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 MüllerTU Berlin & Korea University & Google Deepmind & 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
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
Mu LiAmazonAdresse e-mail validée de amazon.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
Peter BartlettProfessor, EECS and Statistics, UC BerkeleyAdresse e-mail validée de cs.berkeley.edu
Gunnar RätschProfessor, ETH ZürichAdresse e-mail validée de inf.ethz.ch
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
John Shawe-TaylorUCLAdresse e-mail validée de cs.ucl.ac.uk
Sebastian MikaAdresse e-mail validée de sebastianmika.info
Manzil ZaheerGoogle ResearchAdresse e-mail validée de cmu.edu
Jonas MuellerCleanlabAdresse e-mail validée de csail.mit.edu
Alexandros KaratzoglouGoogle DeepmindAdresse e-mail validée de google.com
Choon Hui TeoAmazonAdresse e-mail validée de amazon.com
Malte J RaschIBM Research AIAdresse e-mail validée de ibm.com

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Alex Smola

Boson AI

Adresse e-mail validée de smola.org - Page d'accueil

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	23611*	2002
A tutorial on support vector regression AJ Smola, B Schölkopf Statistics and computing 14, 199-222, 2004	14592	2004
Nonlinear component analysis as a kernel eigenvalue problem B Schölkopf, A Smola, KR Müller Neural computation 10 (5), 1299-1319, 1998	10676	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	6873	2001
Support vector regression machines H Drucker, CJ Burges, L Kaufman, A Smola, V Vapnik Advances in neural information processing systems 9, 1996	6230	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	5417	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	4867	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	4106	1996
New support vector algorithms B Schölkopf, AJ Smola, RC Williamson, PL Bartlett Neural computation 12 (5), 1207-1245, 2000	3655	2000
Kernel principal component analysis B Schölkopf, A Smola, KR Müller International conference on artificial neural networks, 583-588, 1997	3221	1997
Advances in kernel methods: support vector learning B Schölkopf, CJC Burges, AJ Smola MIT press, 1999	2687	1999
Kernel methods in machine learning T Hofmann, B Schölkopf, AJ Smola	2622	2008
Deep sets M Zaheer, S Kottur, S Ravanbakhsh, B Poczos, RR Salakhutdinov, ... Advances in neural information processing systems 30, 2017	2357	2017
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	2279	1999
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	2153	2006
A generalized representer theorem B Schölkopf, R Herbrich, AJ Smola International conference on computational learning theory, 416-426, 2001	2143	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	2119	2016
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	2058	2004
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	2010	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	2009	2006

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