Active Bibliography

1 A review of RKHS methods in machine learning – Thomas Hofmann, Bernhard Schölkopf, Alexander J. Smola - 2006
35 A Review of Kernel Methods in Machine Learning – Thomas Hofmann, Bernhard Schölkopf, Alexander J. Smola - 2006
371 An introduction to kernel-based learning algorithms – Klaus-Robert Müller, Sebastian Mika, Gunnar Rätsch, Koji Tsuda, Bernhard Schölkopf - 2001
110 An introduction to boosting and leveraging – Ron Meir, Gunnar Rätsch - 2003
Bioinformatics – Vol No Pages - 2003
41 Constructing Boosting Algorithms from SVMs: An Application to One-class Classification – Gunnar Rätsch, Sebastian Mika, Bernhard Schölkopf, Klaus-Robert Müller - 2002
1 Reduction techniques for training support vector machines – Kuan-ming Lin - 2002
88 Everything Old Is New Again: A Fresh Look at Historical Approaches – Ryan Michael Rifkin - 2002
50 A unified framework for Regularization Networks and Support Vector Machines – Theodoros Evgeniou, Massimiliano Pontil - 1999
266 Regularization networks and support vector machines – Theodoros Evgeniou, Massimiliano Pontil, Tomaso Poggio - 2000
4 Kernel Methods for Unsupervised Learning – Francesco Camastra - 2004
Bayesian Approach To Support Vector Machines – Chu Wei - 2003
7 An Information Theoretic Approach to Machine Learning – Robert Jenssen - 2005
108 The analysis of decomposition methods for support vector machines – Chih-jen Lin, Nello Cristianini - 1999
175 Multicategory Support Vector Machines, theory, and application to the classification of microarray data and satellite radiance data – Yoonkyung Lee, Yi Lin, Grace Wahba - 2004
90 Training a support vector machine in the primal – Olivier Chapelle - 2007
2 Kernel Methods for Text-Independent Speaker Verification – Chris Longworth - 2010
68 Online Bayes Point Machines – Edward Harrington, Ralf Herbrich, Jyrki Kivinen, John C. Platt, Robert C. Williamson
21 New methods for splice site recognition – S. Sonnenburg, G. Rätsch, A. Jagota, K.-R. Müller - 2002