Table of Contents

  1. Bandits: A new beginning
  2. Finite-armed stochastic bandits: Warming up
  3. First steps: Explore-then-Commit
  4. The Upper Confidence Bound (UCB) Algorithm
  5. Optimality concepts and information theory
  6. More information theory and minimax lower bounds
  7. Instance dependent lower bounds
  8. Adversarial bandits
  9. High probability lower bounds
  10. Contextual bandits, prediction with expert advice and Exp4
  11. Stochastic Linear Bandits and UCB
  12. Ellipsoidal confidence sets for least-squares estimators
  13. Sparse linear bandits
  14. Lower bounds for stochastic linear bandits
  15. Adversarial linear bandits
  16. Adversarial linear bandits and the curious case of linear bandits on the unit ball

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