Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond

by Bernhard Schölkopf and Alexander J. Smola

Book Overview

A comprehensive introduction to Support Vector Machines and related kernel methods. In the 1990s, a new type of learning algorithm was developed, based on results from statistical learning theory: the Support Vector Machine (SVM). This gave rise to a new class of theoretically elegant learning machines that use a central concept of SVMs---kernels--for a number of learning tasks. Kernel machines provide a modular framework that can be adapted to different...

• Format: Hardcover
• Language: English
• ISBN: 0262194759
• ISBN13: 9780262194754
• Release Date: December 2001
• Publisher: MIT Press
• Length: 648 Pages
• Weight: 0.35 lbs.
• Dimensions: 1.4" x 8.2" x 10.2"
• Age Range: 18 years and up
• Grade Range: Postsecondary and higher