Learning with kernels: support vector machines, regularization, optimization, and beyond B Schölkopf, AJ Smola MIT press, 2002 | 24427* | 2002 |
A tutorial on support vector regression AJ Smola, B Schölkopf Statistics and computing 14, 199-222, 2004 | 15319 | 2004 |
Nonlinear component analysis as a kernel eigenvalue problem B Schölkopf, A Smola, KR Müller Neural computation 10 (5), 1299-1319, 1998 | 10999 | 1998 |
Semi-supervised learning O Chapelle, B Schölkopf, A Zien MIT Press, 2006 | 7855* | 2006 |
Estimating the support of a high-dimensional distribution B Schölkopf, JC Platt, J Shawe-Taylor, AJ Smola, RC Williamson Neural computation 13 (7), 1443-1471, 2001 | 7339 | 2001 |
Support vector machines MA Hearst, ST Dumais, E Osuna, J Platt, B Scholkopf IEEE Intelligent Systems and their applications 13 (4), 18-28, 1998 | 6243 | 1998 |
A kernel two-sample test A Gretton, KM Borgwardt, MJ Rasch, B Schölkopf, A Smola The Journal of Machine Learning Research 13 (1), 723-773, 2012 | 5688 | 2012 |
Learning with local and global consistency D Zhou, O Bousquet, T Lal, J Weston, B Schölkopf Advances in neural information processing systems 16, 2003 | 5472 | 2003 |
An introduction to kernel-based learning algorithms KR Muller, S Mika, G Ratsch, K Tsuda, B Scholkopf IEEE Transactions on Neural Networks 12 (2), 181-201, 2001 | 5005* | 2001 |
Advances in kernel methods: support vector learning B Schölkopf, A Burges, C.J.C.: Smola The MIT press, 1999 | 4429* | 1999 |
Fisher discriminant analysis with kernels S Mika, G Rätsch, J Weston, B Schölkopf, K Müller Neural networks for signal processing IX, 1999 | 4224 | 1999 |
Kernel principal component analysis B Schölkopf, A Smola, KR Müller International conference on artificial neural networks, 583-588, 1997 | 3717 | 1997 |
New support vector algorithms B Schölkopf, AJ Smola, RC Williamson, PL Bartlett Neural computation 12 (5), 1207-1245, 2000 | 3551 | 2000 |
Support vector method for novelty detection B Schölkopf, RC Williamson, A Smola, J Shawe-Taylor, J Platt Advances in neural information processing systems 12, 1999 | 3045 | 1999 |
Kernel methods in machine learning T Hofmann, B Schölkopf, AJ Smola Annals of Statistics 36 (3), 1171-1220, 2008 | 2883 | 2008 |
A gene expression map of Arabidopsis thaliana development M Schmid, TS Davison, SR Henz, UJ Pape, M Demar, M Vingron, ... Nature genetics 37 (5), 501-506, 2005 | 2792 | 2005 |
A kernel method for the two-sample-problem A Gretton, K Borgwardt, M Rasch, B Schölkopf, A Smola Advances in neural information processing systems 19, 2006 | 2636 | 2006 |
A generalized representer theorem B Schölkopf, R Herbrich, AJ Smola International conference on computational learning theory, 416-426, 2001 | 2294 | 2001 |
Correcting sample selection bias by unlabeled data J Huang, A Gretton, K Borgwardt, B Schölkopf, A Smola Advances in neural information processing systems 19, 2006 | 2160 | 2006 |
Elements of causal inference: foundations and learning algorithms J Peters, D Janzing, B Schölkopf The MIT Press, 2017 | 2149 | 2017 |