Book contents
- Frontmatter
- Contents
- Preface
- 1 Introduction
- Part one Pattern Classification with Binary-Output Neural Networks
- Part two Pattern Classification with Real-Output Networks
- Part three Learning Real-Valued Functions
- 16 Learning Classes of Real Functions
- 17 Uniform Convergence Results for Real Function Classes
- 18 Bounding Covering Numbers
- 19 Sample Complexity of Learning Real Function Classes
- 20 Convex Classes
- 21 Other Learning Problems
- Part four Algorithmics
- Appendix 1 Useful Results
- Bibliography
- Author index
- Subject index
17 - Uniform Convergence Results for Real Function Classes
Published online by Cambridge University Press: 26 February 2010
Book contents
- Frontmatter
- Contents
- Preface
- 1 Introduction
- Part one Pattern Classification with Binary-Output Neural Networks
- Part two Pattern Classification with Real-Output Networks
- Part three Learning Real-Valued Functions
- 16 Learning Classes of Real Functions
- 17 Uniform Convergence Results for Real Function Classes
- 18 Bounding Covering Numbers
- 19 Sample Complexity of Learning Real Function Classes
- 20 Convex Classes
- 21 Other Learning Problems
- Part four Algorithmics
- Appendix 1 Useful Results
- Bibliography
- Author index
- Subject index
- Type
- Chapter
- Information
- Neural Network LearningTheoretical Foundations, pp. 241 - 246Publisher: Cambridge University PressPrint publication year: 1999