Alex Smola

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Bernhard SchölkopfDirector, Max Planck Institute for Intelligent Systems; Professor at ETH ZürichEmail confirmado em tuebingen.mpg.de
Arthur GrettonGatsby Computational Neuroscience Unit and DeepmindEmail confirmado em gatsby.ucl.ac.uk
Robert C. WilliamsonUniversity of TübingenEmail confirmado em uni-tuebingen.de
Klaus-Robert MüllerTU Berlin & Korea University & Google Brain & Max Planck Institute for Informatics, GermanyEmail confirmado em tu-berlin.de
S V N VishwanathanAssociate Professor of Statistics and Computer Science, Purdue UniversityEmail confirmado em stat.purdue.edu
Amr AhmedSenior Staff Research Scientist, Google AIEmail confirmado em google.com
Karsten BorgwardtDirector, Max Planck Institute of BiochemistryEmail confirmado em biochem.mpg.de
Mu LiAmazonEmail confirmado em amazon.com
Peter BartlettProfessor, EECS and Statistics, UC BerkeleyEmail confirmado em cs.berkeley.edu
Le SongBiomap, Mohamed bin Zayed University of Artificial IntelligenceEmail confirmado em biomap.com
Gunnar RätschProfessor, ETH ZürichEmail confirmado em inf.ethz.ch
Quoc V. LeResearch Scientist, Google BrainEmail confirmado em stanford.edu
John Shawe-TaylorUCLEmail confirmado em cs.ucl.ac.uk
Sebastian MikaEmail confirmado em sebastianmika.info
vapnikProfessor of Columbia, Fellow of NEC Labs America, Email confirmado em nec-labs.com
John C. PlattGoogleEmail confirmado em google.com
Malte J RaschIBM Research AIEmail confirmado em ibm.com
Alexandros KaratzoglouGoogleEmail confirmado em google.com
Manzil ZaheerGoogle ResearchEmail confirmado em cmu.edu
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Alex Smola

Boson AI

Email confirmado em smola.org - Página inicial

Machine Learning Deep Learning Systems


Título Ordenar por citações Ordenar por ano Ordenar por título	Citado por Citado por	Ano
Learning with kernels: Support vector machines, regularization, optimization, and beyond B Schölkopf, AJ Smola the MIT Press, 2002	22600*	2002
A tutorial on support vector regression AJ Smola, B Schölkopf Statistics and computing 14, 199-222, 2004	13696	2004
Nonlinear component analysis as a kernel eigenvalue problem B Schölkopf, A Smola, KR Müller Neural computation 10 (5), 1299-1319, 1998	10356	1998
Support vector regression machines H Drucker, CJ Burges, L Kaufman, A Smola, V Vapnik Advances in neural information processing systems 9, 1996	5680	1996
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	4892	2001
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	4867	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	4080	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	3913	1996
New support vector algorithms B Schölkopf, AJ Smola, RC Williamson, PL Bartlett Neural computation 12 (5), 1207-1245, 2000	3711	2000
Kernel principal component analysis B Schölkopf, A Smola, KR Müller Artificial Neural Networks—ICANN'97: 7th International Conference Lausanne …, 2005	3039	2005
Advances in kernel methods: support vector learning B Schölkopf, CJC Burges, AJ Smola MIT press, 1999	2480	1999
Kernel methods in machine learning T Hofmann, B Schölkopf, AJ Smola	2418	2008
Estimating the support of a high-dimensional distribution JC Platt, JS Shawe-Taylor, AJ Smola, RC Williamson Neural computation 13 (7), 1443-1471, 2001	2254	2001
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	1986	1999
A generalized representer theorem B Schölkopf, R Herbrich, AJ Smola Computational Learning Theory: 14th Annual Conference on Computational …, 2001	1983	2001
Deep sets M Zaheer, S Kottur, S Ravanbakhsh, B Poczos, RR Salakhutdinov, ... Advances in neural information processing systems 30, 2017	1955	2017
kernlab-an S4 package for kernel methods in R A Karatzoglou, K Hornik, A Smola, A Zeileis Journal of statistical software 11 (9), 2004	1951	2004
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	1920	2016
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	1911	2006
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	1866	2006

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