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Chapelle O, Vapnik V, Bousquet O, Mukherjee S (2002) Choosing multiple parameters for support vector machines Machine Learning 46:131-159Cristianini N, Shawe-taylor J (2000) An introduction to support vector machinesCristianini N, Shawe-taylor J, Elisseeff A, Kandola J (2001) On kernel-target alignment Advances in neural information processing systems, Dietterich T:Becker S:Ghahramani Z, ed. pp.367Fukunaga K (1990) Introduction to statistical pattern recognition (2nd ed)Haykin S (1999) Neural Networks: A Comprehensive Foundation (2nd Ed)Herbrich R (2000) Learning linear classifiers Unpublished doctoral dissertationMicchelli CA (1986) Algebraic aspects of interpolation Proceedings Of Symposia In Applied Mathematics 36:81-102Parzen E (1962) On the estimation of a probability density function and mode Ann Math Stat 33:1064-1076Platt JC, Burges CJC, Swenson S, Weare C, Zheng A (2002) Learning a gaussian process prior for automatically generating music playlists Advances in neural information processing systems, Becker S:Thrun S:Obermayer K, ed. pp.1425ROSENBLATT F (1958) The perceptron: a probabilistic model for information storage and organization in the brain. Psychol Rev 65:386-408 [PubMed]Scholkopf B, Smola AJ (2001) Learning with kernels: Support vector machines, regularization, optimization, and beyondUCI (2003) Machine Learning Repository Available online: www.ics.uci.edu-mlearn-MLRepository.htmlVapnik V (1995) The Nature of Statistical Learning TheoryVapnik V, Chervonenkis A (1968) Uniform convergence of frequencies of occurrence of events to their probabilities Dokl Akad Nauk SSSR 181:915-918Vapnik V, Lerner A (1963) Pattern recognition using generalized portrait method Automation And Remote Control 24:774-780Vapnik VN, Chervonenkis AY (1971) On the uniform convergence of relative frequencies of events to their probabilities Theory Of Probability And Its Applications 16:264-280Wang L, Chan KL (2002) Learning kernel parameters by using class separability measure Paper presented at the NIPS kernel workshop, Whistler, Canada |