Support Vector Machines: Theory and Applications

Chapter 1 Support Vector Machines – An Introduction

Chapter 2 Multiple Model Estimation for Nonlinear Classification

Chapter 3 Componentwise Least Squares Support Vector Machines

Chapter 4 Active Support Vector Learning with Statistical Queries

Chapter 5 Local Learning vs. Global Learning: An Introduction to Maxi-Min Margin Machine

Chapter 6 Active-Set Methods for Support Vector Machines

Chapter 7 Theoretical and Practical Model Selection Methods for Support Vector Classifiers

Chapter 8 Adaptive Discriminant and Quasiconformal Kernel Nearest Neighbor Classification

Chapter 9 Improving the Performance of the Support Vector Machine: Two Geometrical Scaling Methods

Chapter 10 An Accelerated Robust Support Vector Machine Algorithm

Chapter 11 Fuzzy Support Vector Machines with Automatic Membership Setting

Chapter 12 Iterative Single Data Algorithm for Training Kernel Machines from Huge Data Sets: Theory and Performance

Chapter 13 Kernel Discriminant Learning with Application to Face Recognition

Chapter 14 Fast Color Texture-Based Object Detection in Images: Application to License Plate Localization

Chapter 15 Support Vector Machines for Signal Processing

Chapter 16 Cancer Diagnosis and Protein Secondary Structure Prediction Using Support Vector Machines

Chapter 17 Gas Sensing Using Support Vector Machines

Chapter 18 Application of Support Vector Machines in Inverse Problems in Ocean Color Remote Sensing

Chapter 19 Application of Support Vector Machine to the Detection of Delayed Gastric Emptying from Electrogastrograms

Chapter 20 Tachycardia Discrimination in Implantable Cardioverter Defibrillators Using Support Vector Machines and Bootstrap Resampling