Alex Smola

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Bernhard SchölkopfDirector, Max Planck Institute for Intelligent Systems & ELLIS Institute Tübingen; Professor at ETHAdresse e-mail validée de tuebingen.mpg.de
Arthur GrettonGatsby Computational Neuroscience Unit and Google DeepmindAdresse e-mail validée de gatsby.ucl.ac.uk
Klaus-Robert MüllerGoogle DeepMind & TU Berlin & Korea University & Max Planck Institute for Informatics, GermanyAdresse e-mail validée de tu-berlin.de
Robert C. WilliamsonUniversity of TübingenAdresse e-mail validée de uni-tuebingen.de
Mu LiAmazonAdresse e-mail validée de amazon.com
S V N VishwanathanAssociate Professor of Statistics and Computer Science, Purdue UniversityAdresse e-mail validée de stat.purdue.edu
Amr AhmedSenior Staff Research Scientist, Google AIAdresse e-mail validée de google.com
Karsten BorgwardtDirector, Max Planck Institute of BiochemistryAdresse e-mail validée de biochem.mpg.de
Le SongBiomap, Mohamed bin Zayed University of Artificial IntelligenceAdresse e-mail validée de biomap.com
Gunnar RätschProfessor, ETH ZürichAdresse e-mail validée de inf.ethz.ch
Peter BartlettProfessor, EECS and Statistics, UC BerkeleyAdresse e-mail validée de cs.berkeley.edu
Quoc V. LeResearch Scientist, GoogleAdresse e-mail validée de stanford.edu
vapnikProfessor of Columbia, Fellow of NEC Labs America, Adresse e-mail validée de nec-labs.com
Sebastian MikaAdresse e-mail validée de sebastianmika.info
John Shawe-TaylorUCLAdresse e-mail validée de cs.ucl.ac.uk
Jonas MuellerCleanlabAdresse e-mail validée de csail.mit.edu
Manzil ZaheerGoogle ResearchAdresse e-mail validée de cmu.edu
Choon Hui TeoAmazonAdresse e-mail validée de amazon.com
Alexandros KaratzoglouGoogle DeepmindAdresse e-mail validée de google.com
Barnabas PoczosAssociate professor, Carnegie Mellon UniversityAdresse e-mail validée de cs.cmu.edu

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Alex Smola

Boson AI

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Machine Learning Deep Learning Systems


Titre Trier par citations Trier par année Trier par titre	Citée par Citée par	Année
Learning with kernels: Support vector machines, regularization, optimization, and beyond B Schölkopf, AJ Smola the MIT Press, 2002	24657*	2002
A tutorial on support vector regression AJ Smola, B Schölkopf Statistics and computing 14, 199-222, 2004	15525	2004
Nonlinear component analysis as a kernel eigenvalue problem B Schölkopf, A Smola, KR Müller Neural computation 10 (5), 1299-1319, 1998	11058	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	7440	2001
Support vector regression machines H Drucker, CJ Burges, L Kaufman, A Smola, V Vapnik Advances in neural information processing systems 9, 1996	6954	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	6024	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	5881	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	4318	1996
New support vector algorithms B Schölkopf, AJ Smola, RC Williamson, PL Bartlett Neural computation 12 (5), 1207-1245, 2000	3783	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	3115	1999
Kernel methods in machine learning T Hofmann, B Schölkopf, AJ Smola	2919	2008
Deep sets M Zaheer, S Kottur, S Ravanbakhsh, B Poczos, RR Salakhutdinov, ... Advances in neural information processing systems 30, 2017	2847	2017
Kernel principal component analysis B Schölkopf, A Smola, KR Müller International conference on artificial neural networks, 583-588, 1997	2711	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	2687	2006
Advances in kernel methods: support vector learning B Schölkopf, CJC Burges, AJ Smola MIT press, 1999	2658	1999
A generalized representer theorem B Schölkopf, R Herbrich, AJ Smola International conference on computational learning theory, 416-426, 2001	2324	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	2300	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	2258	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	2196	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	2195	2004

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