Advances in Kernel Methods

Description:

The Support Vector Machine is a powerful new learning algorithm for solving a variety of learning and function estimation problems, such as pattern recognition, regression estimation, and operator inversion. The impetus for this collection was a workshop on Support Vector Machines held at the 1997 NIPS conference. The contributors, both university researchers and engineers developing applications for the corporate world, form a Who's Who of this exciting new area.

subjects: Algorithms,  Kernel functions,  Machine learning,  Vector analysis,  Apprentissage automatique,  Algorithmes,  Noyaux (Mathématiques),  COMPUTERS,  Enterprise Applications,  Business Intelligence Tools,  Intelligence (AI) & Semantics,  Kunstmatige intelligentie,  Algoritmen,  Patroonherkenning,  Functies (wiskunde),  Machine-learning,  Fiction,  Chinese Americans,  Juvenile fiction,  Brothers,  Railroads,  Central Pacific Railroad Company