Active Bibliography

473 A tutorial on support vector regression – Alex J. Smola, Bernhard Schölkopf - 2004
1 A review of RKHS methods in machine learning – Thomas Hofmann, Bernhard Schölkopf, Alexander J. Smola - 2006
10 A short introduction to learning with kernels – Bernhard Schölkopf, Alexander J. Smola - 2002
373 An introduction to kernel-based learning algorithms – Klaus-Robert Müller, Sebastian Mika, Gunnar Rätsch, Koji Tsuda, Bernhard Schölkopf - 2001
24 Statistical Learning and Kernel Methods – Bernhard Schölkopf - 2000
12 Statistical Learning and Kernel Methods in Bioinformatics – Bernhard Schölkopf, Isabelle Guyon, Jason Weston - 2000
177 Kernel principal component analysis – Bernhard Scholkopf, Alexander Smola, Klaus-Robert Müller - 1999
125 Comparing Support Vector Machines with Gaussian Kernels to Radial Basis Function Classifiers – Bernhard Schölkopf, K. Sung, C. Burges, F. Girosi, P. Niyogi, T. Poggio, V. Vapnik - 1997
• Similarity, kernels, feature spaces • Positive definite kernels and their RKHS – Bernhard Schölkopf, Kernel Means, Representer Theorem, Training Set (x
77 On a Kernel-based Method for Pattern Recognition, Regression, Approximation, and Operator Inversion – Alex J. Smola, Bernhard Schölkopf - 1997
Produced as part of the ESPRIT Working Group in Neural and Computational Learning II, – Robert C. Williamson, Anu Alex, J. Smola, Bernhard Scholkopf - 1998
10 Support Vector Methods in Learning and Feature Extraction – Bernhard Schölkopf, Alex Smola, Klaus-Robert Müller, Chris Burges, Vladimir Vapnik - 1998
88 Input Space Versus Feature Space in Kernel-Based Methods – Bernhard Schölkopf, Sebastian Mika, Chris J. C. Burges, Philipp Knirsch, Klaus-Robert Müller, Gunnar Rätsch, Alexander J. Smola - 1999
146 The Connection between Regularization Operators and Support Vector Kernels – Alex J. Smola, Bernhard Schölkopf, Klaus-Robert Müller - 1998
Contributed article The connection between regularization operators and support vector kernels – Alex J. Smola, Bernhard Schölkopf, Klaus-robert Müller - 1997
2272 A tutorial on support vector machines for pattern recognition – Christopher J. C. Burges - 1998
144 Support Vector Machines for Multi-Class Pattern Recognition – J. Weston, C. Watkins - 1999
5 Mathematical Programming Approaches To Machine Learning And Data Mining – Paul S. Bradley - 1998
216 Generalized Discriminant Analysis Using a Kernel Approach – G. Baudat, F. Anouar - 2000