Learning with kernels : support vector machines, regularization, optimization, and beyond
In the 1990s, a new type of learning algorithm was developed, based on results from statistical learning theory: the Support Vector Machine (SVM). This gave rise to a new class of theoretically elegant learning machines that use a central concept of SVMs -kernels, for a number of learning tasks. Ker...
Saved in:
Main Authors : | , |
---|---|
Format : | Book |
Language : | anglais |
Title statement : | Learning with kernels : support vector machines, regularization, optimization, and beyond / Bernhard Schölkopf, Alexander J. Smola |
Published : |
Cambridge (Mass.), London :
The MIT Press
, C 2002 |
Physical Description : | 1 vol. (XVIII-626 p.) |
Series : | Adaptative computation and machine learning series |
Subjects : |
Bib. CRDM (Mathématiques)
Location | Call Number | Loan type | Status |
---|---|---|---|
Bibliothèque | 68C478 | Prêt sans prolongation | Available |