Bernhard Schölkopf - Google Scholar

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Alex SmolaAmazon Web ServicesVerified email at smola.org
Gunnar RätschProfessor, ETH ZürichVerified email at inf.ethz.ch
Klaus-Robert MüllerGoogle Brain (on leave of Professor for Machine Learning, TU Berlin & Korea University, Seoul)Verified email at tu-berlin.de
arthur grettonGatsby Computational Neuroscience Unit, UCLVerified email at gatsby.ucl.ac.uk
John C. PlattGoogleVerified email at google.com
Dominik JanzingAmazon Development Center, TuebingenVerified email at tuebingen.mpg.de
Jason WestonFacebookVerified email at fb.com
Olivier ChapelleGoogleVerified email at chapelle.cc
Sebastian MikacomtravoVerified email at comtravo.com
Robert C. WilliamsonProfessor of Computer Science, Australian National University; Distinguished Researcher, DATA61Verified email at anu.edu.au
Peter BartlettProfessor, EECS and Statistics, UC BerkeleyVerified email at cs.berkeley.edu
Koji TsudaProfessor, GSFS, The University of TokyoVerified email at k.u-tokyo.ac.jp
Moritz Grosse-WentrupUniversity of ViennaVerified email at univie.ac.at
Olivier BousquetGoogleVerified email at m4x.org
Michael HirschMax Planck Institute for Intelligent Systems TübingenVerified email at tuebingen.mpg.de
Jonas PetersProfessor of Statistics, University of CopenhagenVerified email at math.ku.dk
Jeremy HillResearch Scientist, Burke Neurological Institute and Blythedale Children's HospitalVerified email at med.cornell.edu
Karsten BorgwardtProfessor of Machine Learning in the Life Sciences at ETH ZurichVerified email at bsse.ethz.ch
Kun ZhangCarnegie Mellon University & Max-Planck Institute for Intelligent SystemsVerified email at cmu.edu
Kenji FukumizuThe Institute of Statistical MathematicsVerified email at ism.ac.jp

Bernhard Schölkopf

Director, Max Planck Institute for Intelligent Systems; Professor at ETH Zürich, and Distinguished

Verified email at tuebingen.mpg.de

Machine Learning Causal Inference Artificial Intelligence Computational Photography Statistics


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Learning with kernels: support vector machines, regularization, optimization, and beyond B Schölkopf, AJ Smola, F Bach MIT press, 2002	19093*	2002
A tutorial on support vector regression AJ Smola, B Schölkopf Statistics and computing 14 (3), 199-222, 2004	10071	2004
Nonlinear component analysis as a kernel eigenvalue problem B Schölkopf, A Smola, KR Müller Neural computation 10 (5), 1299-1319, 1998	8832	1998
Making large-scale SVM learning practical T Joachims Technical Report, 1998	7384	1998
Semi-supervised learning O Chapelle, B Schölkopf, A Zien MIT Press, 2006	5205*	2006
Semi-Supervised Learning (Chapelle, O. et al., Eds.; 2006) [Book reviews] O Chapelle, B Scholkopf, A Zien IEEE Transactions on Neural Networks 20 (3), 542-542, 2009	5182	2009
Semi-Supervised Learning (Chapelle, O. et al., Eds.; 2006) [Book reviews] O Chapelle, B Scholkopf, A Zien IEEE Transactions on Neural Networks 20 (3), 542-542, 2009	5182	2009
Estimating the support of a high-dimensional distribution B Scholkopf, JC Platt, J Shawe-Taylor, AJ Smola, RC Williamson	4758	1999
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	4745	2001
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	4288	2001
Learning with local and global consistency D Zhou, O Bousquet, TN Lal, J Weston, B Schölkopf Advances in neural information processing systems, 321-328, 2004	3893	2004
Fisher discriminant analysis with kernels S Mika, G Rätsch, J Weston, B Schölkopf, K Müller Neural networks for signal processing IX, 1999	3226	1999
New support vector algorithms B Schölkopf, AJ Smola, RC Williamson, PL Bartlett Neural computation 12 (5), 1207-1245, 2000	2994	2000
Support vector machines MA Hearst, ST Dumais, E Osuna, J Platt, B Scholkopf IEEE Intelligent Systems and their applications 13 (4), 18-28, 1998	2921	1998
Advances in kernel methods support vector learning B Schèolkopf, CJC Burges, AJ Smola Cambridge, Mass., MIT Press, 1999	2459*	1999
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	2402	2005
Advances in kernel methods: support vector learning B Schölkopf, A Burges, C.J.C.: Smola The MIT press, 1999	2379*	1999
Kernel principal component analysis B Schölkopf, A Smola, KR Müller International conference on artificial neural networks, 583-588, 1997	2286	1997
Principal manifolds and nonlinear dimensionality reduction via tangent space alignment Z Zhang, H Zha SIAM journal on scientific computing 26 (1), 313-338, 2004	2021	2004
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	1695	2012

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