Alex Smola

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Citations	148137	68589
h-index	131	98
i10-index	341	266

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Bernhard SchölkopfDirector, Max Planck Institute for Intelligent Systems; Professor at ETH Zürich, and DistinguishedVerified email at tuebingen.mpg.de
arthur grettonGatsby Computational Neuroscience Unit, UCLVerified email at gatsby.ucl.ac.uk
Klaus-Robert MüllerGoogle Brain (on leave of Professor for Machine Learning, TU Berlin & Korea University, Seoul)Verified 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 BorgwardtProfessor, ETH ZurichVerified email at bsse.ethz.ch
Peter BartlettProfessor, EECS and Statistics, UC BerkeleyVerified email at cs.berkeley.edu
Le SongGeorgia Institute of TechnologyVerified email at cc.gatech.edu
Gunnar RätschProfessor, ETH ZürichVerified email at inf.ethz.ch
Quoc V. LeResearch Scientist, Google BrainVerified email at stanford.edu
Sebastian MikacomtravoVerified email at comtravo.com
vapnikProfessor of Columbia, Fellow of NEC Labs America, Verified email at nec-labs.com
John Shawe-TaylorUCLVerified email at cs.ucl.ac.uk
Mu LiAmazonVerified email at amazon.com
John C. PlattGoogleVerified email at google.com
Alexandros KaratzoglouGoogleVerified email at google.com
Choon Hui TeoAmazonVerified email at amazon.com
Ralf HerbrichZalandoVerified email at zalando.de
Barnabas PoczosAssociate professor, Carnegie Mellon UniversityVerified email at cs.cmu.edu
Malte J RaschIBM Research AIVerified email at ibm.com

Alex Smola

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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	20207*	2002
A tutorial on support vector regression AJ Smola, B Schölkopf Statistics and computing 14 (3), 199-222, 2004	10940	2004
Introduction to machine learning E Alpaydin MIT press, 2020	8762	2020
Nonlinear component analysis as a kernel eigenvalue problem B Schölkopf, A Smola, KR Müller Neural computation 10 (5), 1299-1319, 1998	5947	1998
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	5216	2001
Nonlinear component analysis as a kernel eigenvalue problem S Lim	4411	2011
Support vector regression machines H Drucker, CJC Burges, L Kaufman, A Smola, V Vapnik Advances in neural information processing systems 9, 155-161, 1997	4008	1997
Support vector method for function approximation, regression estimation, and signal processing V Vapnik, SE Golowich, A Smola Advances in neural information processing systems, 281-287, 1997	3499	1997
New support vector algorithms B Schölkopf, AJ Smola, RC Williamson, PL Bartlett Neural computation 12 (5), 1207-1245, 2000	3332	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	3216	1998
Advances in kernel methods: support vector learning R Soentpiet MIT press, 1999	3094*	1999
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	2904	2016
Kernel principal component analysis B Schölkopf, A Smola, KR Müller International conference on artificial neural networks, 583-588, 1997	2457	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	2124	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	2113	2012
Regularization networks and support vector machines T Evgeniou, M Pontil, T Poggio Advances in computational mathematics 13 (1), 1-50, 2000	1920*	2000
Kernel methods in machine learning T Hofmann, B Schölkopf, AJ Smola The annals of statistics, 1171-1220, 2008	1701	2008
Pairwise classification and support vector machines UHG Krebel Advances in kernel methods: support vector learning, 255-268, 1999	1608	1999
A generalized representer theorem B Schölkopf, R Herbrich, AJ Smola International conference on computational learning theory, 416-426, 2001	1568	2001
kernlab-an S4 package for kernel methods in R A Karatzoglou, A Smola, K Hornik, A Zeileis Journal of statistical software 11 (9), 1-20, 2004	1566	2004

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