1999 AdvancesInKernelMethods
- (Schölkopf et al., 1999) ⇒ Bernhard Schölkopf, Christopher J. C. Burges, and Alexander J. Smola. (1999). “Advances in Kernel Methods - Support Vector Learning.” In: MIT Press. ISBN:0-262-19416-3
Subject Headings: Kernel-based Algorithm.
Notes
- It contains (Joachims, 1999) ⇒ Thorsten Joachims. (1999). “Making Large-Scale SVM Learning Practical.” In: (Schölkopf et al., 1999).
Cited By
Quotes
Book Overview
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.
References
,
| Author | volume | Date Value | title | type | journal | titleUrl | doi | note | year | |
|---|---|---|---|---|---|---|---|---|---|---|
| 1999 AdvancesInKernelMethods | Bernhard Schölkopf Alexander J. Smola Christopher J. C. Burges | Advances in Kernel Methods - Support Vector Learning | http://books.google.com/books?id= NYamXKkNM8C |