Book contents
- Frontmatter
- Dedication
- Contents
- Preface
- Notation
- Part One Machine Learning
- Part Two Optimal Recovery
- Part Three Compressive Sensing
- Part Four Optimization
- Part Five Neural Networks
- Appendices
- Appendix A High-Dimensional Geometry
- Appendix B Probability Theory
- Appendix C Functional Analysis
- Appendix D Matrix Analysis
- Appendix E Approximation Theory
- References
- Index
Appendix C - Functional Analysis
from Appendices
Published online by Cambridge University Press: 21 April 2022
Book contents
- Frontmatter
- Dedication
- Contents
- Preface
- Notation
- Part One Machine Learning
- Part Two Optimal Recovery
- Part Three Compressive Sensing
- Part Four Optimization
- Part Five Neural Networks
- Appendices
- Appendix A High-Dimensional Geometry
- Appendix B Probability Theory
- Appendix C Functional Analysis
- Appendix D Matrix Analysis
- Appendix E Approximation Theory
- References
- Index
Summary
This appendix states and proves several important results about completeness, convexity, and extreme points. These results, including the supporting hyperplane theorem and the Hahn–Banach extension theorem, are invoked throughout the text.
- Type
- Chapter
- Information
- Mathematical Pictures at a Data Science Exhibition , pp. 274 - 284Publisher: Cambridge University PressPrint publication year: 2022