https://wiki.devclub.in/index.php?action=history&feed=atom&title=ELL709 2026-04-09T10:55:11Z Revision history for this page on the wiki MediaWiki 1.45.1 https://wiki.devclub.in/index.php?title=ELL709&diff=802&oldid=prev 2026-03-04T10:03:04Z

<p>Creating course page via bot</p> <p><b>New page</b></p><div>{{Infobox Course<br /> | code = ELL709<br /> | name = Online prediction, Optimization, and Learning<br /> | credits = 3<br /> | credit_structure = 3-0-0<br /> | pre_requisites = (MTL106 or ELL711) and ELL706<br /> | overlaps = <br /> }}<br /> <br /> == ELL709 : Online prediction, Optimization, and Learning ==<br /> Online prediction: Majority and weighted majority algorithms, mistake bound; learning with expert advice-exponential weighted average forecaster, convex loss; non-convex loss, randomization; regret bounds; applications to electrical engineering. Online convex optimization (OCO): Follow the leader (FTL), regularised FTL (FTRL), Online gradient descent (OGD), stochastic gradient descent (SGD), online mirror descent (OMD), regret bounds; applications to electrical engineering. Multi-armed bandit (MAB): Stochastic MAB, UCB algorithm, asymptotic and minimax optimality, KL-UCB algorithm; Adversarial bandits, Exp3 and Exp3-IX algorithms; Contextual and linear bandits; regret analysis; lower bounds; best arm identification with high probability; Bayesian bandit- Thompson sampling, Gittin&#039;s index; Restless bandits, Whittle&#039;s index; combinatorial and nonstationary bandits; ranking; applications to electrical engineering.</div>

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