Fall 2021 (Aug-Dec)
Online Prediction and Learning
Course No.: E1 245
Instructor: Aditya Gopalan, ECE 2.09, Dept. of ECE, E-mail: first-name AT iisc.ac.in
Time: TTh 11:30-13:00 (First meeting to discuss course logistics on Tue 3 Aug 2021)
Place: Online on Microsoft
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Course Description: The ability to make continual and accurate forecasts and decisions under uncertainty is key in many of today’s data-driven intelligent systems (think Internet recommendation engines, automated trading, resource allocation, etc.). This elective course exposes students to common approaches in sequential learning and optimization under uncertainty. We will explore several frameworks and algorithms for online and reinforcement learning, aiming to develop a rigorous understanding. We will also look at applications of these techniques, such as portfolio optimization (finance), sequential data compression (information theory), etc.
Contents: (subject to change) Learning with expert advice, Online convex optimization, Multi-armed bandits, Low-regret reinforcement learning
Prerequisites: A basic course in probability or random processes. Exposure to convexity (convex geometry, convex analysis or convex optimization) will be helpful but is not absolutely necessary. Contact the instructor for clarifications.
Last updated: 12-Feb-2024, 11:46:37 IST