Advances in Kernel Methods: Support Vector Learning

Advances in Kernel Methods: Support Vector Learning

Rosanna Soentpiet , Bernhard Scholkopf , Alexander J. Smola
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2014 · Inglés · Tapa blanda · 2 editions
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Descripción

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.

Detalles del libro

Formato Tapa blanda
Idioma Inglés
Publicado May 14, 2014
Editorial MIT Press (MA)
Ediciones 2 editions
ISBN-10 0585128294
ISBN-13 9780585128290
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