Alex Smola

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Bernhard SchölkopfDirector, Max Planck Institute for Intelligent Systems & ELLIS Institute Tübingen; Professor at ETHVerified email at tuebingen.mpg.de
Arthur GrettonGatsby Computational Neuroscience Unit and Google DeepmindVerified email at gatsby.ucl.ac.uk
Klaus-Robert MüllerGoogle DeepMind & TU Berlin & Korea University & Max Planck Institute for Informatics, GermanyVerified email at tu-berlin.de
Robert C. WilliamsonUniversity of TübingenVerified email at uni-tuebingen.de
Mu LiAmazonVerified email at amazon.com
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
Le SongBiomap, Mohamed bin Zayed University of Artificial IntelligenceVerified email at biomap.com
Gunnar RätschProfessor, ETH ZürichVerified email at inf.ethz.ch
Peter BartlettProfessor, EECS and Statistics, UC BerkeleyVerified email at cs.berkeley.edu
Quoc V. LeResearch Scientist, GoogleVerified email at stanford.edu
vapnikProfessor of Columbia, Fellow of NEC Labs America, Verified email at nec-labs.com
Sebastian MikaVerified email at sebastianmika.info
John Shawe-TaylorUCLVerified email at cs.ucl.ac.uk
Jonas MuellerCleanlabVerified email at csail.mit.edu
Manzil ZaheerGoogle ResearchVerified email at cmu.edu
Choon Hui TeoAmazonVerified email at amazon.com
Alexandros KaratzoglouGoogle DeepmindVerified email at google.com
Barnabas PoczosAssociate professor, Carnegie Mellon UniversityVerified email at cs.cmu.edu

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	24633*	2002
A tutorial on support vector regression AJ Smola, B Schölkopf Statistics and computing 14, 199-222, 2004	15497	2004
Nonlinear component analysis as a kernel eigenvalue problem B Schölkopf, A Smola, KR Müller Neural computation 10 (5), 1299-1319, 1998	11049	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	7432	2001
Support vector regression machines H Drucker, CJ Burges, L Kaufman, A Smola, V Vapnik Advances in neural information processing systems 9, 1996	6936	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	6019	2016
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	5848	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	4306	1996
New support vector algorithms B Schölkopf, AJ Smola, RC Williamson, PL Bartlett Neural computation 12 (5), 1207-1245, 2000	3781	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	3107	1999
Kernel methods in machine learning T Hofmann, B Schölkopf, AJ Smola	2913	2008
Deep sets M Zaheer, S Kottur, S Ravanbakhsh, B Poczos, RR Salakhutdinov, ... Advances in neural information processing systems 30, 2017	2834	2017
Kernel principal component analysis B Schölkopf, A Smola, KR Müller International conference on artificial neural networks, 583-588, 1997	2706	1997
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	2681	2006
Advances in kernel methods: support vector learning B Schölkopf, CJC Burges, AJ Smola MIT press, 1999	2665	1999
A generalized representer theorem B Schölkopf, R Herbrich, AJ Smola International conference on computational learning theory, 416-426, 2001	2319	2001
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	2295	2016
Scaling distributed machine learning with the parameter server M Li, DG Andersen, JW Park, AJ Smola, A Ahmed, V Josifovski, J Long, ... 11th USENIX Symposium on operating systems design and implementation (OSDI …, 2014	2252	2014
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	2193	2006
kernlab-an S4 package for kernel methods in R A Karatzoglou, A Smola, K Hornik, A Zeileis Journal of statistical software 11, 1-20, 2004	2191	2004

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