Bernhard Schölkopf - Google Scholar Citations

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Co-authors

Alex SmolaAmazon Web ServicesVerified email at smola.org
John C. PlattGoogleVerified email at google.com
Gunnar RätschProfessor, ETH ZürichVerified email at inf.ethz.ch
Klaus-Robert MüllerProfessor for Machine Learning, TU Berlin, Germany and Korea University, Seoul, Korea and MPIIVerified email at tu-berlin.de
arthur grettonGatsby Computational Neuroscience Unit, UCLVerified email at gatsby.ucl.ac.uk
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
Koji TsudaProfessor, GSFS, The University of TokyoVerified email at k.u-tokyo.ac.jp
Olivier BousquetGoogleVerified email at m4x.org
Moritz Grosse-WentrupUniversity of ViennaVerified email at ieee.org
Jeremy HillResearch Scientist, Burke Neurological Institute and Blythedale Children's HospitalVerified email at med.cornell.edu
Peter BartlettProfessor, EECS and Statistics, UC BerkeleyVerified email at cs.berkeley.edu
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
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
vapnikProfessor of Columbia, Fellow of NEC Labs America, Verified email at nec-labs.com

Bernhard Schölkopf

Director, Max Planck Institute for Intelligent Systems; and Distinguished Amazon Scholar

Verified email at tuebingen.mpg.de

Machine Learning Causal Inference Artificial Intelligence Computational Photography Statistics


Title	Cited by	Year
Learning with kernels: support vector machines, regularization, optimization, and beyond B Schölkopf, AJ Smola, F Bach MIT press, 2002	18590*	2002
A tutorial on support vector regression AJ Smola, B Schölkopf Statistics and computing 14 (3), 199-222, 2004	9585	2004
Nonlinear component analysis as a kernel eigenvalue problem B Schölkopf, A Smola, KR Müller Neural computation 10 (5), 1299-1319, 1998	8570	1998
Semi-supervised learning O Chapelle, B Schölkopf, A Zien MIT Press, 2006	4940*	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	4922	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	4922	2009
Estimating the support of a high-dimensional distribution B Scholkopf, JC Platt, J Shawe-Taylor, AJ Smola, RC Williamson	4543	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	4532	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	4200	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	3740	2004
Fisher discriminant analysis with kernels S Mika, G Rätsch, J Weston, B Schölkopf, K Müller Neural networks for signal processing IX, 1999	3133	1999
New support vector algorithms B Schölkopf, AJ Smola, RC Williamson, PL Bartlett Neural computation 12 (5), 1207-1245, 2000	2930	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	2704	1998
Advances in kernel methods support vector learning B Schèolkopf, CJC Burges, AJ Smola Cambridge, Mass., MIT Press, 1999	2401*	1999
Advances in kernel methods: support vector learning B Schölkopf, A Burges, C.J.C.: Smola The MIT press, 1999	2391*	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	2336	2005
Kernel principal component analysis B Schölkopf, A Smola, KR Müller International conference on artificial neural networks, 583-588, 1997	2175	1997
chapter Making large-Scale SVM Learning Practical T Joachims Advances in Kernel Methods: Support Vector Learning 11, 1999	1572	1999
Large scale multiple kernel learning S Sonnenburg, G Rätsch, C Schäfer, B Schölkopf Journal of Machine Learning Research 7 (Jul), 1531-1565, 2006	1539	2006
Input space versus feature space in kernel-based methods B Schölkopf, S Mika, CJC Burges, P Knirsch, KR Müller, G Rätsch, ... IEEE transactions on neural networks 10 (5), 1000-1017, 1999	1469	1999

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