Preface

Part I. Basic Concepts

1. Pattern analysis

2. Kernel methods: an overview

3. Properties of kernels

4. Detecting stable patterns

Part II. Pattern Analysis Algorithms

5. Elementary algorithms in feature space

6. Pattern analysis using eigen-decompositions

7. Pattern analysis using convex optimisation

8. Ranking, clustering and data visualisation

Part III. Constructing Kernels

9. Basic kernels and kernel types

10. Kernels for text

11. Kernels for structured data: strings, trees, etc.

12. Kernels from generative models

Appendix A. Proofs omitted from the main text

Appendix B. Notational conventions

Appendix C. List of pattern analysis methods

Appendix D. List of kernels

References