Alex Smola

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	All	Since 2016
Citations	143988	66691
h-index	130	96
i10-index	345	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
Peter BartlettProfessor, EECS and Statistics, UC BerkeleyVerified email at cs.berkeley.edu
Karsten BorgwardtProfessor, ETH ZurichVerified email at bsse.ethz.ch
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
Mu LiAmazonVerified email at amazon.com
John Shawe-TaylorUCLVerified email at cs.ucl.ac.uk
Choon Hui TeoAmazonVerified email at amazon.com
Alexandros KaratzoglouGoogleVerified email at google.com
Ralf HerbrichZalandoVerified email at zalando.de
John C. PlattGoogleVerified email at google.com
Malte J RaschIBM Research AIVerified email at ibm.com
Manzil ZaheerGoogle ResearchVerified email at cmu.edu

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	19754*	2002
A tutorial on support vector regression AJ Smola, B Schölkopf Statistics and computing 14 (3), 199-222, 2004	10734	2004
Nonlinear component analysis as a kernel eigenvalue problem B Schölkopf, A Smola, KR Müller Neural computation 10 (5), 1299-1319, 1998	9194	1998
Introduction to machine learning E Alpaydin MIT press, 2020	8673	2020
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	5102	2001
Support vector regression machines H Drucker, CJ Burges, L Kaufman, A Smola, V Vapnik Advances in neural information processing systems 9, 155-161, 1996	3882	1996
Support vector method for function approximation, regression estimation and signal processing V Vapnik, SE Golowich, AJ Smola Advances in neural information processing systems, 281-287, 1997	3429	1997
New support vector algorithms B Schölkopf, AJ Smola, RC Williamson, PL Bartlett Neural computation 12 (5), 1207-1245, 2000	3286	2000
Advances in kernel methods: support vector learning R Soentpiet MIT press, 1999	3198*	1999
Support vector machines MA Hearst, ST Dumais, E Osuna, J Platt, B Scholkopf IEEE Intelligent Systems and their applications 13 (4), 18-28, 1998	3187	1998
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	2791	2016
Kernel principal component analysis B Schölkopf, A Smola, KR Müller International conference on artificial neural networks, 583-588, 1997	2423	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	2087	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	2047	2012
Kernel methods in machine learning T Hofmann, B Schölkopf, AJ Smola The annals of statistics, 1171-1220, 2008	1680	2008
A generalized representer theorem B Schölkopf, R Herbrich, AJ Smola International conference on computational learning theory, 416-426, 2001	1543	2001
Input space versus feature space in kernel-based methods B Scholkopf, S Mika, CJC Burges, P Knirsch, KR Muller, G Ratsch, ... IEEE transactions on neural networks 10 (5), 1000-1017, 1999	1540	1999
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	1532	2004
Support vector method for novelty detection B Schölkopf, RC Williamson, AJ Smola, J Shawe-Taylor, JC Platt Advances in neural information processing systems, 582-588, 2000	1500	2000
Regularization networks and support vector machines T Evgeniou, M Pontil, T Poggio Advances in computational mathematics 13 (1), 1, 2000	1487	2000

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