Book contents
- Frontmatter
- Contents
- Preface
- Notation
- Part I Bandits, Probability and Concentration
- Part II Stochastic Bandits with Finitely Many Arms
- Part III Adversarial Bandits with Finitely Many Arms
- Part IV Lower Bounds for Bandits with Finitely Many Arms
- Part V Contextual and Linear Bandits
- 18 Contextual Bandits
- 19 Stochastic Linear Bandits
- 20 Confidence Bounds for Least Squares Estimators
- 21 Optimal Design for Least Squares Estimators
- 22 Stochastic Linear Bandits with Finitely Many Arms
- 23 Stochastic Linear Bandits with Sparsity
- 24 Minimax Lower Bounds for Stochastic Linear Bandits
- 25 Asymptotic Lower Bounds for Stochastic Linear Bandits
- Part VI Adversarial Linear Bandits
- Part VII Other Topics
- Part VIII Beyond Bandits
- Bibliography
- Index
24 - Minimax Lower Bounds for Stochastic Linear Bandits
from Part V - Contextual and Linear Bandits
Published online by Cambridge University Press: 04 July 2020
Book contents
- Frontmatter
- Contents
- Preface
- Notation
- Part I Bandits, Probability and Concentration
- Part II Stochastic Bandits with Finitely Many Arms
- Part III Adversarial Bandits with Finitely Many Arms
- Part IV Lower Bounds for Bandits with Finitely Many Arms
- Part V Contextual and Linear Bandits
- 18 Contextual Bandits
- 19 Stochastic Linear Bandits
- 20 Confidence Bounds for Least Squares Estimators
- 21 Optimal Design for Least Squares Estimators
- 22 Stochastic Linear Bandits with Finitely Many Arms
- 23 Stochastic Linear Bandits with Sparsity
- 24 Minimax Lower Bounds for Stochastic Linear Bandits
- 25 Asymptotic Lower Bounds for Stochastic Linear Bandits
- Part VI Adversarial Linear Bandits
- Part VII Other Topics
- Part VIII Beyond Bandits
- Bibliography
- Index
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- Bandit Algorithms , pp. 250 - 257Publisher: Cambridge University PressPrint publication year: 2020