Matthias Seeger

Citirano

	Sve	Od 2018.
Citati	14152	6925
H-indeks	40	30
i10-indeks	71	49

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Suautori

Cédric ArchambeauAmazon Web Services, BerlinPotvrđena adresa e-pošte na amazon.com
Sham M KakadeHarvard UniversityPotvrđena adresa e-pošte na seas.harvard.edu
Andreas KrauseProfessor of Computer Science, ETH ZurichPotvrđena adresa e-pošte na inf.ethz.ch
Hannes NickischPhilips ResearchPotvrđena adresa e-pošte na philips.com
Chris WilliamsProfessor of Machine Learning, University of EdinburghPotvrđena adresa e-pošte na inf.ed.ac.uk
Neil D. LawrenceUniversity of CambridgePotvrđena adresa e-pošte na cl.cam.ac.uk
Jan PetersProfessor for Intelligent Autonomous Systems at Technische Universität DarmstadtPotvrđena adresa e-pošte na ias.tu-darmstadt.de
Rodolphe JENATTONSenior machine learning scientist at Google Brain, BerlinPotvrđena adresa e-pošte na google.com
Ralf HerbrichHasso Plattner InstitutePotvrđena adresa e-pošte na hpi.de
Bernhard SchölkopfDirector, Max Planck Institute for Intelligent Systems; Professor at ETH Zürich, and DistinguishedPotvrđena adresa e-pošte na tuebingen.mpg.de
Michael I. JordanProfessor of Electrical Engineering and Computer Sciences and Professor of Statistics, UC BerkeleyPotvrđena adresa e-pošte na cs.berkeley.edu
David SalinasAmazonPotvrđena adresa e-pošte na ens-lyon.org
Florian SteinkeProfessor, Energy Information Networks & Systems, TU DarmstadtPotvrđena adresa e-pošte na eins.tu-darmstadt.de
Aaron KleinAWS Research BerlinPotvrđena adresa e-pošte na amazon.com
Yee Whye TehProfessor of Statistical Machine Learning, Oxford, Research Scientist, DeepMindPotvrđena adresa e-pošte na stats.ox.ac.uk
Andrew NgStanford UniversityPotvrđena adresa e-pošte na cs.stanford.edu
Martin WistubaIBM ResearchPotvrđena adresa e-pošte na ismll.de

Prati

Matthias Seeger

Principal Applied Scientist, Amazon, Berlin

Potvrđena adresa e-pošte na amazon.de - Početna stranica

Machine Learning Bayesian Statistics Bayesian Optimization


Naslov Poredaj po navodima Poredaj po godini Poredaj po naslovu	Citirano Citirano	Godina
Using the Nyström method to speed up kernel machines C Williams, M Seeger Advances in neural information processing systems 13, 2000	2722	2000
Gaussian process optimization in the bandit setting: No regret and experimental design N Srinivas, A Krause, SM Kakade, M Seeger arXiv preprint arXiv:0912.3995, 2009	2032	2009
Gaussian processes for machine learning M Seeger International journal of neural systems 14 (02), 69-106, 2004	889	2004
Learning with labeled and unlabeled data M Seeger	722	2000
Information-theoretic regret bounds for gaussian process optimization in the bandit setting N Srinivas, A Krause, SM Kakade, MW Seeger IEEE transactions on information theory 58 (5), 3250-3265, 2012	714	2012
Fast sparse Gaussian process methods: The informative vector machine N Lawrence, M Seeger, R Herbrich Advances in neural information processing systems 15, 2002	693	2002
Fast forward selection to speed up sparse Gaussian process regression MW Seeger, CKI Williams, ND Lawrence International Workshop on Artificial Intelligence and Statistics, 254-261, 2003	579	2003
Deep state space models for time series forecasting SS Rangapuram, MW Seeger, J Gasthaus, L Stella, Y Wang, ... Advances in neural information processing systems 31, 2018	439	2018
Bayesian inference and optimal design in the sparse linear model M Seeger, F Steinke, K Tsuda Artificial Intelligence and Statistics, 444-451, 2007	366	2007
PAC-Bayesian generalisation error bounds for Gaussian process classification M Seeger Journal of machine learning research 3 (Oct), 233-269, 2002	357	2002
Model learning with local gaussian process regression D Nguyen-Tuong, M Seeger, J Peters Advanced Robotics 23 (15), 2015-2034, 2009	354	2009
Semiparametric latent factor models YW Teh, M Seeger, MI Jordan International Workshop on Artificial Intelligence and Statistics, 333-340, 2005	294	2005
Local gaussian process regression for real time online model learning D Nguyen-Tuong, J Peters, M Seeger Advances in neural information processing systems 21, 2008	278	2008
Bayesian Gaussian process models: PAC-Bayesian generalisation error bounds and sparse approximations M Seeger University of Edinburgh, 2003	233	2003
The effect of the input density distribution on kernel-based classifiers C Williams, M Seeger ICML'00 Proceedings of the Seventeenth International Conference on Machine …, 2000	224	2000
Expectation propagation for exponential families M Seeger	198	2005
Computed torque control with nonparametric regression models D Nguyen-Tuong, M Seeger, J Peters 2008 American Control Conference, 212-217, 2008	174	2008
Optimization of k‐space trajectories for compressed sensing by Bayesian experimental design M Seeger, H Nickisch, R Pohmann, B Schölkopf Magnetic Resonance in Medicine: An Official Journal of the International …, 2010	170	2010
Bayesian model selection for support vector machines, Gaussian processes and other kernel classifiers M Seeger Advances in neural information processing systems 12, 1999	169	1999
Fast gaussian process regression using kd-trees Y Shen, M Seeger, A Ng Advances in neural information processing systems 18, 2005	149	2005

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