{"id":7330,"date":"2023-01-03T12:20:04","date_gmt":"2023-01-03T06:50:04","guid":{"rendered":"https:\/\/www.ee.iitb.ac.in\/web?post_type=course_lists&#038;p=7330"},"modified":"2023-02-17T12:21:06","modified_gmt":"2023-02-17T06:51:06","slug":"ee-6106-online-learning-and-optimisation","status":"publish","type":"course_lists","link":"https:\/\/www.ee.iitb.ac.in\/web\/course_lists\/ee-6106-online-learning-and-optimisation\/","title":{"rendered":"EE 6106 &#8211; Online Learning and Optimisation"},"content":{"rendered":"\n<p>The course will primarily be on online learning in a stochastic environment. The emphasis will be on proving formal performance guarantees of algorithms, and also fundamental limits on the performance of any algorithm.<\/p>\n\n\n\nThe first half of the course will focus on variants of the multi-armed bandit problem:<br>\n<ul>\n    <li>Regret minimization: algorithms and information theoretic lower bounds<\/li>\n    <li>Pure exploration: fixed budget and fixed confidence<\/li>\n    <li>Linear bandits, contextual bandits, Bayesian bandits (Thompson sampling)<\/li>\n<\/ul>\nThe second half of the course will focus on learning in the context of Markov decision processes (MDPs):\n<ul>\n<li>Background on MDPs<\/li>\n<li>Markovian bandits (rested and restless); Gittins and Whittle index<\/li>\n<li>Reinforcement learning<\/li>\n<\/ul>\nEvaluation will be based on home works, exam and a research project. <br> <br>\n\n\n\n<strong>Text\/References<\/strong>\n<ol>\n    <li>T. Lattimore and C. Szepesv\u00e1ri, \u201cBandit Algorithms,\u201d Available at http:\/\/tor-lattimore.com\/downloads\/book\/book.pdf.<\/li>\n    <li>Alexandre Slivkins, \u201cIntroduction to Multi-Armed Bandits,\u201d NOW Publishers, 2019<\/li>\n    <li>D. Russo, et al, \u201cA Tutorial on Thompson Sampling,\u201d NOW Publishers, 2018. <\/li>\n    <li>S. Shalev-Schwartz, \u201cOnline Learning and Online Convex Optimization,\u201d NOW Publishers 2011. <\/li>\n    <li>Contemporary research papers<\/li>\n<\/ol>\n","protected":false},"featured_media":0,"parent":0,"template":"","meta":{"site-sidebar-layout":"default","site-content-layout":"default","ast-global-header-display":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"","ast-breadcrumbs-content":"","ast-featured-img":"","footer-sml-layout":"","theme-transparent-header-meta":"","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":""},"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v19.8 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>EE 6106 - Online Learning and Optimisation &ndash; EE IIT Bombay<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.ee.iitb.ac.in\/webcourse_lists\/ee-6106-online-learning-and-optimisation\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"EE 6106 - Online Learning and Optimisation &ndash; EE IIT Bombay\" \/>\n<meta property=\"og:description\" content=\"The course will primarily be on online learning in a stochastic environment. The emphasis will be on proving formal performance guarantees of algorithms, and also fundamental limits on the performance of any algorithm. 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