Advances in Kernel Methods: Support Vector Learning photograph

Advances In Kernel Methods: Support Vector Learning

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Originally published 1999
Editors Christopher J. C. Burges
Bernhard Schölkopf
Date of Reg.
Date of Upd.
ID2210615
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About Advances In Kernel Methods: Support Vector Learning


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. . . .

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