Book contents
- Frontmatter
- Contents
- Preface
- 1 Introduction
- 2 Basic Probability Inequalities for Sums of Independent Random Variables
- 3 Uniform Convergence and Generalization Analysis
- 4 Empirical Covering Number Analysis and Symmetrization
- 5 Covering Number Estimates
- 6 Rademacher Complexity and Concentration Inequalities
- 7 Algorithmic Stability Analysis
- 8 Model Selection
- 9 Analysis of Kernel Methods
- 10 Additive and Sparse Models
- 11 Analysis of Neural Networks
- 12 Lower Bounds and Minimax Analysis
- 13 Probability Inequalities for Sequential Random Variables
- 14 Basic Concepts of Online Learning
- 15 Online Aggregation and Second-Order Algorithms
- 16 Multiarmed Bandits
- 17 Contextual Bandits
- 18 Reinforcement Learning
- Appendix A Basics of Convex Analysis
- Appendix B f-divergence of Probability Measures
- References
- Author Index
- Subject Index
Appendix A - Basics of Convex Analysis
Published online by Cambridge University Press: 20 July 2023
Book contents
- Frontmatter
- Contents
- Preface
- 1 Introduction
- 2 Basic Probability Inequalities for Sums of Independent Random Variables
- 3 Uniform Convergence and Generalization Analysis
- 4 Empirical Covering Number Analysis and Symmetrization
- 5 Covering Number Estimates
- 6 Rademacher Complexity and Concentration Inequalities
- 7 Algorithmic Stability Analysis
- 8 Model Selection
- 9 Analysis of Kernel Methods
- 10 Additive and Sparse Models
- 11 Analysis of Neural Networks
- 12 Lower Bounds and Minimax Analysis
- 13 Probability Inequalities for Sequential Random Variables
- 14 Basic Concepts of Online Learning
- 15 Online Aggregation and Second-Order Algorithms
- 16 Multiarmed Bandits
- 17 Contextual Bandits
- 18 Reinforcement Learning
- Appendix A Basics of Convex Analysis
- Appendix B f-divergence of Probability Measures
- References
- Author Index
- Subject Index
Summary
A summary is not available for this content so a preview has been provided. Please use the Get access link above for information on how to access this content.
- Type
- Chapter
- Information
- Mathematical Analysis of Machine Learning Algorithms , pp. 414 - 419Publisher: Cambridge University PressPrint publication year: 2023