Bernhard Schölkopf

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Alex SmolaBoson AIEmail confirmado em smola.org
Klaus-Robert MüllerGoogle DeepMind & TU Berlin & Korea University & Max Planck Institute for Informatics, GermanyEmail confirmado em tu-berlin.de
Gunnar RätschProfessor, ETH ZürichEmail confirmado em inf.ethz.ch
Arthur GrettonGatsby Computational Neuroscience Unit and Google DeepmindEmail confirmado em gatsby.ucl.ac.uk
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Jonas PetersProfessor of Statistics, ETH ZurichEmail confirmado em stat.math.ethz.ch
Robert C. WilliamsonUniversity of TübingenEmail confirmado em uni-tuebingen.de
Kun ZhangCarnegie Mellon University & Mohamed bin Zayed University of Artificial Intelligence (MBZUAI)Email confirmado em cmu.edu
Francesco LocatelloAssistant Professor, ISTAEmail confirmado em ista.ac.at
Michael HirschMax Planck Institute for Intelligent Systems TübingenEmail confirmado em tuebingen.mpg.de
Moritz Grosse-WentrupUniversity of ViennaEmail confirmado em univie.ac.at
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Karsten BorgwardtDirector, Max Planck Institute of BiochemistryEmail confirmado em biochem.mpg.de
Jeremy HillNational Center for Adaptive Neurotechnologies; Stratton VA Medical Center, Albany, NY, USAEmail confirmado em med.cornell.edu

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Bernhard Schölkopf

Director, Max Planck Institute for Intelligent Systems & ELLIS Institute Tübingen; Professor at ETH

Email confirmado em tuebingen.mpg.de

Machine Learning Causal Inference Artificial Intelligence Computational Photography Statistics


Título Ordenar por citações Ordenar por ano Ordenar por título	Citado por Citado por	Ano
Learning with kernels: support vector machines, regularization, optimization, and beyond B Schölkopf, AJ Smola MIT press, 2002	24734*	2002
A tutorial on support vector regression AJ Smola, B Schölkopf Statistics and computing 14, 199-222, 2004	15542	2004
Nonlinear component analysis as a kernel eigenvalue problem B Schölkopf, A Smola, KR Müller Neural computation 10 (5), 1299-1319, 1998	11056	1998
Semi-supervised learning O Chapelle, B Schölkopf, A Zien MIT Press, 2006	7919*	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	7443	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	6466	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	5873	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	5533	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	5025*	2001
Advances in kernel methods: support vector learning B Schölkopf, A Burges, C.J.C.: Smola The MIT press, 1999	4442*	1999
Fisher discriminant analysis with kernels S Mika, G Rätsch, J Weston, B Schölkopf, K Müller Neural networks for signal processing IX, 1999	4239	1999
Kernel principal component analysis B Schölkopf, A Smola, KR Müller International conference on artificial neural networks, 583-588, 1997	3747	1997
New support vector algorithms B Schölkopf, AJ Smola, RC Williamson, PL Bartlett Neural computation 12 (5), 1207-1245, 2000	3574	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	3113	1999
Kernel methods in machine learning T Hofmann, B Schölkopf, AJ Smola Annals of Statistics 36 (3), 1171-1220, 2008	2918	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	2809	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	2685	2006
A generalized representer theorem B Schölkopf, R Herbrich, AJ Smola International conference on computational learning theory, 416-426, 2001	2324	2001
Elements of causal inference: foundations and learning algorithms J Peters, D Janzing, B Schölkopf The MIT Press, 2017	2224	2017
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	2197	2006

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