{"id":671130,"date":"2020-07-02T15:27:43","date_gmt":"2020-07-02T22:27:43","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/?post_type=msr-event&p=671130"},"modified":"2025-08-06T11:52:41","modified_gmt":"2025-08-06T18:52:41","slug":"colt-2020","status":"publish","type":"msr-event","link":"https:\/\/www.microsoft.com\/en-us\/research\/event\/colt-2020\/","title":{"rendered":"Microsoft at COLT 2020"},"content":{"rendered":"\n\n

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

Microsoft is proud to be a Platinum sponsor of the Thirty-Third Annual Conference on Learning Theory (COLT) (opens in new tab)<\/span><\/a>, as well as Diamond partners for the Women in Machine Learning workshop (opens in new tab)<\/span><\/a>. Please see detailed information on our contributions to the program below.<\/p>\n

Committee members<\/strong><\/p>\n

Publications Chair: Suriya Gunasekar<\/a><\/p>\n

Senior Program Committee members: Adam Tauman Kalai<\/a>, Alekh Agarwal<\/a>, Alex Slivkins<\/a>, Navin Goyal<\/a>, Praneeth Netrapalli<\/a>, Prateek Jain<\/a>, Robert Schapire<\/a>, S\u00e9bastien Bubeck<\/a>, Vasilis Syrgkanis<\/a><\/p>\n

Accepted papers<\/h3>\n

Thursday, July 9<\/strong><\/p>\n

5:30 AM \u2013 8:00 AM PDT | Session 1A
\nLocally Private Hypothesis Selection<\/strong><\/a>
\nSivakanth Gopi<\/a>, Gautam Kamath, Janardhan D Kulkarni<\/a>, Aleksandar Nikolov, Steven Wu, Huanyu Zhang<\/p>\n

10:00 AM \u2013 12:30 PM PDT | Session 1B
\nFrom Tree Matching to Sparse Graph Alignment<\/strong><\/a>
\nLuca Ganassali, Laurent Massoulie<\/p>\n

10:00 AM \u2013 12:30 PM PDT | Session 1B
\nOptimality and Approximation with Policy Gradient Methods in Markov Decision Processes<\/strong><\/a>
\nAlekh Agarwal<\/a>, Sham Kakade, Jason Lee, Gaurav Mahajan<\/p>\n

Friday, July 10<\/strong><\/p>\n

10:00 AM \u2013 12:30 PM PDT | Session 2B
\nHow to Trap a Gradient Flow<\/strong><\/a>
\nDan Mikulincer, S\u00e9bastien Bubeck<\/a><\/p>\n

5:00 PM \u2013 7:00 PM PDT | Session 2C
\nModel-Based Reinforcement Learning with a Generative Model is Minimax Optimal<\/strong><\/a>
\nAlekh Agarwal<\/a>, Sham Kakade, Lin Yang<\/p>\n

Saturday, July 11<\/strong><\/p>\n

5:30 AM \u2013 8:00 AM PDT | Session 3A
\nEstimation and Inference with Trees and Forests in High Dimensions<\/strong>
\nVasilis Syrgkanis<\/a>, Emmanouil Zampetakis<\/p>\n

10:00 AM \u2013 12:30 PM PDT | Session 3B
\nCoordination Without Communication: Optimal Regret in Two Players Multi-armed Bandits<\/strong><\/a>
\nS\u00e9bastien Bubeck<\/a>, Thomas Budzinski<\/p>\n

10:00 AM \u2013 12:30 PM PDT | Session 3B
\nGradient Descent Follows the Regularization Path for General Losses<\/strong><\/a>
\nZiwei Ji, Miroslav Dudik<\/a>, Robert Schapire<\/a>, Matus Telgarsky<\/p>\n

10:00 AM \u2013 12:30 PM PDT | Session 3B
\nNon-Stochastic Multi-Player Multi-Armed Bandits: Optimal Rate With Collision Information, Sublinear Without<\/strong><\/a>
\nS\u00e9bastien Bubeck<\/a>, Yuanzhi Li, Yuval Peres, Mark Sellke<\/p>\n

10:00 AM \u2013 12:30 PM PDT | Session 3B
\nTaking a Hint: How to Leverage Loss Predictors in Contextual Bandits?<\/strong><\/a>
\nChen-Yu Wei, Haipeng Luo, Alekh Agarwal<\/a>Opens in a new tab<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"

Microsoft is proud to be a Platinum sponsor of the Thirty-Third Annual Conference on Learning Theory (COLT).<\/p>\n","protected":false},"featured_media":0,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"_classifai_error":"","msr_startdate":"2020-07-09","msr_enddate":"2020-07-12","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":[],"msr-event-type":[197941],"msr-video-type":[],"msr-locale":[268875],"msr-program-audience":[],"msr-post-option":[],"msr-impact-theme":[],"class_list":["post-671130","msr-event","type-msr-event","status-publish","hentry","msr-research-area-artificial-intelligence","msr-event-type-conferences","msr-locale-en_us"],"msr_about":"\n\n

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

Microsoft is proud to be a Platinum sponsor of the Thirty-Third Annual Conference on Learning Theory (COLT)<\/a>, as well as Diamond partners for the Women in Machine Learning workshop<\/a>. Please see detailed information on our contributions to the program below.<\/p>\n

Committee members<\/strong><\/p>\n

Publications Chair: Suriya Gunasekar<\/a><\/p>\n

Senior Program Committee members: Adam Tauman Kalai<\/a>, Alekh Agarwal<\/a>, Alex Slivkins<\/a>, Navin Goyal<\/a>, Praneeth Netrapalli<\/a>, Prateek Jain<\/a>, Robert Schapire<\/a>, S\u00e9bastien Bubeck<\/a>, Vasilis Syrgkanis<\/a><\/p>\n

Accepted papers<\/h3>\n

Thursday, July 9<\/strong><\/p>\n

5:30 AM \u2013 8:00 AM PDT | Session 1A
\nLocally Private Hypothesis Selection<\/strong><\/a>
\nSivakanth Gopi<\/a>, Gautam Kamath, Janardhan D Kulkarni<\/a>, Aleksandar Nikolov, Steven Wu, Huanyu Zhang<\/p>\n

10:00 AM \u2013 12:30 PM PDT | Session 1B
\nFrom Tree Matching to Sparse Graph Alignment<\/strong><\/a>
\nLuca Ganassali, Laurent Massoulie<\/p>\n

10:00 AM \u2013 12:30 PM PDT | Session 1B
\nOptimality and Approximation with Policy Gradient Methods in Markov Decision Processes<\/strong><\/a>
\nAlekh Agarwal<\/a>, Sham Kakade, Jason Lee, Gaurav Mahajan<\/p>\n

Friday, July 10<\/strong><\/p>\n

10:00 AM \u2013 12:30 PM PDT | Session 2B
\nHow to Trap a Gradient Flow<\/strong><\/a>
\nDan Mikulincer, S\u00e9bastien Bubeck<\/a><\/p>\n

5:00 PM \u2013 7:00 PM PDT | Session 2C
\nModel-Based Reinforcement Learning with a Generative Model is Minimax Optimal<\/strong><\/a>
\nAlekh Agarwal<\/a>, Sham Kakade, Lin Yang<\/p>\n

Saturday, July 11<\/strong><\/p>\n

5:30 AM \u2013 8:00 AM PDT | Session 3A
\nEstimation and Inference with Trees and Forests in High Dimensions<\/strong>
\nVasilis Syrgkanis<\/a>, Emmanouil Zampetakis<\/p>\n

10:00 AM \u2013 12:30 PM PDT | Session 3B
\nCoordination Without Communication: Optimal Regret in Two Players Multi-armed Bandits<\/strong><\/a>
\nS\u00e9bastien Bubeck<\/a>, Thomas Budzinski<\/p>\n

10:00 AM \u2013 12:30 PM PDT | Session 3B
\nGradient Descent Follows the Regularization Path for General Losses<\/strong><\/a>
\nZiwei Ji, Miroslav Dudik<\/a>, Robert Schapire<\/a>, Matus Telgarsky<\/p>\n

10:00 AM \u2013 12:30 PM PDT | Session 3B
\nNon-Stochastic Multi-Player Multi-Armed Bandits: Optimal Rate With Collision Information, Sublinear Without<\/strong><\/a>
\nS\u00e9bastien Bubeck<\/a>, Yuanzhi Li, Yuval Peres, Mark Sellke<\/p>\n

10:00 AM \u2013 12:30 PM PDT | Session 3B
\nTaking a Hint: How to Leverage Loss Predictors in Contextual Bandits?<\/strong><\/a>
\nChen-Yu Wei, Haipeng Luo, Alekh Agarwal<\/a>Opens in a new tab<\/span><\/p>\n","tab-content":[{"id":0,"name":"About","content":"Microsoft is proud to be a Platinum sponsor of the Thirty-Third Annual Conference on Learning Theory (COLT)<\/a>, as well as Diamond partners for the Women in Machine Learning workshop<\/a>. Please see detailed information on our contributions to the program below.\r\n\r\nCommittee members<\/strong>\r\n\r\nPublications Chair: Suriya Gunasekar<\/a>\r\n\r\nSenior Program Committee members: Adam Tauman Kalai<\/a>, Alekh Agarwal<\/a>, Alex Slivkins<\/a>, Navin Goyal<\/a>, Praneeth Netrapalli<\/a>, Prateek Jain<\/a>, Robert Schapire<\/a>, S\u00e9bastien Bubeck<\/a>, Vasilis Syrgkanis<\/a>\r\n

Accepted papers<\/h3>\r\nThursday, July 9<\/strong>\r\n\r\n5:30 AM \u2013 8:00 AM PDT | Session 1A\r\nLocally Private Hypothesis Selection<\/strong><\/a>\r\nSivakanth Gopi<\/a>, Gautam Kamath, Janardhan D Kulkarni<\/a>, Aleksandar Nikolov, Steven Wu, Huanyu Zhang\r\n\r\n10:00 AM \u2013 12:30 PM PDT | Session 1B\r\nFrom Tree Matching to Sparse Graph Alignment<\/strong><\/a>\r\nLuca Ganassali, Laurent Massoulie\r\n\r\n10:00 AM \u2013 12:30 PM PDT | Session 1B\r\nOptimality and Approximation with Policy Gradient Methods in Markov Decision Processes<\/strong><\/a>\r\nAlekh Agarwal<\/a>, Sham Kakade, Jason Lee, Gaurav Mahajan\r\n\r\nFriday, July 10<\/strong>\r\n\r\n10:00 AM \u2013 12:30 PM PDT | Session 2B\r\nHow to Trap a Gradient Flow<\/strong><\/a>\r\nDan Mikulincer, S\u00e9bastien Bubeck<\/a>\r\n\r\n5:00 PM \u2013 7:00 PM PDT | Session 2C\r\nModel-Based Reinforcement Learning with a Generative Model is Minimax Optimal<\/strong><\/a>\r\nAlekh Agarwal<\/a>, Sham Kakade, Lin Yang\r\n\r\nSaturday, July 11<\/strong>\r\n\r\n5:30 AM \u2013 8:00 AM PDT | Session 3A\r\nEstimation and Inference with Trees and Forests in High Dimensions<\/strong>\r\nVasilis Syrgkanis<\/a>, Emmanouil Zampetakis\r\n\r\n10:00 AM \u2013 12:30 PM PDT | Session 3B\r\nCoordination Without Communication: Optimal Regret in Two Players Multi-armed Bandits<\/strong><\/a>\r\nS\u00e9bastien Bubeck<\/a>, Thomas Budzinski\r\n\r\n10:00 AM \u2013 12:30 PM PDT | Session 3B\r\nGradient Descent Follows the Regularization Path for General Losses<\/strong><\/a>\r\nZiwei Ji, Miroslav Dudik<\/a>, Robert Schapire<\/a>, Matus Telgarsky\r\n\r\n10:00 AM \u2013 12:30 PM PDT | Session 3B\r\nNon-Stochastic Multi-Player Multi-Armed Bandits: Optimal Rate With Collision Information, Sublinear Without<\/strong><\/a>\r\nS\u00e9bastien Bubeck<\/a>, Yuanzhi Li, Yuval Peres, Mark Sellke\r\n\r\n10:00 AM \u2013 12:30 PM PDT | Session 3B\r\nTaking a Hint: How to Leverage Loss Predictors in Contextual Bandits?<\/strong><\/a>\r\nChen-Yu Wei, Haipeng Luo, Alekh Agarwal<\/a>"}],"msr_startdate":"2020-07-09","msr_enddate":"2020-07-12","msr_event_time":"","msr_location":"Virtual\/Online","msr_event_link":"","msr_event_recording_link":"","msr_startdate_formatted":"July 9, 2020","msr_register_text":"Watch now","msr_cta_link":"","msr_cta_text":"","msr_cta_bi_name":"","featured_image_thumbnail":null,"event_excerpt":"Microsoft is proud to be a Platinum sponsor of the Thirty-Third Annual Conference on Learning Theory (COLT).","msr_research_lab":[],"related-researchers":[],"msr_impact_theme":[],"related-academic-programs":[],"related-groups":[],"related-projects":[],"related-opportunities":[],"related-publications":[],"related-videos":[],"related-posts":[],"_links":{"self":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-event\/671130","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\/671130\/revisions"}],"predecessor-version":[{"id":1146949,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-event\/671130\/revisions\/1146949"}],"wp:attachment":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/media?parent=671130"}],"wp:term":[{"taxonomy":"msr-research-area","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/research-area?post=671130"},{"taxonomy":"msr-region","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-region?post=671130"},{"taxonomy":"msr-event-type","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-event-type?post=671130"},{"taxonomy":"msr-video-type","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-video-type?post=671130"},{"taxonomy":"msr-locale","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-locale?post=671130"},{"taxonomy":"msr-program-audience","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-program-audience?post=671130"},{"taxonomy":"msr-post-option","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-post-option?post=671130"},{"taxonomy":"msr-impact-theme","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-impact-theme?post=671130"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}