Alex Smola

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Bernhard SchölkopfDirector, Max Planck Institute for Intelligent Systems; Professor at ETH ZürichVerified email at tuebingen.mpg.de
Arthur GrettonGatsby Computational Neuroscience Unit and DeepmindVerified email at gatsby.ucl.ac.uk
Robert C. WilliamsonUniversity of TübingenVerified email at uni-tuebingen.de
Klaus-Robert MüllerTU Berlin & Korea University & Google Brain & Max Planck Institute for Informatics, GermanyVerified email at tu-berlin.de
S V N VishwanathanAssociate Professor of Statistics and Computer Science, Purdue UniversityVerified email at stat.purdue.edu
Amr AhmedSenior Staff Research Scientist, Google AIVerified email at google.com
Karsten BorgwardtDirector, Max Planck Institute of BiochemistryVerified email at biochem.mpg.de
Mu LiAmazonVerified email at amazon.com
Peter BartlettProfessor, EECS and Statistics, UC BerkeleyVerified email at cs.berkeley.edu
Le SongBiomap, Mohamed bin Zayed University of Artificial IntelligenceVerified email at biomap.com
Gunnar RätschProfessor, ETH ZürichVerified email at inf.ethz.ch
Quoc V. LeResearch Scientist, Google BrainVerified email at stanford.edu
John Shawe-TaylorUCLVerified email at cs.ucl.ac.uk
Sebastian MikaVerified email at sebastianmika.info
vapnikProfessor of Columbia, Fellow of NEC Labs America, Verified email at nec-labs.com
John C. PlattGoogleVerified email at google.com
Malte J RaschIBM Research AIVerified email at ibm.com
Manzil ZaheerGoogle ResearchVerified email at cmu.edu
Alexandros KaratzoglouGoogle DeepmindVerified email at google.com
Choon Hui TeoAmazonVerified email at amazon.com

Alex Smola

Boson AI

Verified email at smola.org - Homepage

Machine Learning Deep Learning Systems


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 the MIT Press, 2002	22805*	2002
A tutorial on support vector regression AJ Smola, B Schölkopf Statistics and computing 14, 199-222, 2004	13929	2004
Nonlinear component analysis as a kernel eigenvalue problem B Schölkopf, A Smola, KR Müller Neural computation 10 (5), 1299-1319, 1998	10430	1998
Support vector regression machines H Drucker, CJ Burges, L Kaufman, A Smola, V Vapnik Advances in neural information processing systems 9, 1996	5808	1996
Hierarchical attention networks for document classification Z Yang, D Yang, C Dyer, X He, A Smola, E Hovy Proceedings of the 2016 conference of the North American chapter of the …, 2016	5001	2016
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	4975	2001
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	4272	2012
Support vector method for function approximation, regression estimation and signal processing V Vapnik, S Golowich, A Smola Advances in neural information processing systems 9, 1996	3959	1996
New support vector algorithms B Schölkopf, AJ Smola, RC Williamson, PL Bartlett Neural computation 12 (5), 1207-1245, 2000	3737	2000
Kernel principal component analysis B Schölkopf, A Smola, KR Müller Artificial Neural Networks—ICANN'97: 7th International Conference Lausanne …, 2005	3070	2005
Advances in kernel methods: support vector learning B Schölkopf, CJC Burges, AJ Smola MIT press, 1999	2495	1999
Kernel methods in machine learning T Hofmann, B Schölkopf, AJ Smola	2463	2008
Estimating the support of a high-dimensional distribution JC Platt, JS Shawe-Taylor, AJ Smola, RC Williamson Neural computation 13 (7), 1443-1471, 2001	2275	2001
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	2065	1999
Deep sets M Zaheer, S Kottur, S Ravanbakhsh, B Poczos, RR Salakhutdinov, ... Advances in neural information processing systems 30, 2017	2050	2017
A generalized representer theorem B Schölkopf, R Herbrich, AJ Smola Computational Learning Theory: 14th Annual Conference on Computational …, 2001	2026	2001
kernlab-an S4 package for kernel methods in R A Karatzoglou, K Hornik, A Smola, A Zeileis Journal of statistical software 11 (9), 2004	1980	2004
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	1974	2006
Stacked attention networks for image question answering Z Yang, X He, J Gao, L Deng, A Smola Proceedings of the IEEE conference on computer vision and pattern …, 2016	1970	2016
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	1901	2006

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