Bayes Optimal Hyperplanes -> Maximal Margin Hyperplanes (1999)

Cached

Download Links

by Simon Tong , Daphne Koller
Venue:IJCAI'99 Workshop on Support Vector Machines (robotics.stanford.edu/~koller
Citations:3 - 0 self

Documents Related by Co-Citation

12 On the relationship between the support vector machine for classification and sparsified Fisher's linear discriminant – A. Amnon Shashua - 1999
2641 Introduction to statistical pattern recognition – K Fukunaga - 1972
256 Soft Margins for AdaBoost – Gunnar Rätsch, Takashi Onoda, Klaus-R. Müller - 1998
1048 Nonlinear component analysis as a kernel eigenvalue problem – Bernhard Schölkopf, Alexander Smola, Klaus-Robert Müller - 1996
304 Regularized discriminant analysis – Jerome H. Friedman - 1989
4786 Neural Networks for Pattern Recognition – C M Bishop - 1995
8950 The Nature of Statistical Learning Theory – Vladimir N. Vapnik - 1995
1 Comparison of full bayes and bayes-least squares criteria for normal discrimination – B Q Fang, A P Dawid - 1996
1279 A training algorithm for optimal margin classifiers – Bernhard E. Boser, et al. - 1992
2307 A Decision-Theoretic Generalization of on-Line Learning and an Application to Boosting – Yoav Freund, Robert E. Schapire - 1997
35 Principal Component Neural Networks – K I Diamantaras, S Y Kung - 1996
312 Fisher Discriminant Analysis With Kernels – Sebastian Mika, Gunnar Rätsch, Jason Weston, Bernhard Schölkopf, Klaus-Robert Müller - 1999
472 Fast learning in networks of locally-tuned processing units – J Moody, C Darken - 1989
76 Theory of reproducing kernels and its applications – S Saitoh - 1988
131 Support Vector Learning – Bernhard Schölkopf - 1997
12 Theory of Reproducing Kernels and its – S Saitoh - 1988
29 Support Vector Learning. R. Oldenbourg – B Schölkopf - 1997
639 Pattern recognition. A statistical approach – P A Devijver, J Kittler - 1982
1108 Pattern Recognition and Neural Networks – Brian D Ripley - 1996