Brief Introduction
1. Multi-armed Bandit Framework
2. The Upper Confidence Bound (UCB) Method
3. Elementary Improvements for Both Regret Minimization and Pure Exploration Settings
4. The Law-of-Iterated-Logarithm UCB Algorithm
5. Linear Contextual Bandits
6. Generalized Linear Models and Generalized Linear Contextual Bandits
7. Dynamic Assortment Optimization and the Multilinear Logit Bandit Problem
8. (If Time Permits) Zeroth Order Convex Optimization
Time
2018-07-11 ~ 2018-08-05
Lecturers
Yuan Zhou, Indiana University Bloomington
Venue
Room 104, School of Information Management & Engineering, Shanghai University of Finance & Economics
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Program
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