Contents Overview

See detailed contents list »

Part One: Basic Concepts

  1. Pattern Analysis
  2. Kernel Methods: an Overview
  3. Properties of Kernels
  4. Detecting Stable Patterns

Part Two: Pattern Analysis Algorithms

  1. Elementary Algorithms in feature Space
  2. Pattern Analysis Using Eigen Decompositions
  3. Pattern Analysis Using Convex Optimisation
  4. Ranking, Clustering and Data Visualisation

Part Three: Constructing Kernels

  1. Basic Kernels and Kernel Types
  2. Kernels for Text
  3. Kernels for Structured Data: Strings, Trees and beyond
  4. Kernels from Generative Models

Part Four: Appendices

  • A1 – Proofs Omitted from the Main Text
  • A2 – Notational Conventions
  • A3 – List of Pattern Analysis Methods
  • A4 – List of Kernels
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