Support Vector Machines

Authors:

ISBN: 978-0-387-77241-7 (Print) 978-0-387-77242-4 (Online)

Table of contents (12 chapters)

  1. Front Matter

    Pages 1-14

  2. No Access

    Chapter

    Pages 1-20

    Introduction

  3. No Access

    Chapter

    Pages 21-47

    Loss Functions and Their Risks

  4. No Access

    Chapter

    Pages 48-109

    Surrogate Loss Functions (*)

  5. No Access

    Chapter

    Pages 110-163

    Kernels and Reproducing Kernel Hilbert Spaces

  6. No Access

    Chapter

    Pages 164-201

    Infinite-Sample Versions of Support VectorMachines

  7. No Access

    Chapter

    Pages 202-237

    Basic Statistical Analysis of SVMs

  8. No Access

    Chapter

    Pages 238-284

    Advanced Statistical Analysis of SVMs (*)

  9. No Access

    Chapter

    Pages 285-329

    Support Vector Machines for Classification

  10. No Access

    Chapter

    Pages 330-351

    Support Vector Machines for Regression.

  11. No Access

    Chapter

    Pages 352-407

    Robustness

  12. No Access

    Chapter

    Pages 408-451

    Computational Aspects

  13. No Access

    Chapter

    Pages 452-466

    Data Mining

  14. Back Matter

    Pages 1-130