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
- 13 Lower Bounds: Basic Ideas
- 14 Foundations of Information Theory
- 15 Minimax Lower Bounds
- 16 Instance-Dependent Lower Bounds
- 17 High-Probability Lower Bounds
- Part V Contextual and Linear Bandits
- Part VI Adversarial Linear Bandits
- Part VII Other Topics
- Part VIII Beyond Bandits
- Bibliography
- Index
15 - Minimax Lower Bounds
from Part IV - Lower Bounds for Bandits with Finitely Many Arms
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
- 13 Lower Bounds: Basic Ideas
- 14 Foundations of Information Theory
- 15 Minimax Lower Bounds
- 16 Instance-Dependent Lower Bounds
- 17 High-Probability Lower Bounds
- Part V Contextual and Linear Bandits
- Part VI Adversarial Linear Bandits
- Part VII Other Topics
- Part VIII Beyond Bandits
- Bibliography
- Index
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- Bandit Algorithms , pp. 170 - 176Publisher: Cambridge University PressPrint publication year: 2020