New Support Vector Algorithms (2000)

by Bernhard Schölkopf , Alex J. Smola , Robert C. Williamson , Peter L. Bartlett
Citations:321 - 45 self

Active Bibliography

473 A tutorial on support vector regression – Alex J. Smola, Bernhard Schölkopf - 2004
2272 A tutorial on support vector machines for pattern recognition – Christopher J. C. Burges - 1998
10 Support Vector Methods in Learning and Feature Extraction – Bernhard Schölkopf, Alex Smola, Klaus-Robert Müller, Chris Burges, Vladimir Vapnik - 1998
373 An introduction to kernel-based learning algorithms – Klaus-Robert Müller, Sebastian Mika, Gunnar Rätsch, Koji Tsuda, Bernhard Schölkopf - 2001
Contributed article The connection between regularization operators and support vector kernels – Alex J. Smola, Bernhard Schölkopf, Klaus-robert Müller - 1997
146 The Connection between Regularization Operators and Support Vector Kernels – Alex J. Smola, Bernhard Schölkopf, Klaus-Robert Müller - 1998
1 A review of RKHS methods in machine learning – Thomas Hofmann, Bernhard Schölkopf, Alexander J. Smola - 2006
24 Statistical Learning and Kernel Methods – Bernhard Schölkopf - 2000
16 Regression Models for Ordinal Data: A Machine Learning Approach – Ralf Herbrich, Thore Graepel, Klaus Obermayer - 1999
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 A short introduction to learning with kernels – Bernhard Schölkopf, Alexander J. Smola - 2002
35 A Review of Kernel Methods in Machine Learning – Thomas Hofmann, Bernhard Schölkopf, Alexander J. Smola - 2006
501 Estimating the Support of a High-Dimensional Distribution – Bernhard Schölkopf, John C. Platt, John Shawe-taylor, Alex J. Smola, Robert C. Williamson - 1999
136 Training Invariant Support Vector Machines – Dennis DeCoste, Bernhard Schölkopf, Nello Cristianini - 2002
8 On a class of support vector kernels based on frames in function hilbert spaces – J. B. Gao, C. J. Harris, S. R. Gunn - 2001
15 Machine learning techniques for brain-computer interfaces – K.-R. Müller, M. Krauledat, G. Dornhege, G. Curio, B. Blankertz - 2004
6 Large margin multi-category discriminant models and scale-sensitive Ψ-dimensions – Yann Guermeur - 2006
73 Generalization Performance of Regularization Networks and Support . . . – Robert C. Williamson, Alex J. Smola, Bernhard Schölkopf - 2001
5 Mathematical Programming Approaches To Machine Learning And Data Mining – Paul S. Bradley - 1998