This class is part of the Master 2 MVA. It will last 18 hours (3x6 lectures) + 2h for the exam.
Final grade: approximately 70% final exam, 30% homeworks (to implement some of the algorithms seen in class). A single two-sided sheet of handwritten notes (with any content) will be allowed for the exam.
Friday mornings from 9h00 to 12h00 at ENS Paris-Saclay. Information will be provided on the website before each class. Lecture notes will be updated here on the fly.
|1||13/01/2023||PG||1B18||Introduction. Sequential learning with individual sequences. Learning from expert advice.|
|2||20/01/2023||PG||1B18||Online convex optimization. Exponentiated Gradient. Online gradient descent.|
|4||03/02/2023||RD||1B18||Stochastic Bandits 1. Basic algorithms: Explore-Then-Commit, Upper Confidence Bound, \(\epsilon\)-greedy.|
|5||10/02/2023||RD||1B18||Stochastic Bandits 2. Linear and continuous bandits.|
|6||17/02/2023||RD||1B18||Stochastic Bandits 3. Lower bounds. Best arm identification.|
|17/03/2022||1B18||Exam (from 10:00 to 12:00). It will be in person at ENS Paris-Saclay.|