Advances In Kernel Methods: Support Vector Learning
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Google books | books.google.com |
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Originally published | 1999 |
Editors | Christopher J. C. Burges |
Bernhard Schölkopf | |
Date of Reg. | |
Date of Upd. | |
ID | 2210615 |
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. . . .