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Advances in Kernel methods. Support vector learning. (English) Zbl 0935.68084

London: MIT Press. 392 p. (1998).
Publisher’s 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.

MSC:

68T05 Learning and adaptive systems in artificial intelligence
68-01 Introductory exposition (textbooks, tutorial papers, etc.) pertaining to computer science

Software:

MINOS
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