| 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, 89-129, 2008 | 534 | 2008 |
| Convergence properties of functional estimates for discrete distributions A Antos, I Kontoyiannis Random Structures & Algorithms 19 (3‐4), 163-193, 2001 | 324 | 2001 |
| Fitted Q-iteration in continuous action-space MDPs A Antos, R Munos, C Szepesvári Advances in Neural Information Processing Systems 20, 9-16, 2008 | 319 | 2008 |
| Online Markov decision processes under bandit feedback G Neu, A György, C Szepesvári, A Antos Advances in Neural Information Processing Systems 23, 1804-1812, 2010 | 225 | 2010 |
| Lower bounds for Bayes error estimation A Antos, L Devroye, L Györfi Pattern Analysis and Machine Intelligence, IEEE Transactions on 21 (7), 643-645, 1999 | 101 | 1999 |
| Active learning in heteroscedastic noise A Antos, V Grover, C Szepesvári Theoretical Computer Science 411 (29-30), 2712-2728, 2010 | 79 | 2010 |
| Active learning in multi-armed bandits A Antos, V Grover, C Szepesvári Algorithmic Learning Theory: 19th International Conference, ALT 2008 …, 2008 | 78 | 2008 |
| Data-dependent margin-based generalization bounds for classification A Antos, B Kégl, T Linder, G Lugosi Journal of Machine Learning Research 3, 73-98, 2003 | 61 | 2003 |
| Individual convergence rates in empirical vector quantizer design A Antos, L Györfi, A György Information Theory, IEEE Transactions on 51 (11), 4013-4022, 2005 | 58 | 2005 |
| Improved convergence rates in empirical vector quantizer design A Antos, L Györfi, A György Proceedings 2004 IEEE International Symposium on Information Theory, 301, 2004 | 58* | 2004 |
| Value-iteration based fitted policy iteration: learning with a single trajectory A Antos, C Szepesvári, R Munos Approximate Dynamic Programming and Reinforcement Learning, 2007. ADPRL 2007 …, 2007 | 54 | 2007 |
| Toward a classification of finite partial-monitoring games A Antos, G Bartók, D Pál, C Szepesvári Theoretical Computer Science, Arxiv preprint arXiv:1102.2041, 2012 | 52 | 2012 |
| Strong minimax lower bounds for learning A Antos, G Lugosi Proceedings of the Ninth Annual Conference on Computational Learning Theory …, 1996 | 49 | 1996 |
| Learning near-optimal policies with Bellman-residual minimization based fitted policy iteration and a single sample path A Antos, C Szepesvari, R Munos The Nineteenth Annual Conference on Learning Theory, COLT 2006, Proceedings …, 2006 | 41 | 2006 |
| Improved minimax bounds on the test and training distortion of empirical designed vector quantizers A Antos LNCS/LNAI: The Eighteenth Annual Conference on Learning Theory, COLT 2005 …, 2005 | 36 | 2005 |
| Forced-exploration based algorithms for playing in stochastic linear bandits Y Abbasi-Yadkori, A Antos, C Szepesvári COLT Workshop on On-line Learning with Limited Feedback 92, 236, 2009 | 29 | 2009 |
| Adaptive strategy for stratified Monte Carlo sampling. A Carpentier, R Munos, A Antos J. Mach. Learn. Res. 16, 2231-2271, 2015 | 27 | 2015 |
| Lower bounds on the rate of convergence of nonparametric regression estimates A Antos, L Györfi, M Kohler Journal of statistical planning and inference 83 (1), 91-100, 2000 | 19 | 2000 |
| Estimating the entropy of discrete distributions A Antos, I Kontoyiannis IEEE International Symposium on Information Theory, 45-45, 2001 | 17 | 2001 |
| Performance limits of nonparametric estimators A Antos Technical University of Budapest, 1999 | 8 | 1999 |
Csaba SzepesvariDeepMind & University of AlbertaVerified email at cs.ualberta.ca
