IE613: Online Machine Learning, Jan-April 2020Aim of this course is to study bandit algorithms and analyze their performance. Lecture HoursMonday 5.30-7pmThursday 5.30-7pm LocationOnline using MS TeamsTeaching AssistantsFehmina MalikDebamita Ghosh Hitesh Gudwani Harshit Pandey TA HoursTimings: Every Monday 2-4pmVenue : Room 201, IEOR building SyllabusIntroduction to batch learning: Empirical Rsik Minimization, PAC learning. Online learning: adversarial and stochastic settings, online learning with expert feedback, bandit feedback. Multi-Armed Bandits: Algorithms for simple and cumulative regret (expected and high probability), and their analysis. Contextual Bandits Pure exploration Course Grades20 points: Midterm35 points: 3 Assingments 15 points: Pre-project report 30 points: Final project Reference textsAssignments |