{"id":171233,"date":"2013-10-24T16:52:27","date_gmt":"2013-10-24T16:52:27","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/project\/explore-exploit-learning\/"},"modified":"2017-08-10T13:39:37","modified_gmt":"2017-08-10T20:39:37","slug":"explore-exploit-learning","status":"publish","type":"msr-project","link":"https:\/\/www.microsoft.com\/en-us\/research\/project\/explore-exploit-learning\/","title":{"rendered":"Explore-Exploit Learning @MSR-NYC"},"content":{"rendered":"<p>This is an umbrella project for machine learning with <strong><em>explore-exploit tradeoff<\/em><\/strong>: the trade-off between acquiring and using information. This is a mature, yet very active, research area studied in Machine Learning, Theoretical Computer Science, Operations Research, and Economics. Much of our activity focuses on &#8220;multi-armed bandits&#8221; and &#8220;contextual bandits&#8221;, relatively simple and yet very powerful models for explore-exploit tradeoff.<\/p>\n<p>We are located in (or heavily collaborating with)\u00a0<a href=\"https:\/\/www.microsoft.com\/en-us\/research\/lab\/microsoft-research-new-york\/\">Microsoft Research New York City<\/a>. Most of us are involved in <a href=\"https:\/\/www.microsoft.com\/en-us\/research\/project\/multi-world-testing-mwt\/\">Multi-World Testing<\/a>: an approach & system for contextual bandit learning.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>This is an umbrella project for machine learning with explore-exploit tradeoff: the trade-off between acquiring and using information. This is a mature, yet very active, research area studied in Machine Learning, Theoretical Computer Science, Operations Research, and Economics. Much of our activity focuses on &#8220;multi-armed bandits&#8221; and &#8220;contextual bandits&#8221;, relatively simple and yet very powerful [&hellip;]<\/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":"","footnotes":""},"research-area":[13561,13556],"msr-locale":[268875],"msr-impact-theme":[],"msr-pillar":[],"class_list":["post-171233","msr-project","type-msr-project","status-publish","hentry","msr-research-area-algorithms","msr-research-area-artificial-intelligence","msr-locale-en_us","msr-archive-status-active"],"msr_project_start":"2013-10-24","related-publications":[164717,167490,238203,165787,167628,148357,238204,165791,167886,154104,246479,166357,167900,156114,383549,166359,167936,159105,166368,167963,159394,166471,168003,159585,166480,168347,162631,166519,168899,164061,166521,237177,164558,166522,238202],"related-downloads":[],"related-videos":[],"related-groups":[144902],"related-events":[],"related-opportunities":[],"related-posts":[],"related-articles":[],"tab-content":[],"slides":[],"related-researchers":[{"type":"user_nicename","display_name":"Robert Schapire","user_id":33549,"people_section":"Group 1","alias":"schapire"},{"type":"user_nicename","display_name":"Paul Mineiro","user_id":33272,"people_section":"Group 1","alias":"pmineiro"},{"type":"user_nicename","display_name":"Siddhartha Sen","user_id":33656,"people_section":"Group 1","alias":"sidsen"},{"type":"user_nicename","display_name":"Sarah Bird","user_id":33684,"people_section":"Group 1","alias":"slbird"},{"type":"user_nicename","display_name":"Alex Slivkins","user_id":33685,"people_section":"Group 1","alias":"slivkins"},{"type":"user_nicename","display_name":"Miro Dud\u00edk","user_id":32867,"people_section":"Group 1","alias":"mdudik"},{"type":"user_nicename","display_name":"John Langford","user_id":32204,"people_section":"Group 1","alias":"jcl"},{"type":"user_nicename","display_name":"Markus Cozowicz","user_id":32803,"people_section":"Group 1","alias":"marcozo"}],"msr_research_lab":[199571],"msr_impact_theme":[],"_links":{"self":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-project\/171233"}],"collection":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-project"}],"about":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/types\/msr-project"}],"version-history":[{"count":0,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-project\/171233\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/media?parent=171233"}],"wp:term":[{"taxonomy":"msr-research-area","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/research-area?post=171233"},{"taxonomy":"msr-locale","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-locale?post=171233"},{"taxonomy":"msr-impact-theme","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-impact-theme?post=171233"},{"taxonomy":"msr-pillar","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-pillar?post=171233"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}