Csaba Szepesvari - Google Scholar Citations

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Rémi MunosDeepMindVerified email at inria.fr
Andras GyorgyDeepMindVerified email at ualberta.ca
Yasin Abbasi-YadkoriResearcher, VinAIVerified email at vinai.io
Kocsis LeventeMTA SZTAKIVerified email at sztaki.hu
Lorincz, AndrasEotvos Lorand UniversityVerified email at inf.elte.hu
Richard S. SuttonDeepMind and Dept of Computing Science, University of AlbertaVerified email at richsutton.com
Amir-massoud FarahmandVector InstituteVerified email at vectorinstitute.ai
Branislav KvetonGoogle ResearchVerified email at google.com
András AntosBudapest University of Technology and EconomicsVerified email at cs.bme.hu
Tor LattimoreDeepMindVerified email at google.com
David PalPrincipal Applied Researcher, Expedia GroupVerified email at expedia.com
Shalabh BhatnagarProfessor in the Department of Computer Science and Automation, Indian Institute of ScienceVerified email at iisc.ac.in
Mohammad GhavamzadehFacebook AI Research (FAIR)Verified email at inria.fr
Zheng WenDeepMindVerified email at google.com
Hamid MaeiCriteo AI LabVerified email at criteo.com
Michael LittmanBrown UniversityVerified email at brown.edu
Shie MannorProfessor of Electrical Engineering, TechnionVerified email at technion.ac.il
Gábor BartókETH ZurichVerified email at ualberta.ca
Gergely NeuArtificial Intelligence and Machine Learning group, Universitat Pompeu FabraVerified email at upf.edu
David SilverGoogle DeepMindVerified email at google.com

Csaba Szepesvari

DeepMind & Department of Computing Science, University of Alberta

Verified email at cs.ualberta.ca - Homepage

machine learning learning theory online learning reinforcement learning Markov Decision Processes


Title	Cited by	Year
Bandit based monte-carlo planning L Kocsis, C Szepesvári European conference on machine learning, 282-293, 2006	2563	2006
Algorithms for Reinforcement Learning C Szepesvari Morgan and Claypool, 2010	874	2010
Convergence results for single-step on-policy reinforcement-learning algorithms S Singh, T Jaakkola, ML Littman, C Szepesvári Machine learning 38 (3), 287-308, 2000	658	2000
Improved algorithms for linear stochastic bandits Y Abbasi-Yadkori, C Szepesvári, D Pál Advances in Neural Information Processing Systems, 2312-2320, 2011	485	2011
Exploration–exploitation tradeoff using variance estimates in multi-armed bandits JY Audibert, R Munos, C Szepesvári Theoretical Computer Science 410 (19), 1876-1902, 2009	434	2009
Fast gradient-descent methods for temporal-difference learning with linear function approximation RS Sutton, HR Maei, D Precup, S Bhatnagar, D Silver, C Szepesvári, ... Proceedings of the 26th Annual International Conference on Machine Learning …, 2009	420	2009
X-armed bandits S Bubeck, R Munos, G Stoltz, C Szepesvári Journal of Machine Learning Research 12 (May), 1655-1695, 2011	281	2011
Learning near-optimal policies with Bellman-residual minimization based fitted policy iteration and a single sample path A Antos, C Szepesvári, R Munos Machine Learning 71 (1), 89-129, 2008	241	2008
A generalized reinforcement-learning model: Convergence and applications ML Littman, C Szepesvári ICML 96, 310-318, 1996	234	1996
Finite-time bounds for fitted value iteration R Munos, C Szepesvári Journal of Machine Learning Research 9 (May), 815-857, 2008	229	2008
The grand challenge of computer Go: Monte Carlo tree search and extensions S Gelly, L Kocsis, M Schoenauer, M Sebag, D Silver, C Szepesvári, ... Communications of the ACM 55 (3), 106-113, 2012	221	2012
Apprenticeship learning using inverse reinforcement learning and gradient methods G Neu, C Szepesvári arXiv preprint arXiv:1206.5264, 2012	210	2012
Multi-criteria reinforcement learning. Z Gábor, Z Kalmár, C Szepesvári ICML 98, 197-205, 1998	207	1998
Toward off-policy learning control with function approximation HR Maei, C Szepesvári, S Bhatnagar, RS Sutton ICML, 2010	198	2010
Parametric bandits: The generalized linear case S Filippi, O Cappe, A Garivier, C Szepesvári Advances in Neural Information Processing Systems, 586-594, 2010	197	2010
Online optimization in X-armed bandits S Bubeck, G Stoltz, C Szepesvári, R Munos Advances in Neural Information Processing Systems, 201-208, 2009	194	2009
Convergent temporal-difference learning with arbitrary smooth function approximation S Bhatnagar, D Precup, D Silver, RS Sutton, HR Maei, C Szepesvári Advances in neural information processing systems, 1204-1212, 2009	188	2009
Empirical bernstein stopping V Mnih, C Szepesvári, JY Audibert Proceedings of the 25th international conference on Machine learning, 672-679, 2008	183	2008
Fitted Q-iteration in continuous action-space MDPs A Antos, C Szepesvári, R Munos Advances in neural information processing systems, 9-16, 2008	162	2008
Improved rates for the stochastic continuum-armed bandit problem P Auer, R Ortner, C Szepesvári International Conference on Computational Learning Theory, 454-468, 2007	157	2007

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