- Bandits: A new beginning
- Finite-armed stochastic bandits: Warming up
- First steps: Explore-then-Commit
- The Upper Confidence Bound (UCB) Algorithm
- Optimality concepts and information theory
- More information theory and minimax lower bounds
- Instance dependent lower bounds
- Adversarial bandits
- High probability lower bounds
- Contextual bandits, prediction with expert advice and Exp4
- Stochastic Linear Bandits and UCB
- Ellipsoidal confidence sets for least-squares estimators
- Sparse linear bandits
- Lower bounds for stochastic linear bandits
- Adversarial linear bandits
- Adversarial linear bandits and the curious case of linear bandits on the unit ball
- First order bounds for k-armed adversarial bandits
- The variance of Exp3
- Bayesian/minimax duality for adversarial bandits
So we can comment on individual paragraphs. How cool is that?
Hi, is this TOC updated with the recent posts too?
Or are they meant to be read standalone?
The new posts depend on background from the previous posts, which we refer to occasionally. We’re now a little more lax and sometimes also refer to the book. The TOC should be updated from now on though.