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ORCIDMachine Learning, Volume 46, 2002
Volume 46, Number 1-3, January-February-March 2002
- Nello Cristianini, Colin Campbell, Chris Burges:
Editorial: Kernel Methods: Current Research and Future Directions. 5-9 - Christopher K. I. Williams:
On a Connection between Kernel PCA and Metric Multidimensional Scaling. 11-19 - Peter Sollich
:
Bayesian Methods for Support Vector Machines: Evidence and Predictive Class Probabilities. 21-52 - Sebastian Risau-Gusman, Mirta B. Gordon:
Hierarchical Learning in Polynomial Support Vector Machines. 53-70 - Junbin Gao, Steve R. Gunn, Chris J. Harris, Martin Brown:
A Probabilistic Framework for SVM Regression and Error Bar Estimation. 71-89 - Tong Zhang:
On the Dual Formulation of Regularized Linear Systems with Convex Risks. 91-129 - Olivier Chapelle, Vladimir Vapnik, Olivier Bousquet, Sayan Mukherjee:
Choosing Multiple Parameters for Support Vector Machines. 131-159 - Dennis DeCoste, Bernhard Schölkopf:
Training Invariant Support Vector Machines. 161-190 - Yi Lin, Yoonkyung Lee, Grace Wahba:
Support Vector Machines for Classification in Nonstandard Situations. 191-202 - Theodore B. Trafalis, Alexander M. Malyscheff:
An Analytic Center Machine. 203-223 - Ayhan Demiriz, Kristin P. Bennett, John Shawe-Taylor:
Linear Programming Boosting via Column Generation. 225-254 - Olvi L. Mangasarian, David R. Musicant:
Large Scale Kernel Regression via Linear Programming. 255-269 - Gary William Flake, Steve Lawrence:
Efficient SVM Regression Training with SMO. 271-290 - Chih-Wei Hsu, Chih-Jen Lin:
A Simple Decomposition Method for Support Vector Machines. 291-314 - Pavel Laskov:
Feasible Direction Decomposition Algorithms for Training Support Vector Machines. 315-349 - S. Sathiya Keerthi, Elmer G. Gilbert:
Convergence of a Generalized SMO Algorithm for SVM Classifier Design. 351-360 - Yi Li, Philip M. Long:
The Relaxed Online Maximum Margin Algorithm. 361-387 - Isabelle Guyon, Jason Weston, Stephen Barnhill, Vladimir Vapnik:
Gene Selection for Cancer Classification using Support Vector Machines. 389-422 - Edda Leopold, Jörg Kindermann:
Text Categorization with Support Vector Machines. How to Represent Texts in Input Space? 423-444
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