Alex Smola

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Bernhard SchölkopfDirector, Max Planck Institute for Intelligent Systems & ELLIS Institute Tübingen; Professor at ETHPatvirtintas el. paštas tuebingen.mpg.de
Arthur GrettonGatsby Computational Neuroscience Unit and Google DeepmindPatvirtintas el. paštas gatsby.ucl.ac.uk
Klaus-Robert MüllerGoogle DeepMind & TU Berlin & Korea University & Max Planck Institute for Informatics, GermanyPatvirtintas el. paštas tu-berlin.de
Robert C. WilliamsonUniversity of TübingenPatvirtintas el. paštas uni-tuebingen.de
Mu LiAmazonPatvirtintas el. paštas amazon.com
S V N VishwanathanAssociate Professor of Statistics and Computer Science, Purdue UniversityPatvirtintas el. paštas stat.purdue.edu
Amr AhmedSenior Staff Research Scientist, Google AIPatvirtintas el. paštas google.com
Karsten BorgwardtDirector, Max Planck Institute of BiochemistryPatvirtintas el. paštas biochem.mpg.de
Le SongBiomap, Mohamed bin Zayed University of Artificial IntelligencePatvirtintas el. paštas biomap.com
Gunnar RätschProfessor, ETH ZürichPatvirtintas el. paštas inf.ethz.ch
Peter BartlettProfessor, EECS and Statistics, UC BerkeleyPatvirtintas el. paštas cs.berkeley.edu
Quoc V. LeResearch Scientist, GooglePatvirtintas el. paštas stanford.edu
vapnikProfessor of Columbia, Fellow of NEC Labs America, Patvirtintas el. paštas nec-labs.com
Sebastian MikaPatvirtintas el. paštas sebastianmika.info
John Shawe-TaylorUCLPatvirtintas el. paštas cs.ucl.ac.uk
Jonas MuellerCleanlabPatvirtintas el. paštas csail.mit.edu
Manzil ZaheerGoogle ResearchPatvirtintas el. paštas cmu.edu
Choon Hui TeoAmazonPatvirtintas el. paštas amazon.com
Alexandros KaratzoglouGoogle DeepmindPatvirtintas el. paštas google.com
Barnabas PoczosAssociate professor, Carnegie Mellon UniversityPatvirtintas el. paštas cs.cmu.edu

Stebėti

Alex Smola

Boson AI

Patvirtintas el. paštas smola.org - Pagrindinis puslapis

Machine Learning Deep Learning Systems


Pavadinimas Rūšiuoti pagal šaltinius Rūšiuoti pagal metus Rūšiuoti pagal pavadinimą	Cituota Cituota	Metai
Learning with kernels: Support vector machines, regularization, optimization, and beyond B Schölkopf, AJ Smola the MIT Press, 2002	24835*	2002
A tutorial on support vector regression AJ Smola, B Schölkopf Statistics and computing 14, 199-222, 2004	15722	2004
Nonlinear component analysis as a kernel eigenvalue problem B Schölkopf, A Smola, KR Müller Neural computation 10 (5), 1299-1319, 1998	11110	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	7535	2001
Support vector regression machines H Drucker, CJ Burges, L Kaufman, A Smola, V Vapnik Advances in neural information processing systems 9, 1996	7083	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	6134	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	6078	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	4359	1996
New support vector algorithms B Schölkopf, AJ Smola, RC Williamson, PL Bartlett Neural computation 12 (5), 1207-1245, 2000	3802	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	3180	1999
Kernel methods in machine learning T Hofmann, B Schölkopf, AJ Smola	2972	2008
Deep sets M Zaheer, S Kottur, S Ravanbakhsh, B Poczos, RR Salakhutdinov, ... Advances in neural information processing systems 30, 2017	2955	2017
Kernel principal component analysis B Schölkopf, A Smola, KR Müller International conference on artificial neural networks, 583-588, 1997	2744	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	2734	2006
Advances in kernel methods: support vector learning B Schölkopf, CJC Burges, AJ Smola MIT press, 1999	2677	1999
A generalized representer theorem B Schölkopf, R Herbrich, AJ Smola International conference on computational learning theory, 416-426, 2001	2353	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	2342	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	2306	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	2225	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	2218	2004

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