td>\r\nAmy Siebenthaler, HR Team\/Recruiter\r\nAndrea Trevino Gavito, Data & Applied Scientist\r\nPraveen Palanisamy<\/a>, Research & Engineering<\/td>\r\n<\/tr>\r\n
14:00\u201315:00<\/td>\r\nAmy Siebenthaler, HR Team\/Recruiter\r\nJenna Hong, Data & Applied Scientist<\/td>\r\n<\/tr>\r\n
15:00\u201316:00<\/td>\r\nTristan Naumann<\/a>, Researcher\r\nVikas Gosain, HR Team\/Recruiter<\/td>\r\n<\/tr>\r\n
16:00\u201317:00<\/td>\r\nAhmed Awadallah<\/a>, Principal Research Manager\r\nChi Wang<\/a>, Researcher\r\nJason Eisner, Researcher<\/td>\r\n<\/tr>\r\n
Wednesday, December 9<\/strong><\/td>\r\n<\/tr>\r\n
Time (PT)<\/strong><\/td>\r\nName, Title<\/strong><\/td>\r\n<\/tr>\r\n
04:00\u201305:00<\/td>\r\nHannes Schulz<\/a>, Senior Researcher\r\nHarm van Seijen<\/a>, Researcher<\/td>\r\n<\/tr>\r\n
11:00\u201312:00<\/td>\r\nAmy Siebenthaler, HR Team\/Recruiter\r\nAndrea Trevino Gavito, Data & Applied Scientist\r\nJames Budnik, HR Team\/Recruiter\r\nJenna Hong, Data & Applied Scientist<\/td>\r\n<\/tr>\r\n
12:00\u201313:00<\/td>\r\nPaul Mineiro<\/a>, Research & Engineering\r\nDipendra Misra, Researcher<\/td>\r\n<\/tr>\r\n
13:00\u201314:00<\/td>\r\nAmy Siebenthaler, HR Team\/Recruiter\r\nVishak Gopal<\/a>, Principal Software Engineer<\/td>\r\n<\/tr>\r\n
14:00\u201315:00<\/td>\r\nArushi Jain, Data & Applied Scientist\r\nEmre K\u0131c\u0131man<\/a>, Researcher\r\nOssie Roycroft, HR Team\/Recruiter<\/td>\r\n<\/tr>\r\n
15:00\u201316:00<\/td>\r\nHari Dubey, Scientist\/Engineer\r\nVikas Gosain, HR Team\/Recruiter<\/td>\r\n<\/tr>\r\n
16:00\u201317:00<\/td>\r\nAlekh Agarwal<\/a>, Researcher\r\nVikas Gosain, HR Team\/Recruiter<\/td>\r\n<\/tr>\r\n
Thursday, December 10<\/strong><\/td>\r\n<\/tr>\r\n
Time (PT)<\/strong><\/td>\r\nName, Title<\/strong><\/td>\r\n<\/tr>\r\n
04:00\u201305:00<\/td>\r\nCammy Vasquez, HR Team\r\nHannes Schulz<\/a>, Senior Researcher<\/td>\r\n<\/tr>\r\n
05:00\u201306:00<\/td>\r\nHarm van Seijen<\/a>, Researcher\r\nJenna Hong, Data & Applied Scientist<\/td>\r\n<\/tr>\r\n
06:00\u201307:00<\/td>\r\nCassandra Oduola, Responsible AI<\/td>\r\n<\/tr>\r\n
09:00\u201310:00<\/td>\r\nWomen at Microsoft\r\nAndrea Trevino Gavito<\/a>, Microsoft AI Development\r\nAnusua Trivedi<\/a>, AI for Good\r\nArushi Jain<\/a>, Microsoft AI Development\r\nBesmira Nushi<\/a>, Responsible AI, Human AI-Collaboration\r\nCassandra Oduola, Responsible AI\r\nEvelyne Viegas<\/a>, Research Engagement Outreach Programs (e.g., collaborative projects, fellowships)\r\nFanny Nina Paravecino<\/a>, CAST (Cloud AI System Technology in Azure)\r\nHanna Wallach<\/a>, FATE (fairness, accountability, transparency, and ethics in AI)\r\nJenn Wortman Vaughan<\/a>, FATE (fairness, accountability, transparency, and ethics in AI)\r\nJenna Hong<\/a>, Microsoft AI Development\r\nKatja Hofmann<\/a>, Game Intelligence\r\nLingling Zheng<\/a>, AI Ops\/Cloud Intelligence\r\nSarah Bird<\/a>, Responsible AI Lead, Azure Cognitive Services\r\nShruthi Bannur<\/a>, Health Intelligence<\/td>\r\n<\/tr>\r\n
11:00\u201312:00<\/td>\r\nAmy Siebenthaler, HR Team\/Recruiter\r\nAndrea Trevino Gavito, Data & Applied Scientist\r\nJenna Hong, Data & Applied Scientist<\/td>\r\n<\/tr>\r\n
12:00\u201313:00<\/td>\r\nPaul Mineiro<\/a>, Research & Engineering\r\nRemi Tachet<\/a>, Senior Researcher<\/td>\r\n<\/tr>\r\n
13:00\u201314:00<\/td>\r\nAmy Siebenthaler, HR Team\/Recruiter\r\nDipendra Misra, Researcher\r\nJenna Hong, Data & Applied Scientist<\/td>\r\n<\/tr>\r\n
14:00\u201315:00<\/td>\r\nArushi Jain, Data & Applied Scientist\r\nOssie Roycroft, HR Team\/Recruiter<\/td>\r\n<\/tr>\r\n
15:00\u201316:00<\/td>\r\nUrszula Chajewska, Data & Applied Scientist\r\nVikas Gosain, HR Team\/Recruiter<\/td>\r\n<\/tr>\r\n
16:00\u201317:00<\/td>\r\nJason Eisner, Researcher\r\nVikas Gosain, HR Team\/Recruiter<\/td>\r\n<\/tr>\r\n<\/tbody>\r\n<\/table>\r\n
<\/div>\r\n

Live Demo schedule<\/h2>\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n
Tuesday, December 8<\/strong><\/td>\r\n<\/tr>\r\n
Time (PT)<\/strong><\/td>\r\nLive Demo<\/strong><\/td>\r\n<\/tr>\r\n
11:00\u201312:00<\/td>\r\nMineRL, Sean Kuno<\/a><\/td>\r\n<\/tr>\r\n
13:00\u201313:30<\/td>\r\nRecruiting Q&A, Amy Sibenthaler<\/td>\r\n<\/tr>\r\n
15:00\u201316:00<\/td>\r\nMineRL, Sean Kuno<\/a><\/td>\r\n<\/tr>\r\n
Wednesday, December 9<\/strong><\/td>\r\n<\/tr>\r\n
Time (PT)<\/strong><\/td>\r\nLive Demo<\/strong><\/td>\r\n<\/tr>\r\n
11:00\u201312:00<\/td>\r\nMineRL, Sean Kuno<\/a><\/td>\r\n<\/tr>\r\n
13:00\u201313:30<\/td>\r\nRecruiting Q&A, Amy Sibenthaler<\/td>\r\n<\/tr>\r\n
15:00\u201316:00<\/td>\r\nMineRL, Sean Kuno<\/a><\/td>\r\n<\/tr>\r\n
17:00\u201318:00<\/td>\r\nThe future of intelligent sensors and Low code\/No code model creation, Henry Jerez<\/td>\r\n<\/tr>\r\n
Thursday, December 10<\/strong><\/td>\r\n<\/tr>\r\n
Time (PT)<\/strong><\/td>\r\nLive Demo<\/strong><\/td>\r\n<\/tr>\r\n
11:00\u201312:00<\/td>\r\nMineRL, Sean Kuno<\/a><\/td>\r\n<\/tr>\r\n
13:00\u201313:30<\/td>\r\nRecruiting Q&A, Amy Sibenthaler<\/td>\r\n<\/tr>\r\n
15:00\u201316:00<\/td>\r\nMineRL, Sean Kuno<\/a><\/td>\r\n<\/tr>\r\n
16:00\u201317:00<\/td>\r\nThe future of intelligent sensors and Low code\/No code model creation, Henry Jerez<\/td>\r\n<\/tr>\r\n<\/tbody>\r\n<\/table>"},{"id":2,"name":"Accepted papers","content":"[accordion][panel header=\"Monday, December 7\"]\r\n

Monday, December 7<\/h2>\r\n

18:15\u201318:30 PT | Oral: COVID\/Health\/Bio Applications<\/p>\r\n

Multi-Task Temporal Shift Attention Networks for On-Device Contactless Vitals Measurement<\/b><\/a><\/p>\r\n

Xin Liu, Josh Fromm, Shwetak Patel, Daniel McDuff<\/a><\/p>\r\nPoster Session: December 7<\/em>\r\n

19:00\u201319:10 PT | Spotlight: Representation\/Relational<\/p>\r\n

On the Equivalence between Online and Private Learnability beyond Binary Classification<\/b><\/a><\/p>\r\n

Young H Jung<\/a>, Baekjin Kim, Ambuj Tewari<\/p>\r\nPoster Session: December 7<\/em>\r\n

20:20\u201320:30 PT | Spotlight: Reinforcement Learning<\/p>\r\n

Safe Reinforcement Learning via Curriculum Induction<\/b><\/a><\/p>\r\n

Matteo Turchetta, Andrey Kolobov<\/a>, Shital Shah<\/a>, Andreas Krause, Alekh Agarwal<\/a><\/p>\r\nPoster Session: December 7<\/em>\r\n\r\n

\r\n\r\n21:00\u201323:00 PT | Poster Session 0\r\n

Adversarial Attacks on Deep Graph Matching<\/b><\/p>\r\nZijie Zhang, Zeru Zhang, Yang Zhou, Yelong Shen<\/a>, Ruoming Jin, Dejing Dou\r\n

Constrained episodic reinforcement learning in concave-convex and knapsack settings<\/b><\/a><\/p>\r\nKiant\u00e9 Brantley, Miro Dudik<\/a>, Thodoris Lykouris<\/a>, Sobhan Miryoosefi, Max Simchowitz, Aleksandrs Slivkins<\/a>, Wen Sun\r\n

Hierarchical Poset Decoding for Compositional Generalization in Language<\/b><\/a><\/p>\r\nYinuo Guo, Zeqi Lin<\/a>, Jian-Guang Lou<\/a>, Dongmei Zhang<\/a>\r\n

Information Theoretic Regret Bounds for Online Nonlinear Control<\/b><\/a><\/p>\r\nSham Kakade, Akshay Krishnamurthy<\/a>, Kendall Lowrey, Motoya Ohnishi, Wen Sun\r\n

Learning Dynamic Belief Graphs to Generalize on Text-Based Games<\/b><\/a><\/p>\r\nAshutosh Adhikari, Xingdi Yuan<\/a>, Marc-Alexandre C\u00f4t\u00e9<\/a>, Mikul\u00e1\u0161 Zelinka, Marc-Antoine Rondeau<\/a>, Romain Laroche<\/a>, Pascal Poupart, Jian Tang, Adam Trischler<\/a>, Will Hamilton\r\n

MiniLM: Deep Self-Attention Distillation for Task-Agnostic Compression of Pre-Trained Transformers<\/b><\/p>\r\nWenhui Wang<\/a>, Furu Wei<\/a>, Li Dong<\/a>, Hangbo Bao, Nan Yang<\/a>, Ming Zhou<\/a>\r\n

MOReL: Model-Based Offline Reinforcement Learning<\/b><\/a><\/p>\r\nRahul Kidambi, Aravind Rajeswaran, Praneeth Netrapalli<\/a>, Thorsten Joachims\r\n

MPNet: Masked and Permuted Pre-training for Language Understanding<\/b><\/a><\/p>\r\nKaitao Song, Xu Tan<\/a>, Tao Qin<\/a>, Jianfeng Lu, Tie-Yan Liu<\/a>\r\n

Multi-Task Temporal Shift Attention Networks for On-Device Contactless Vitals Measurement<\/b><\/a><\/p>\r\n

Xin Liu, Josh Fromm, Shwetak Patel, Daniel McDuff<\/a><\/p>\r\nOral Session: December 7<\/em>\r\n

On the Equivalence between Online and Private Learnability beyond Binary Classification<\/b><\/a><\/p>\r\n

Young H Jung<\/a>, Baekjin Kim, Ambuj Tewari<\/p>\r\nSpotlight Session: December 7<\/em>\r\n

Parametric Instance Classification for Unsupervised Visual Feature learning<\/b><\/p>\r\nYue Cao<\/a>, Zhenda Xie, Bin Liu, Yutong Lin, Zheng Zhang<\/a>, Han Hu<\/a>\r\n

Provably Good Batch Reinforcement Learning Without Great Exploration<\/b><\/a><\/p>\r\nYao Liu, Adith Swaminathan<\/a>, Alekh Agarwal<\/a>, Emma Brunskill\r\n

Restoring Negative Information in Few-Shot Object Detection<\/b><\/p>\r\nYukuan Yang, Fangyun Wei<\/a>, Miaojing Shi, Guoqi Li\r\n

Safe Reinforcement Learning via Curriculum Induction<\/b><\/a><\/p>\r\n

Matteo Turchetta, Andrey Kolobov<\/a>, Shital Shah<\/a>, Andreas Krause, Alekh Agarwal<\/a><\/p>\r\nSpotlight Session: December 7<\/em>\r\n

Sampling-Decomposable Generative Adversarial Recommender<\/b><\/a><\/p>\r\nBinbin Jin, Defu Lian, Zheng Liu<\/a>, Qi Liu, Jianhui Ma, Xing Xie<\/a>, Enhong Chen\r\n

Understanding Global Feature Contributions With Additive Importance Measures<\/b><\/a><\/p>\r\nIan Covert, Scott Lundberg<\/a>, Su-In Lee [\/panel][panel header=\"Tuesday, December 8\"]\r\n

Tuesday, December 8<\/h2>\r\n

06:30\u201306:45 PT | Oral: Reinforcement Learning<\/p>\r\n

FLAMBE: Structural Complexity and Representation Learning of Low Rank MDPs<\/b><\/a><\/p>\r\n

Alekh Agarwal<\/a>, Sham Kakade, Akshay Krishnamurthy<\/a>, Wen Sun<\/p>\r\nPoster Session: December 8<\/em>\r\n

07:00\u201307:10 PT | Spotlight: Social\/Privacy<\/p>\r\n

Multi-Robot Collision Avoidance under Uncertainty with Probabilistic Safety Barrier Certificates<\/b><\/p>\r\n

Wenhao Luo, Wen Sun, Ashish Kapoor<\/a><\/p>\r\nPoster Session: December 8<\/em>\r\n

07:30\u201307:40 PT | Spotlight: Vision Applications<\/p>\r\n

Learning Semantic-aware Normalization for Generative Adversarial Networks<\/b><\/p>\r\n

Heliang Zheng, Jianlong Fu<\/a>, Yanhong Zeng, Zheng-Jun Zha, Jiebo Luo<\/p>\r\nPoster Session: December 8<\/em>\r\n

07:40\u201308:00 PT | Demonstration<\/p>\r\n

MosAIc: Finding Artistic Connections across Culture with Conditional Image Retrieval<\/b><\/p>\r\nMark Hamilton, Lei Zhang, Bill Freeman, Marina Rogers, Darius Bopp, Johnny Bui, Margaret Wang, Mindren Lu, Zhenbang Chen, Christopher Hoder\r\n

08:20\u201308:30 PT | Spotlight: Reinforcement Learning<\/p>\r\n

Sample-Efficient Reinforcement Learning of Undercomplete POMDPs<\/b><\/a><\/p>\r\n

Chi Jin, Sham Kakade, Akshay Krishnamurthy<\/a>, Qinghua Liu<\/p>\r\nPoster Session: December 8<\/em>\r\n\r\n

\r\n\r\n09:00\u201311:00 PT | Poster Session 1\r\n

CoinPress: Practical Private Mean and Covariance Estimation<\/b><\/a><\/p>\r\nSourav Biswas, Yihe Dong<\/a>, Gautam Kamath, Jonathan Ullman\r\n

Cross-validation Confidence Intervals for Test Error<\/b><\/a><\/p>\r\nPierre Bayle, Alexandre Bayle, Lucas Janson, Lester Mackey<\/a>\r\n

Deep Reinforcement and InfoMax Learning<\/b><\/a><\/p>\r\nBogdan Mazoure, Remi Tachet des Combes<\/a>, Thang Long DOAN, Philip Bachman<\/a>, R Devon Hjelm<\/a>\r\n

Denoised Smoothing: A Provable Defense for Pretrained Classifiers<\/b><\/a><\/p>\r\nHadi Salman<\/a>, Mingjie Sun, Greg Yang<\/a>, Ashish Kapoor<\/a>, J. Zico Kolter\r\n

Efficient Contextual Bandits with Continuous Actions<\/b><\/a><\/p>\r\nMaryam Majzoubi, Chicheng Zhang, Rajan Chari<\/a>, Akshay Krishnamurthy<\/a>, John Langford<\/a>, Aleksandrs Slivkins<\/a>\r\n

Fairness in Streaming Submodular Maximization: Algorithms and Hardness<\/b><\/a><\/p>\r\nMarwa El Halabi, Slobodan Mitrovi\u0107, Ashkan Norouzi-Fard, Jakab Tardos, Jakub Tarnawski<\/a>\r\n

FLAMBE: Structural Complexity and Representation Learning of Low Rank MDPs<\/b><\/a><\/p>\r\n

Alekh Agarwal<\/a>, Sham Kakade, Akshay Krishnamurthy<\/a>, Wen Sun<\/p>\r\nOral Session: December 8<\/em>\r\n

Learning Semantic-aware Normalization for Generative Adversarial Networks<\/b><\/p>\r\n

Heliang Zheng, Jianlong Fu<\/a>, Yanhong Zeng, Zheng-Jun Zha, Jiebo Luo<\/p>\r\nSpotlight Session: December 8<\/em>\r\n

Learning Structured Distributions From Untrusted Batches: Faster and Simpler<\/b><\/p>\r\nSitan Chen, Jerry Li<\/a>, Ankur Moitra\r\n

Learning the Linear Quadratic Regulator from Nonlinear Observations<\/b><\/a><\/p>\r\nZakaria Mhammedi, Dylan Foster, Max Simchowitz, Wen Sun, Dipendra Misra<\/a>, Akshay Krishnamurthy<\/a>, Alexander Rakhlin, John Langford<\/a>\r\n

Multi-Robot Collision Avoidance under Uncertainty with Probabilistic Safety Barrier Certificates<\/b><\/p>\r\n

Wenhao Luo, Wen Sun, Ashish Kapoor<\/a><\/p>\r\nSpotlight Session: December 8<\/em>\r\n

Network size and size of the weights in memorization with two-layers neural networks<\/b><\/p>\r\nSebastien Bubeck<\/a>, Ronen Eldan, Yin Tat Lee, Dan Mikulincer\r\n

On Infinite-Width Hypernetworks<\/b><\/a><\/p>\r\nEtai Littwin, Tomer Galanti, Lior Wolf, Greg Yang<\/a>\r\n

PC-PG: Policy Cover Directed Exploration for Provable Policy Gradient Learning<\/b><\/a><\/p>\r\nAlekh Agarwal<\/a>, Mikael Henaff<\/a>, Sham Kakade<\/a>, Wen Sun\r\n

Provably adaptive reinforcement learning in metric spaces<\/b><\/a><\/p>\r\nTongyi Cao, Akshay Krishnamurthy<\/a>\r\n

Pushing the Limits of Narrow Precision Inferencing at Cloud Scale with Microsoft Floating Point<\/b><\/a><\/p>\r\nBita Darvish Rouhani<\/a>, Daniel Lo<\/a>, Ritchie Zhao<\/a>, Ming Liu<\/a>, Jeremy Fowers<\/a>, Kalin Ovtcharov<\/a>, Anna Vinogradsky, Sarah Massengill<\/a>, Lita Yang<\/a>, Ray Bittner<\/a>, Alessandro Forin<\/a>, Haishan Zhu<\/a>, Taesik Na<\/a>, Prerak Patel<\/a>, Shuai Che<\/a>, Lok Chand Koppaka<\/a>, Steve Reinhardt<\/a>, Sitaram Lanka<\/a>, Xia Song<\/a>, Subhojit Som<\/a>, Kaustav Das<\/a>, Saurabh K T<\/a>, Eric Chung<\/a>, Doug Burger<\/a>\r\n

RepPoints v2: Verification Meets Regression for Object Detection<\/b><\/p>\r\nYihong Chen, Zheng Zhang<\/a>, Yue Cao<\/a>, Liwei Wang, Stephen Lin<\/a>, Han Hu<\/a>\r\n

Robust and Heavy-Tailed Mean Estimation Made Simple, via Regret Minimization<\/b><\/p>\r\nSam Hopkins, Jerry Li<\/a>, Fred Zhang\r\n

Sample-Efficient Reinforcement Learning of Undercomplete POMDPs<\/b><\/a><\/p>\r\n

Chi Jin, Sham Kakade<\/a>, Akshay Krishnamurthy<\/a>, Qinghua Liu<\/p>\r\nSpotlight Session: December 8<\/em>\r\n

The LoCA Regret: A Consistent Metric to Evaluate Model-Based Behavior in Reinforcement Learning<\/b><\/a><\/p>\r\nHarm Van Seijen<\/a>, Hadi Nekoei, Evan Racah, Sarath Chandar\r\n\r\n

\r\n

18:30\u201318:45 PT | Oral: Vision Applications<\/p>\r\n

Do Adversarially Robust ImageNet Models Transfer Better?<\/b><\/a><\/p>\r\n

Hadi Salman<\/a>, Andrew Ilyas, Logan Engstrom, Ashish Kapoor<\/a>, Aleksander Madry<\/p>\r\nPoster Session: December 8<\/em>\r\n

19:30\u201319:40 PT | Spotlight: Vision Applications<\/p>\r\n

Large-Scale Adversarial Training for Vision-and-Language Representation Learning<\/b><\/a><\/p>\r\n

Zhe Gan<\/a>, Yen-Chun Chen<\/a>, Linjie Li<\/a>, Chen Zhu, Yu Cheng<\/a>, Jingjing Liu<\/a><\/p>\r\nPoster Session: December 8<\/em>\r\n

19:50\u201320:00 PT | Spotlight: Deep Learning\/Theory<\/p>\r\n

Robust Sub-Gaussian Principal Component Analysis and Width-Independent Schatten Packing<\/b><\/p>\r\n

Arun Jambulapati, Jerry Li<\/a>, Kevin Tian<\/p>\r\nPoster Session: December 8<\/em>\r\n

20:50\u201320:00 PT | Spotlight: Reinforcement Learning<\/p>\r\n

Policy Improvement via Imitation of Multiple Oracles<\/b><\/a><\/p>\r\n

Ching-An Cheng<\/a>, Andrey Kolobov<\/a>, Alekh Agarwal<\/a><\/p>\r\nPoster Session: December 8<\/em>\r\n\r\n

\r\n\r\n21:00\u201323:00 PT | Poster Session 2\r\n

Do Adversarially Robust ImageNet Models Transfer Better?<\/b><\/a><\/p>\r\n

Hadi Salman<\/a>, Andrew Ilyas, Logan Engstrom, Ashish Kapoor<\/a>, Aleksander Madry<\/p>\r\nOral Session: December 8<\/em>\r\n

GreedyFool: Distortion-Aware Sparse Adversarial Attack<\/b><\/p>\r\nXiaoyi Dong, Dongdong Chen<\/a>, Jianmin Bao<\/a>, Chuan Qin, Lu Yuan<\/a>, Weiming Zhang, Nenghai Yu, Dong Chen<\/a>\r\n

Large-Scale Adversarial Training for Vision-and-Language Representation Learning<\/b><\/a><\/p>\r\n

Zhe Gan<\/a>, Yen-Chun Chen<\/a>, Linjie Li<\/a>, Chen Zhu, Yu Cheng<\/a>, Jingjing Liu<\/a><\/p>\r\nSpotlight Session: December 8<\/em>\r\n

Policy Improvement via Imitation of Multiple Oracles<\/b><\/a><\/p>\r\n

Ching-An Cheng<\/a>, Andrey Kolobov<\/a>, Alekh Agarwal<\/a><\/p>\r\nSpotlight Session: December 8<\/em>\r\n

RD2: Reward Decomposition with Representation Disentanglement<\/b><\/a><\/p>\r\nZichuan Lin, Derek Yang, Li Zhao<\/a>, Tao Qin<\/a>, Guangwen Yang, Tie-Yan Liu<\/a>\r\n

Robust Gaussian Covariance Estimation in Nearly-Matrix Multiplication Time<\/b><\/p>\r\nJerry Li<\/a>, Guanghao Ye\r\n

Robust Sub-Gaussian Principal Component Analysis and Width-Independent Schatten Packing<\/b><\/p>\r\n

Arun Jambulapati, Jerry Li<\/a>, Kevin Tian<\/p>\r\nSpotlight Session: December 8<\/em>\r\n

Towards Interpretable Natural Language Understanding with Explanations as Latent Variables<\/b><\/p>\r\nWangchunshu Zhou, Jinyi Hu, Hanlin Zhang, Xiaodan Liang, Maosong Sun, Chenyan Xiong<\/a>, Jian Tang [\/panel][panel header=\"Wednesday, December 9\"]\r\n

Wednesday, December 9<\/h2>\r\n

06:15\u201306:30 PT | Oral: COVID\/Applications\/Composition<\/p>\r\n

Learning Composable Energy Surrogates for PDE Order Reduction<\/b><\/a><\/p>\r\n

Alex Beatson, Jordan Ash<\/a>, Geoffrey Roeder, Tianju Xue, Ryan Adams<\/p>\r\nPoster Session: December 9<\/em>\r\n

07:00\u201307:10 PT | Spotlight: COVID\/Applications\/Composition<\/p>\r\n

Compositional Generalization by Learning Analytical Expressions<\/b><\/a><\/p>\r\n

Qian Liu, Shengnan An, Jian-Guang Lou<\/a>, Bei Chen<\/a>, Zeqi Lin<\/a>, Yan Gao<\/a>, Bin Zhou, Nanning Zheng, Dongmei Zhang<\/a><\/p>\r\nPoster Session: December 9<\/em>\r\n

07:30\u201307:40 PT | Spotlight: Continual\/Meta\/Misc Learning<\/p>\r\n

Uncertainty-aware Self-training for Few-shot Text Classification<\/b><\/a><\/p>\r\n

Subhabrata Mukherjee<\/a>, Ahmed Awadallah<\/a><\/p>\r\nPoster Session: December 9<\/em>\r\n

07:50\u201308:00 PT | Spotlight: Deep Learning<\/p>\r\n

Implicit Bias in Deep Linear Classification: Initialization Scale vs Training Accuracy<\/b><\/a><\/p>\r\n

Edward Moroshko, Suriya Gunasekar<\/a>, Blake Woodworth, Jason Lee, Nati Srebro, Daniel Soudry<\/p>\r\nPoster Session: December 9<\/em>\r\n

08:10\u201308:20 PT | Spotlight: Optimization<\/p>\r\n

Least Squares Regression with Markovian Data: Fundamental Limits and Algorithms<\/b><\/p>\r\n

Dheeraj Nagaraj, Xian Wu, Guy Bresler, Prateek Jain<\/a>, Praneeth Netrapalli<\/a><\/p>\r\nPoster Session: December 9<\/em>\r\n\r\n

\r\n\r\n09:00\u201311:00 PT | Poster Session 3\r\n

A Causal View on Robustness of Neural Networks<\/b><\/a><\/p>\r\nCheng Zhang<\/a>, Kun Zhang, Yingzhen Li<\/a>\r\n

AvE: Assistance via Empowerment<\/b><\/a><\/p>\r\nYuqing Du, Stas Tiomkin, Emre Kiciman<\/a>, Daniel Polani, Pieter Abbeel, Anca Dragan\r\n

BERT Loses Patience: Fast and Robust Inference with Early Exit<\/b><\/p>\r\nWangchunshu Zhou, Canwen Xu, Tao Ge<\/a>, Julian McAuley, Ke Xu, Furu Wei<\/a>\r\n

Compositional Generalization by Learning Analytical Expressions<\/b><\/a><\/p>\r\n

Qian Liu, Shengnan An, Jian-Guang Lou<\/a>, Bei Chen<\/a>, Zeqi Lin<\/a>, Yan Gao<\/a>, Bin Zhou, Nanning Zheng, Dongmei Zhang<\/a><\/p>\r\nSpotlight Session: December 9<\/em>\r\n

Domain Adaptation with Conditional Distribution Matching and Generalized Label Shift<\/b><\/a><\/p>\r\nRemi Tachet des Combes<\/a>, Han Zhao, Yu-Xiang Wang, Geoffrey Gordon<\/a>\r\n

Efficient Algorithms for Device Placement of DNN Graph Operators<\/b><\/a><\/p>\r\nJakub Tarnawski<\/a>, Amar Phanishayee<\/a>, Nikhil Devanur, Divya Mahajan<\/a>, Fanny Nina Paravecino<\/a>\r\n

Follow the Perturbed Leader: Optimism and Fast Parallel Algorithms for Smooth Minimax Games<\/b><\/p>\r\nArun Suggala, Praneeth Netrapalli<\/a>\r\n

Geometric Dataset Distances via Optimal Transport<\/b><\/a><\/p>\r\nDavid Alvarez Melis, Nicolo Fusi<\/a>\r\n

How do fair decisions fare in long-term qualification?<\/b><\/p>\r\nXueru Zhang, Ruibo Tu, Yang Liu, mingyan liu, Hedvig Kjellstrom, Kun Zhang, Cheng Zhang<\/a>\r\n

Implicit Bias in Deep Linear Classification: Initialization Scale vs Training Accuracy<\/b><\/p>\r\n

Edward Moroshko, Suriya Gunasekar<\/a>, Blake Woodworth, Jason Lee, Nati Srebro, Daniel Soudry<\/p>\r\nSpotlight Session: December 9<\/em>\r\n

Learning Composable Energy Surrogates for PDE Order Reduction<\/b><\/a><\/p>\r\n

Alex Beatson, Jordan Ash<\/a>, Geoffrey Roeder, Tianju Xue, Ryan Adams<\/p>\r\nOral Session: December 9<\/em>\r\n

Least Squares Regression with Markovian Data: Fundamental Limits and Algorithms<\/b><\/p>\r\n

Dheeraj Nagaraj, Xian Wu, Guy Bresler, Prateek Jain<\/a>, Praneeth Netrapalli<\/a><\/p>\r\nSpotlight Session: December 9<\/em>\r\n

MESA: Boost Ensemble Imbalanced Learning with MEta-SAmpler<\/b><\/p>\r\nZhining Liu, Pengfei Wei, Jing Jiang, Wei Cao<\/a>, Jiang Bian<\/a>, Yi Chang\r\n

Minimax Estimation of Conditional Moment Models<\/b><\/a><\/p>\r\nNishanth Dikkala, Greg Lewis<\/a>, Lester Mackey<\/a>, Vasilis Syrgkanis<\/a>\r\n

On the Loss Landscape of Adversarial Training: Identifying Challenges and How to Overcome Them<\/b><\/a><\/p>\r\nChen Liu, Mathieu Salzmann, Tao LIN, Ryota Tomioka<\/a>, Sabine S\u00fcsstrunk\r\n

Statistical Optimal Transport posed as Learning Kernel Embedding<\/b><\/p>\r\nSaketha Nath Jagarlapudi, Pratik Kumar Jawanpuria<\/a>\r\n

The Pitfalls of Simplicity Bias in Neural Networks<\/b><\/p>\r\nHarshay Shah<\/a>, Kaustav Tamuly, Aditi Raghunathan, Prateek Jain<\/a>, Praneeth Netrapalli<\/a>\r\n

Uncertainty-aware Self-training for Few-shot Text Classification<\/b><\/a><\/p>\r\n

Subhabrata Mukherjee<\/a>, Ahmed Awadallah<\/a><\/p>\r\nSpotlight Session: December 9<\/em>\r\n

Zero-Resource Knowledge-Grounded Dialogue Generation<\/b><\/p>\r\nLinxiao Li, Can Xu, Wei Wu, Yufan Zhao, Xueliang Zhao, Chongyang Tao\r\n\r\n

\r\n

19:10\u201319:20 PT | Spotlight: Graph\/Meta Learning\/Software<\/p>\r\n

Spectral Temporal Graph Neural Network for Multivariate Time-series Forecasting<\/b><\/a><\/p>\r\n

Defu Cao, Yujing Wang, Juanyong Duan, Ce Zhang, Xia Zhu<\/a>, Congrui Huang<\/a>, Yunhai Tong, Bixiong Xu<\/a>, Jing Bai<\/a>, Jie Tong<\/a>, Qi Zhang<\/a><\/p>\r\nPoster Session: December 9<\/em>\r\n

20:10\u201320:20 PT | Spotlight: Graph\/Meta Learning\/Software<\/p>\r\n

RNNPool: Efficient Non-linear Pooling for RAM Constrained Inference<\/a><\/b><\/p>\r\n

Oindrila Saha<\/a>, Venkata Aditya Kusupati, Harsha Vardhan Simhadri<\/a>, Manik Varma<\/a>, Prateek Jain<\/a><\/p>\r\nPoster Session: December 9<\/em>\r\n

20:20\u201320:30 PT | Spotlight: Vision Applications<\/p>\r\n

RelationNet++: Bridging Visual Representations for Object Detection via Transformer Decoder<\/b><\/p>\r\n

Cheng Chi, Fangyun Wei<\/a>, Han Hu<\/a><\/p>\r\nPoster Session: December 9<\/em>\r\n\r\n

\r\n\r\n21:00\u201323:00 PT | Poster Session 4\r\n

A Matrix Chernoff Bound for Markov Chains and Its Application to Co-occurrence Matrices<\/b><\/a><\/p>\r\nJiezhong Qiu, Chi Wang<\/a>, Ben Liao, Richard Peng, Jie Tang\r\n

Adaptive Learning of Rank-One Models for Efficient Pairwise Sequence Alignment<\/b><\/p>\r\nGovinda Kamath<\/a>, Tavor Baharav, Ilan Shomorony\r\n

GAN Memory with No Forgetting<\/b><\/p>\r\nChunyuan Li<\/a>, Miaoyun Zhao, Jianqiao Li, Sijia Wang, Lawrence Carin\r\n

Online Influence Maximization under Linear Threshold Model<\/b><\/a><\/p>\r\nShuai Li, Fang Kong, Kejie Tang, Qizhi Li, Wei Chen<\/b>\r\n

RelationNet++: Bridging Visual Representations for Object Detection via Transformer Decoder<\/b><\/p>\r\n

Cheng Chi, Fangyun Wei<\/a>, Han Hu<\/a><\/p>\r\nSpotlight Session: December 9<\/em>\r\n

RNNPool: Efficient Non-linear Pooling for RAM Constrained Inference<\/a><\/b><\/p>\r\n

Oindrila Saha<\/a>, Venkata Aditya Kusupati, Harsha Vardhan Simhadri<\/a>, Manik Varma<\/a>, Prateek Jain<\/a><\/p>\r\nSpotlight Session: December 9<\/em>\r\n

Spectral Temporal Graph Neural Network for Multivariate Time-series Forecasting<\/b><\/a><\/p>\r\n

Defu Cao, Yujing Wang, Juanyong Duan, Ce Zhang, Xia Zhu<\/a>, Congrui Huang<\/a>, Yunhai Tong, Bixiong Xu<\/a>, Jing Bai<\/a>, Jie Tong<\/a>, Qi Zhang<\/a><\/p>\r\nSpotlight Session: December 9<\/em> [\/panel][panel header=\"Thursday, December 10\"]\r\n

Thursday, December 10<\/h2>\r\n

07:10\u201307:20 PT | Spotlight: Optimization<\/p>\r\n

Projection Efficient Subgradient Method and Optimal Nonsmooth Frank-Wolfe Method<\/b><\/a><\/p>\r\n

Kiran Thekumparampil, Prateek Jain<\/a>, Praneeth Netrapalli<\/a>, Sewoong Oh<\/p>\r\nPoster Session: December 10<\/em>\r\n

08:20\u201308:30 PT | Spotlight: Graph\/Relational\/Theory<\/p>\r\n

Beyond Perturbations: Learning Guarantees with Arbitrary Adversarial Test Examples<\/b><\/a><\/p>\r\n

Shafi Goldwasser, Adam Tauman Kalai<\/a>, Yael Kalai, Omar Montasser<\/p>\r\nPoster Session: December 10<\/em>\r\n\r\n

\r\n\r\n09:00\u201311:00 PT | Poster Session 5\r\n

Beyond Perturbations: Learning Guarantees with Arbitrary Adversarial Test Examples<\/b><\/a><\/p>\r\n

Shafi Goldwasser, Adam Tauman Kalai<\/a>, Yael Kalai, Omar Montasser<\/p>\r\nSpotlight Session: December 10<\/em>\r\n

COPT: Coordinated Optimal Transport on Graphs<\/b><\/a><\/p>\r\nYihe Dong<\/a>, Will Sawin\r\n

Empirical Likelihood for Contextual Bandits<\/b><\/a><\/p>\r\nPaul Mineiro<\/a>, Nikos Karampatziakis<\/a>, John Langford<\/a>\r\n

Implicit Regularization and Convergence for Weight Normalization<\/b><\/a><\/p>\r\nXiaoxia Wu, Edgar Dobriban, Tongzheng Ren, Shanshan Wu, Zhiyuan Li, Suriya Gunasekar<\/a>, Rachel Ward, Qiang Liu\r\n

On the Expressiveness of Approximate Inference in Bayesian Neural Networks<\/b><\/p>\r\nAndrew Foong, David Burt, Yingzhen Li<\/a>, Richard E Turner\r\n

On Warm-Starting Neural Network Training<\/b><\/a><\/p>\r\nJordan Ash<\/a>, Ryan Adams\r\n

VAEM: a Deep Generative Model for Heterogeneous Mixed Type Data<\/b><\/p>\r\nChao Ma, Sebastian Tschiatschek, Richard E Turner, Jos\u00e9 Miguel Hern\u00e1ndez-Lobato, Cheng Zhang<\/a>\r\n\r\n

\r\n

18:30\u201318:45 PT | Oral: Optimization<\/p>\r\n

Fully Dynamic Algorithm for Constrained Submodular Optimization<\/b><\/a><\/p>\r\n

Silvio Lattanzi, Slobodan Mitrovi\u0107, Ashkan Norouzi-Fard, Jakub Tarnawski<\/a>, Morteza Zadimoghaddam<\/p>\r\nPoster Session: December 10<\/em>\r\n\r\n

\r\n\r\n21:00\u201323:00 PT | Poster Session 6\r\n

Accelerating Training of Transformer-Based Language Models with Progressive Layer Dropping<\/b><\/a><\/p>\r\nMinjia Zhang<\/a>, Yuxiong He<\/a>\r\n

AdaTune: Adaptive Tensor Program Compilation Made Efficient<\/b><\/a><\/p>\r\nMenghao Li<\/a>, Minjia Zhang<\/a>, Chi Wang<\/a>, Mingqin Li<\/a>\r\n

Cream of the Crop: Distilling Prioritized Paths For One-Shot Neural Architecture Search<\/b><\/p>\r\nHouwen Peng<\/a>, Hao Du<\/a>, Hongyuan Yu, QI LI, Jing Liao, Jianlong Fu<\/a>\r\n

Disentangling Human Error from Ground Truth in Segmentation of Medical Images<\/b><\/a><\/p>\r\nLe Zhang, Ryutaro Tanno<\/a>, Moucheng Xu, Chen Jin, Joseph Jacob, Olga Cicarrelli, Frederik Barkhof, Daniel Alexander\r\n

Fully Dynamic Algorithm for Constrained Submodular Optimization<\/b><\/a><\/p>\r\n

Silvio Lattanzi, Slobodan Mitrovi\u0107, Ashkan Norouzi-Fard, Jakub Tarnawski<\/a>, Morteza Zadimoghaddam<\/p>\r\nOral Session: December 10<\/em>\r\n

Graph Policy Network for Transferable Active Learning on Graphs<\/b><\/p>\r\nShengding Hu, Zheng Xiong, Meng Qu, Xingdi Yuan<\/a>, Marc-Alexandre C\u00f4t\u00e9<\/a>, Zhiyuan Liu, Jian Tang\r\n

HM-ANN: Efficient Billion-Point Nearest Neighbor Search on Heterogeneous Memory<\/b><\/a><\/p>\r\nJie Ren, Minjia Zhang<\/a>, Dong Li\r\n

ImpatientCapsAndRuns: Approximately Optimal Algorithm Configuration from an Infinite Pool<\/b><\/a><\/p>\r\nGellert Weisz, Andr\u00e1s Gy\u00f6rgy, Wei-I Lin, Devon Graham, Kevin Leyton-Brown, Csaba Szepesvari, Brendan Lucier<\/a>\r\n

Intra Order-preserving Functions for Calibration of Multi-Class Neural Networks<\/b><\/a><\/p>\r\nAmir Rahimi, Amirreza Shaban, Ching-An Cheng<\/a>, Richard I Hartley, Byron Boots\r\n

Passport-aware Normalization for Deep Model Protection<\/b><\/p>\r\nJie Zhang, Dongdong Chen<\/a>, Jing Liao, Weiming Zhang, Gang Hua, Nenghai Yu\r\n

Projection Efficient Subgradient Method and Optimal Nonsmooth Frank-Wolfe Method<\/b><\/a><\/p>\r\n

Kiran Thekumparampil, Prateek Jain<\/a>, Praneeth Netrapalli<\/a>, Sewoong Oh<\/p>\r\nSpotlight Session: December 10<\/em>\r\n

Semi-Supervised Neural Architecture Search<\/b><\/a><\/p>\r\nRenqian Luo, Xu Tan<\/a>, Rui Wang<\/a>, Tao Qin<\/a>, Enhong Chen, Tie-Yan Liu<\/a>\r\n

Stochastic Stein Discrepancies<\/b><\/a><\/p>\r\nJackson Gorham, Anant Raj, Lester Mackey<\/a> [\/panel][\/accordion]"},{"id":3,"name":"Tutorials & Workshops","content":"

Sunday, December 6<\/h2>\r\n10:00 PT | Workshop\r\nReal World RL with Vowpal Wabbit: Beyond Contextual Bandits<\/strong>\r\nJacob Alber<\/a>, John Langford<\/a>, Rafah Hosn<\/a>\r\n\r\n14:00 PT | Talk\r\nThe Unpaved Path of Deploying Reliable and Human-Centered Machine Learning Systems<\/strong>\r\nBesmira Nushi<\/a>\r\n\r\n
\r\n\r\n

Monday, December 7<\/h2>\r\n06:00 \u2013 12:30 PT | Workshop\r\nBlack in AI<\/strong><\/a>\r\nMentorship Roundtable Hosts: Danielle Belgrave<\/a>, Hanna Wallach<\/a>, Jenn Wortman Vaughan<\/a>\r\n\r\n08:00\u201310:30 PT | Tutorial\r\nAdvances in Approximate Inference<\/b>\r\nYingzhen Li<\/a>, Cheng Zhang<\/a>\r\n\r\n
\r\n\r\n

Tuesday, December 8<\/h2>\r\n12:00\u201316:00 PT | Symposium\r\nCOVID-19 Symposium Day 1<\/strong><\/a>\r\nAndrew Beam, Tristan Naumann<\/a>, Katherine Heller, Elaine Nsoesie\r\n\r\n
\r\n\r\n

Wednesday, December 9<\/h2>\r\n01:40 \u2013 18:00 PT | Workshop\r\nWomen in Machine Learning<\/strong><\/a>\r\nDiversity & Inclusion Co-chair: Danielle Belgrave<\/a>\r\nArea Chair: Besmira Nushi<\/a>\r\nMentorship Roundtable Hosts: Chris Bishop<\/a>, Danielle Belgrave<\/a>, Emma Pierson<\/a>, Jenn Wortman Vaughan<\/a>, John Langford<\/a>, Kate Crawford<\/a>, Nicolo Fusi<\/a>, Sham Kakade<\/a>, Stephanie Hyland<\/a>, Susan Dumais<\/a>\r\n\r\n12:00\u201316:00 PT | Symposium\r\nCOVID-19 Symposium Day 2<\/strong><\/a>\r\nAndrew Beam, Tristan Naumann<\/a>, Katherine Heller, Elaine Nsoesie\r\n\r\n
\r\n\r\n

Friday, December 11<\/h2>\r\n06:50\u201316:50 PT | Workshop\r\nCausal Discovery and Causality-Inspired Machine Learning<\/b><\/a>\r\nBiwei\u00a0Huang,\u00a0Sara\u00a0Magliacane,\u00a0Kun\u00a0Zhang,\u00a0Danielle Belgrave<\/a>,\u00a0Elias\u00a0Bareinboim,\u00a0Daniel Malinsky,\u00a0Thomas Richardson,\u00a0Christopher Meek<\/a>,\u00a0Peter\u00a0Spirtes,\u00a0Bernhard\u00a0Sch\u00f6lkopf\r\n\r\n06:00\u201316:20 PT | Workshop\r\nMachine Learning for Health: Advancing Healthcare for All<\/b><\/a>\r\nStephanie Hyland<\/a>,\u00a0Emily\u00a0Alsentzer,\u00a0Andrew Beam,\u00a0Brett Beaulieu-Jones,\u00a0Danielle Belgrave<\/a>,\u00a0Allen Schmaltz,\u00a0Irene Y Chen,\u00a0Anna Goldenberg,\u00a0Matthew McDermott,\u00a0Tristan Naumann<\/a>,\u00a0Charles\u00a0Onu\r\n\r\n08:30\u201321:00 PT | Workshop\r\nML Retrospectives, Surveys & meta-Analyses<\/a>\u00a0<\/b>\r\nChhavi\u00a0Yadav,\u00a0Prabhu Pradhan,\u00a0Abhishek Gupta<\/a>,\u00a0Ryan Lowe,\u00a0Peter Henderson,\u00a0Jessica Forde Jessica Forde,\u00a0Mayoore\u00a0Jaiswal,\u00a0Jesse Dodge\r\n\r\n
\r\n\r\n

Saturday, December 12<\/h2>\r\nMachine Learning For Systems<\/strong> | Workshop\r\nAccepted paper: Resonance: Replacing Software Constants with Context-Aware Models in Real-time Communication<\/a>\r\nJayant Gupchup<\/strong>, Ashkan Aazami<\/strong>, Yaran Fan<\/strong>, Senja Filipi<\/strong>, Tom Finley<\/strong>, Scott Inglis<\/strong>, Marcus Asteborg<\/strong>, Luke Caroll<\/strong>, Rajan Chari<\/strong>, Markus Cozowicz<\/strong>, Vishak Gopal<\/strong>, Vinod Prakash<\/strong>, Sasikanth Bendapudi<\/strong>, Jack Gerrits<\/strong>, Eric Lau<\/strong>, Huazhou Liu<\/strong>, Marco Rossi<\/strong>, Dima Slobodianyk<\/strong>, Dmitri Birjukov<\/strong>, Matty Cooper<\/strong>, Nilesh Javar<\/strong>, Dmitriy Perednya<\/strong>, Sriram Srinivasan<\/strong>, John Langford<\/strong>, Ross Cutler<\/strong>, Johannes Gehrke<\/strong>\r\n\r\n04:45\u201314:45 PT | Workshop\r\nI Can\u2019t Believe it is Not Better: Bridging the Gap between Theory and Empiricism in Probabilistic Machine Learning<\/strong><\/a>\r\nJessica Zosa Forde, Francisco Ruiz, Melanie F. Pradier<\/a>, Aaron Schein, Finale Doshi-Velez, David Blei, Hanna Wallach<\/a>\r\n\r\n05:20\u201312:55 PT | Workshop\r\nCooperative AI<\/b><\/a>\r\nThore\u00a0Graepel,\u00a0Dario\u00a0Amodei,\u00a0Vincent\u00a0Conitzer,\u00a0Allan Dafoe,\u00a0Gillian Hadfield,\u00a0Eric Horvitz<\/a>,\u00a0Sarit Kraus,\u00a0Kate Larson,\u00a0Yoram Bachrach\r\n\r\n05:30\u201315:00 PT | Workshop\r\nNavigating the Broader Impacts of AI Research<\/b><\/a>\r\nAccepted paper: Overcoming Failures of Imagination in AI Infused System Development and Deployment<\/a>\r\nCarolyn Ashurst,\u00a0Rosie Campbell,\u00a0Deborah Raji,\u00a0Solon Barocas<\/a>,\u00a0Stuart Russell\r\n\r\n06:00\u201315:00 PT | Workshop\r\nWordplay: When Language Meets Games<\/b><\/a>\r\nPrithviraj\u00a0Ammanabrolu,\u00a0Matthew Hausknecht<\/a>,\u00a0Xingdi\u00a0Yuan<\/a>,\u00a0Marc-Alexandre\u00a0C\u00f4t\u00e9<\/a>,\u00a0Adam Trischler<\/a>, Kory Mathewson, John\u00a0Urbanek,\u00a0Jason Weston,\u00a0Mark\u00a0Riedl\r\n\r\n08:50\u201318:40 PT | Workshop\r\nSelf-Supervised Learning \u2013 Theory and Practice<\/strong><\/a>\r\nAccepted paper: Make Lead Bias in Your Favor: Zero-shot Abstractive News Summarization<\/a>\r\nChenguang Zhu<\/a>, Ziyi Yang, Robert Gmyr<\/a>, Michael Zeng<\/a>, Xuedong Huang<\/a>"},{"id":4,"name":"Competitions","content":"

Competitions<\/h2>\r\nDiagnostic Questions: Predicting Student Responses and Measuring Question Quality<\/b><\/a>\r\nSimon Woodhead, Craig Barton, Jos\u00e9 Miguel Hern\u00e1ndez-Lobato, Richard Turner, Jack Wang, Richard G. Baraniuk, Angus Lamb<\/a>,\u00a0Evgeny\u00a0Saveliev,\u00a0Pashmina Cameron<\/a>, Yordan Zaykov<\/a>, Simon Peyton-Jones<\/a>,\u00a0Cheng Zhang<\/a>\r\n\r\nEfficient Open-Domain Question Answering<\/strong><\/a>\r\nHao Cheng<\/strong>, Yelong Shen<\/strong>, Xiaodong Liu<\/a>, Pengcheng He<\/strong>, Weizhu Chen<\/strong>, Jianfeng Gao<\/a>\r\n*First place in the Efficient Open-Domain Question Answering unrestrictive track<\/em>\r\n\r\nHide-and-Seek Privacy Challenge: Synthetic Data Generation vs. Patient Re-identification with Clinical Time-series Data<\/b> <\/a>\r\nJames Jordon, Daniel Jarrett, Jinsung Yoon, Paul Elbers, Patrick Thoral, Ari Ercole, Cheng Zhang<\/a>, Danielle Belgrave<\/a>,\u00a0Mihaela van der Schaar, Nick Maxfield"},{"id":5,"name":"Webinars","content":"Discover more about work accepted at NeurIPS 2020 in these webinars presented by Microsoft Research. Join these experts as they present their research in practical tutorials and answer questions afterwards in a live Q&A. All presentations and live Q&A sessions are recorded and will be available on demand.\r\n\r\nTo learn more about the webinars and for registration, click \u201cregister\u201d below. See our full list of offerings at the Microsoft Research Webinars<\/a> homepage.\r\n
<\/div>\r\n[row][column class=\"m-col-12-24\"]\"Amit<\/a>\r\nFoundations of causal inference and its impacts on machine learning<\/strong><\/a>\r\n\r\nDecember 3, 2020 | 08:00 AM (PT)\r\n
[msr-button text=\"Register\" url=\"https:\/\/note.microsoft.com\/MSR-Webinar-DoWhy-Library-Registration-Live.html\" new-window=\"true\" ]<\/div>\r\n[\/column]\r\n[column class=\"m-col-12-24\"]\"Daniel<\/a>\r\nCamera-based non-contact health sensing<\/strong><\/a>\r\n\r\nAvailable on-demand\r\n
[msr-button text=\"Register\" url=\"https:\/\/note.microsoft.com\/MSR-Webinar-Health-Sensing-Registration-On-Demand.html\" new-window=\"true\" ]<\/div>\r\n[\/column][\/row]\r\n[row][column class=\"m-col-12-24\"]<\/a>\r\nDiscovering hidden connections in art with deep, interpretable visual analogies<\/strong><\/a>\r\n\r\nAvailable on-demand\r\n
[msr-button text=\"Register\" url=\"https:\/\/note.microsoft.com\/MSR-Webinar-Visual-Analogies-Registration-On-Demand.html\" new-window=\"true\" ]<\/div>\r\n[\/column][column class=\"m-col-12-24\"][\/column][\/row]"},{"id":6,"name":"#AlchemyFriends","content":"Print your own copy<\/a> of Alchemy with Friends to play at home.\r\n\r\nShare your favorite card combinations using #AlchemyFriends on Twitter, Facebook, or Instagram. We now have three versions of the game available for you to play at home!\r\n\r\n\"Animated<\/a>\r\n
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[msr-button text=\"Alchemy with Friends Original (must have this deck)\" url=\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2020\/11\/Alchemy-with-Friends-Print-at-Home-2020.pdf\" new-window=\"true\" ]<\/div>\r\n
[msr-button text=\"Alchemy with Friends ML Expansion Pack\" url=\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2020\/06\/Alchemy-with-Friends-ML-Expansion-Pack.pdf\" new-window=\"true\" ]<\/div>\r\n
[msr-button text=\"Alchemy with Friends CV Expansion Pack\" url=\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2020\/06\/Alchemy-with-Friends-CV-Expansion-Pack.pdf\" new-window=\"true\" ]<\/div>\r\n<\/div>\r\n
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