Title: 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