Csaba Szepesvári

	2012
101		Mahdi Milani Fard, Joelle Pineau, Csaba Szepesvári: PAC-Bayesian Policy Evaluation for Reinforcement Learning CoRR abs/1202.3717: (2012)
100		Sylvain Gelly, Levente Kocsis, Marc Schoenauer, Michèle Sebag, David Silver, Csaba Szepesvári, Olivier Teytaud: The grand challenge of computer Go: Monte Carlo tree search and extensions. Commun. ACM 55(3): 106-113 (2012)
99		Yasin Abbasi-Yadkori, Dávid Pál, Csaba Szepesvári: Online-to-Confidence-Set Conversions and Application to Sparse Stochastic Bandits. Journal of Machine Learning Research - Proceedings Track 22: 1-9 (2012)
98		Gergely Neu, András György, Csaba Szepesvári: The adversarial stochastic shortest path problem with unknown transition probabilities. Journal of Machine Learning Research - Proceedings Track 22: 805-813 (2012)
	2011
97		Jyrki Kivinen, Csaba Szepesvári, Esko Ukkonen, Thomas Zeugmann: Algorithmic Learning Theory - 22nd International Conference, ALT 2011, Espoo, Finland, October 5-7, 2011. Proceedings Springer 2011
96		Jyrki Kivinen, Csaba Szepesvári, Esko Ukkonen, Thomas Zeugmann: Editors' Introduction. ALT 2011: 1-13
95		Csaba Szepesvári: Invited Talk: Towards Robust Reinforcement Learning Algorithms. EWRL 2011: 4
94		Pallavi Arora, Csaba Szepesvári, Rong Zheng: Sequential learning for optimal monitoring of multi-channel wireless networks. INFOCOM 2011: 1152-1160
93		Yasin Abbasi-Yadkori, Dávid Pál, Csaba Szepesvári: Improved Algorithms for Linear Stochastic Bandits. NIPS 2011: 2312-2320
92		Mahdi Milani Fard, Joelle Pineau, Csaba Szepesvári: PAC-Bayesian Policy Evaluation for Reinforcement Learning. UAI 2011: 195-202
91		András Antos, Gábor Bartók, Dávid Pál, Csaba Szepesvári: Toward a Classification of Finite Partial-Monitoring Games CoRR abs/1102.2041: (2011)
90		Yasin Abbasi-Yadkori, Dávid Pál, Csaba Szepesvári: Online Least Squares Estimation with Self-Normalized Processes: An Application to Bandit Problems CoRR abs/1102.2670: (2011)
89		András Antos, Gábor Bartók, Csaba Szepesvári: Non-trivial two-armed partial-monitoring games are bandits CoRR abs/1108.4961: (2011)
88		Arash Afkanpour, Csaba Szepesvári, Michael H. Bowling: Alignment Based Kernel Learning with a Continuous Set of Base Kernels CoRR abs/1112.4607: (2011)
87		Sébastien Bubeck, Rémi Munos, Gilles Stoltz, Csaba Szepesvári: X-Armed Bandits. Journal of Machine Learning Research 12: 1655-1695 (2011)
86		Yasin Abbasi-Yadkori, Csaba Szepesvári: Regret Bounds for the Adaptive Control of Linear Quadratic Systems. Journal of Machine Learning Research - Proceedings Track 19: 1-26 (2011)
85		Gábor Bartók, Dávid Pál, Csaba Szepesvári: Minimax Regret of Finite Partial-Monitoring Games in Stochastic Environments. Journal of Machine Learning Research - Proceedings Track 19: 133-154 (2011)
84		István Szita, Csaba Szepesvári: Agnostic KWIK learning and efficient approximate reinforcement learning. Journal of Machine Learning Research - Proceedings Track 19: 739-772 (2011)
83		Amir Massoud Farahmand, Csaba Szepesvári: Model selection in reinforcement learning. Machine Learning 85(3): 299-332 (2011)
	2010
82		Csaba Szepesvári: Algorithms for Reinforcement Learning Morgan & Claypool Publishers 2010
81		Gábor Bartók, Dávid Pál, Csaba Szepesvári: Toward a Classification of Finite Partial-Monitoring Games. ALT 2010: 224-238
80		Gergely Neu, András György, Csaba Szepesvári: The Online Loop-free Stochastic Shortest-Path Problem. COLT 2010: 231-243
79		Istvan Szita, Csaba Szepesvári: Model-based reinforcement learning with nearly tight exploration complexity bounds. ICML 2010: 1031-1038
78		Hamid Reza Maei, Csaba Szepesvári, Shalabh Bhatnagar, Richard S. Sutton: Toward Off-Policy Learning Control with Function Approximation. ICML 2010: 719-726
77		Liuyang Li, Barnabás Póczos, Csaba Szepesvári, Russell Greiner: Budgeted Distribution Learning of Belief Net Parameters. ICML 2010: 879-886
76		Yasin Abbasi-Yadkori, Joseph Modayil, Csaba Szepesvári: Extending rapidly-exploring random trees for asymptotically optimal anytime motion planning. IROS 2010: 127-132
75		Gergely Neu, András György, Csaba Szepesvári, András Antos: Online Markov Decision Processes under Bandit Feedback. NIPS 2010: 1804-1812
74		Dávid Pál, Barnabás Póczos, Csaba Szepesvári: Estimation of Renyi Entropy and Mutual Information Based on Generalized Nearest-Neighbor Graphs. NIPS 2010: 1849-1857
73		Amir Massoud Farahmand, Rémi Munos, Csaba Szepesvári: Error Propagation for Approximate Policy and Value Iteration. NIPS 2010: 568-576
72		Sarah Filippi, Olivier Cappé, Aurélien Garivier, Csaba Szepesvári: Parametric Bandits: The Generalized Linear Case. NIPS 2010: 586-594
71		Sébastien Bubeck, Rémi Munos, Gilles Stoltz, Csaba Szepesvári: X-Armed Bandits CoRR abs/1001.4475: (2010)
70		Dávid Pál, Barnabás Póczos, Csaba Szepesvári: Estimation of Rényi Entropy and Mutual Information Based on Generalized Nearest-Neighbor Graphs CoRR abs/1003.1954: (2010)
69		Gábor Bartók, Csaba Szepesvári, Sandra Zilles: Models of active learning in group-structured state spaces. Inf. Comput. 208(4): 364-384 (2010)
68		Barnabás Póczos, Sergey Kirshner, Csaba Szepesvári: REGO: Rank-based Estimation of Renyi Information using Euclidean Graph Optimization. Journal of Machine Learning Research - Proceedings Track 9: 605-612 (2010)
67		Péter Torma, András György, Csaba Szepesvári: A Markov-Chain Monte Carlo Approach to Simultaneous Localization and Mapping. Journal of Machine Learning Research - Proceedings Track 9: 852-859 (2010)
66		András Antos, Varun Grover, Csaba Szepesvári: Active learning in heteroscedastic noise. Theor. Comput. Sci. 411(29-30): 2712-2728 (2010)
	2009
65		Hengshuai Yao, Shalabh Bhatnagar, Csaba Szepesvári: LMS-2: Towards an algorithm that is as cheap as LMS and almost as efficient as RLS. CDC 2009: 1181-1188
64		Barnabás Póczos, Yasin Abbasi-Yadkori, Csaba Szepesvári, Russell Greiner, Nathan R. Sturtevant: Learning when to stop thinking and do something! ICML 2009: 104
63		Richard S. Sutton, Hamid Reza Maei, Doina Precup, Shalabh Bhatnagar, David Silver, Csaba Szepesvári, Eric Wiewiora: Fast gradient-descent methods for temporal-difference learning with linear function approximation. ICML 2009: 125
62		Jean-Yves Audibert, Peter Auer, Alessandro Lazaric, Rémi Munos, Daniil Ryabko, Csaba Szepesvári: Workshop summary: On-line learning with limited feedback. ICML 2009: 168
61		Alireza Farhangfar, Russell Greiner, Csaba Szepesvári: Learning to segment from a few well-selected training images. ICML 2009: 39
60		Amir Massoud Farahmand, Azad Shademan, Martin Jägersand, Csaba Szepesvári: Model-based and model-free reinforcement learning for visual servoing. ICRA 2009: 2917-2924
59		Hamid Reza Maei, Csaba Szepesvári, Shalabh Bhatnagar, Doina Precup, David Silver, Richard S. Sutton: Convergent Temporal-Difference Learning with Arbitrary Smooth Function Approximation. NIPS 2009: 1204-1212
58		Hengshuai Yao, Richard S. Sutton, Shalabh Bhatnagar, Diao Dongcui, Csaba Szepesvári: Multi-Step Dyna Planning for Policy Evaluation and Control. NIPS 2009: 2187-2195
57		Yaoliang Yu, Yuxi Li, Dale Schuurmans, Csaba Szepesvári: A General Projection Property for Distribution Families. NIPS 2009: 2232-2240
56		Yuxi Li, Csaba Szepesvári, Dale Schuurmans: Learning Exercise Policies for American Options. Journal of Machine Learning Research - Proceedings Track 5: 352-359 (2009)
55		Gergely Neu, Csaba Szepesvári: Training parsers by inverse reinforcement learning. Machine Learning 77(2-3): 303-337 (2009)
54		Jean-Yves Audibert, Rémi Munos, Csaba Szepesvári: Exploration-exploitation tradeoff using variance estimates in multi-armed bandits. Theor. Comput. Sci. 410(19): 1876-1902 (2009)
	2008
53		András Antos, Varun Grover, Csaba Szepesvári: Active Learning in Multi-armed Bandits. ALT 2008: 287-302
52		Gábor Bartók, Csaba Szepesvári, Sandra Zilles: Active Learning of Group-Structured Environments. ALT 2008: 329-343
51		Amir Massoud Farahmand, Mohammad Ghavamzadeh, Csaba Szepesvári, Shie Mannor: Regularized Fitted Q-Iteration: Application to Planning. EWRL 2008: 55-68
50		Volodymyr Mnih, Csaba Szepesvári, Jean-Yves Audibert: Empirical Bernstein stopping. ICML 2008: 672-679
49		Richard S. Sutton, Csaba Szepesvári, Hamid Reza Maei: A Convergent O(n) Temporal-difference Algorithm for Off-policy Learning with Linear Function Approximation. NIPS 2008: 1609-1616
48		Sébastien Bubeck, Rémi Munos, Gilles Stoltz, Csaba Szepesvári: Online Optimization in X-Armed Bandits. NIPS 2008: 201-208
47		Amir Massoud Farahmand, Mohammad Ghavamzadeh, Csaba Szepesvári, Shie Mannor: Regularized Policy Iteration. NIPS 2008: 441-448
46		Alejandro Isaza, Csaba Szepesvári, Vadim Bulitko, Russell Greiner: Speeding Up Planning in Markov Decision Processes via Automatically Constructed Abstraction. UAI 2008: 306-314
45		Richard S. Sutton, Csaba Szepesvári, Alborz Geramifard, Michael H. Bowling: Dyna-Style Planning with Linear Function Approximation and Prioritized Sweeping. UAI 2008: 528-536
44		Rémi Munos, Csaba Szepesvári: Finite-Time Bounds for Fitted Value Iteration. Journal of Machine Learning Research 9: 815-857 (2008)
43		András Antos, Csaba Szepesvári, Rémi Munos: Learning near-optimal policies with Bellman-residual minimization based fitted policy iteration and a single sample path. Machine Learning 71(1): 89-129 (2008)
	2007
42		Jean-Yves Audibert, Rémi Munos, Csaba Szepesvári: Tuning Bandit Algorithms in Stochastic Environments. ALT 2007: 150-165
41		Peter Auer, Ronald Ortner, Csaba Szepesvári: Improved Rates for the Stochastic Continuum-Armed Bandit Problem. COLT 2007: 454-468
40		Amir Massoud Farahmand, Csaba Szepesvári, Jean-Yves Audibert: Manifold-adaptive dimension estimation. ICML 2007: 265-272
39		István Bíró, Zoltán Szamonek, Csaba Szepesvári: Sequence Prediction Exploiting Similary Information. IJCAI 2007: 1576-1581
38		András György, Levente Kocsis, Ivett Szabó, Csaba Szepesvári: Continuous Time Associative Bandit Problems. IJCAI 2007: 830-835
37		András Antos, Rémi Munos, Csaba Szepesvári: Fitted Q-iteration in continuous action-space MDPs. NIPS 2007
36		Gergely Neu, Csaba Szepesvári: Apprenticeship Learning using Inverse Reinforcement Learning and Gradient Methods. UAI 2007: 295-302
	2006
35		Levente Kocsis, Csaba Szepesvári, Mark H. M. Winands: RSPSA: Enhanced Parameter Optimization in Games. ACG 2006: 39-56
34		András Antos, Csaba Szepesvári, Rémi Munos: Learning Near-Optimal Policies with Bellman-Residual Minimization Based Fitted Policy Iteration and a Single Sample Path. COLT 2006: 574-588
33		Levente Kocsis, Csaba Szepesvári: Bandit Based Monte-Carlo Planning. ECML 2006: 282-293
32		Péter Torma, Csaba Szepesvári: Local Importance Sampling: A Novel Technique to Enhance Particle Filtering. Journal of Multimedia 1(1): 32-43 (2006)
31		Levente Kocsis, Csaba Szepesvári: Universal parameter optimisation in games based on SPSA. Machine Learning 63(3): 249-286 (2006)
	2005
30		Zoltán Szamonek, Csaba Szepesvári: X-mHMM: An Efficient Algorithm for Training Mixtures of HMMs When the Number of Mixtures Is Unknown. ICDM 2005: 434-441
29		Csaba Szepesvári, Rémi Munos: Finite time bounds for sampling based fitted value iteration. ICML 2005: 880-887
	2004
28		Csaba Szepesvári: Shortest Path Discovery Problems: A Framework, Algorithms and Experimental Results. AAAI 2004: 550-555
27		Csaba Szepesvári, András Kocsor, Kornél Kovács: Kernel Machine Based Feature Extraction Algorithms for Regression Problems. ECAI 2004: 1091-1092
26		Péter Torma, Csaba Szepesvári: Enhancing Particle Filters Using Local Likelihood Sampling. ECCV (1) 2004: 16-27
25		András Kocsor, Kornél Kovács, Csaba Szepesvári: Margin Maximizing Discriminant Analysis. ECML 2004: 227-238
24		Csaba Szepesvári, William D. Smart: Interpolation-based Q-learning. ICML 2004
	2002
23		M. French, Csaba Szepesvári, Eric Rogers: LQ performance bounds for adaptive output feedback controllers for functionally uncertain nonlinear systems. Automatica 38(4): 683-693 (2002)
22		M. French, Csaba Szepesvári, Eric Rogers: An Asymptotic Scaling Analysis of LQ Performance for an Approximate Adaptive Control Design. MCSS 15(2): 145-176 (2002)
	2001
21		Csaba Szepesvári: Efficient approximate planning in continuous space Markovian Decision Problems. AI Commun. 14(3): 163-176 (2001)
20		András Lörincz, György Hévízi, Csaba Szepesvári: Ockham's Razor Modeling of the Matrisome Channels of the Basal Ganglia Thalamocortical Loops. Int. J. Neural Syst. 11(2): 125-143 (2001)
	2000
19		György Balogh, Ervin Dobler, Tamás Gröbler, Béla Smodics, Csaba Szepesvári: FlexVoice: A Parametric Approach to High-Quality Speech Synthesis. TSD 2000: 189-194
18		Zsolt Kalmár, Csaba Szepesvári, András Lörincz: Modular Reinforcement Learning: A Case Study in a Robot Domain. Acta Cybern. 14(3): 507-522 (2000)
17		Satinder P. Singh, Tommi Jaakkola, Michael L. Littman, Csaba Szepesvári: Convergence Results for Single-Step On-Policy Reinforcement-Learning Algorithms. Machine Learning 38(3): 287-308 (2000)
	1999
16		Csaba Szepesvári, Michael L. Littman: A Unified Analysis of Value-Function-Based Reinforcement Learning Algorithms. Neural Computation 11(8): 2017-2060 (1999)
15		Zsolt Kalmár, Zsolt Marczell, Csaba Szepesvári, András Lörincz: Parallel and robust skeletonization built on self-organizing elements. Neural Networks 12(1): 163-173 (1999)
14		János Murvai, Kristian Vlahovicek, Endre Barta, Csaba Szepesvári, Cristina Acatrinei, Sándor Pongor: The SBASE protein domain library, release 6.0: a collection of annotated protein sequence segments. Nucleic Acids Research 27(1): 257-259 (1999)
	1998
13		Zoltán Gábor, Zsolt Kalmár, Csaba Szepesvári: Multi-criteria Reinforcement Learning. ICML 1998: 197-205
12		Csaba Szepesvári: Non-Markovian Policies in Sequential Decision Problems. Acta Cybern. 13(3): 305-318 (1998)
11		Zsolt Kalmár, Csaba Szepesvári, András Lörincz: Module-Based Reinforcement Learning: Experiments with a Real Robot. Auton. Robots 5(3-4): 273-295 (1998)
10		Zsolt Kalmár, Csaba Szepesvári, András Lörincz: Module-Based Reinforcement Learning: Experiments with a Real Robot. Machine Learning 31(1-3): 55-85 (1998)
	1997
9		Csaba Szepesvári: Learning and Exploitation Do Not Conflict Under Minimax Optimality. ECML 1997: 242-249
8		Zsolt Kalmár, Csaba Szepesvári, András Lörincz: Module Based Reinforcement Learning: An Application to a Real Robot. EWLR 1997: 29-45
7		Csaba Szepesvári: The Asymptotic Convergence-Rate of Q-learning. NIPS 1997
6		Csaba Szepesvári, Szabolcs Cimmer, András Lörincz: Neurocontroller using dynamic state feedback for compensatory control. Neural Networks 10(9): 1691-1708 (1997)
	1996
5		Csaba Szepesvári, András Lörincz: Inverse Dynamics Controllers for Robust Control: Consequences for Neurocontrollers. ICANN 1996: 791-796
4		Michael L. Littman, Csaba Szepesvári: A Generalized Reinforcement-Learning Model: Convergence and Applications. ICML 1996: 310-318
3		Tibor Fomin, Tamás Rozgonyi, Csaba Szepesvári, András Lörincz: Self-Organizing Multi-Resolution Grid for Motion Planning and Control. Int. J. Neural Syst. 7(6): 757- (1996)
2		Csaba Szepesvári, András Lörincz: Approximate geometry representations and sensory fusion. Neurocomputing 12(2-3): 267-287 (1996)
	1994
1		Csaba Szepesvári, László Balázs, András Lörincz: Topology Learning Solved by Extended Objects: A Neural Network Model. Neural Computation 6(3): 441-458 (1994)

Coauthor Index

1	Yasin Abbasi-Yadkori	[64] [76] [86] [90] [93] [99]
2	Cristina Acatrinei	[14]
3	Arash Afkanpour	[88]
4	András Antos	[34] [37] [43] [53] [66] [75] [89] [91]
5	Pallavi Arora	[94]
6	Jean-Yves Audibert	[40] [42] [50] [54] [62]
7	Peter Auer	[41] [62]
8	László Balázs	[1]
9	György Balogh	[19]
10	Endre Barta	[14]
11	Gábor Bartók	[52] [69] [81] [85] [89] [91]
12	Shalabh Bhatnagar	[58] [59] [63] [65] [78]
13	István Bíró	[39]
14	Michael H. Bowling	[45] [88]
15	Sébastien Bubeck	[48] [71] [87]
16	Vadim Bulitko	[46]
17	Olivier Cappé	[72]
18	Szabolcs Cimmer	[6]
19	Ervin Dobler	[19]
20	Diao Dongcui	[58]
21	Amir Massoud Farahmand	[40] [47] [51] [60] [73] [83]
22	Mahdi Milani Fard	[92] [101]
23	Alireza Farhangfar	[61]
24	Sarah Filippi	[72]
25	Tibor Fomin	[3]
26	M. French	[22] [23]
27	Zoltán Gábor	[13]
28	Aurélien Garivier	[72]
29	Sylvain Gelly	[100]
30	Alborz Geramifard	[45]
31	Mohammad Ghavamzadeh	[47] [51]
32	Russell Greiner	[46] [61] [64] [77]
33	Tamás Gröbler	[19]
34	Varun Grover	[53] [66]
35	András György	[38] [67] [75] [80] [98]
36	György Hévízi	[20]
37	Alejandro Isaza	[46]
38	Tommi Jaakkola	[17]
39	Martin Jägersand	[60]
40	Zsolt Kalmár	[8] [10] [11] [13] [15] [18]
41	Sergey Kirshner	[68]
42	Jyrki Kivinen	[96] [97]
43	Levente Kocsis	[31] [33] [35] [38] [100]
44	András Kocsor	[25] [27]
45	Kornél Kovács	[25] [27]
46	Alessandro Lazaric	[62]
47	Liuyang Li	[77]
48	Yuxi Li	[56] [57]
49	Michael L. Littman	[4] [16] [17]
50	András Lörincz	[1] [2] [3] [5] [6] [8] [10] [11] [15] [18] [20]
51	Hamid Reza Maei	[49] [59] [63] [78]
52	Shie Mannor	[47] [51]
53	Zsolt Marczell	[15]
54	Volodymyr Mnih	[50]
55	Joseph Modayil	[76]
56	Rémi Munos	[29] [34] [37] [42] [43] [44] [48] [54] [62] [71] [73] [87]
57	János Murvai	[14]
58	Gergely Neu	[36] [55] [75] [80] [98]
59	Ronald Ortner	[41]
60	Dávid Pál	[70] [74] [81] [85] [90] [91] [93] [99]
61	Joelle Pineau	[92] [101]
62	Barnabás Póczos	[64] [68] [70] [74] [77]
63	Sándor Pongor	[14]
64	Doina Precup	[59] [63]
65	Eric Rogers	[22] [23]
66	Tamás Rozgonyi	[3]
67	Daniil Ryabko	[62]
68	Marc Schoenauer	[100]
69	Dale Schuurmans	[56] [57]
70	Michèle Sebag	[100]
71	Azad Shademan	[60]
72	David Silver	[59] [63] [100]
73	Satinder P. Singh	[17]
74	William D. Smart	[24]
75	Béla Smodics	[19]
76	Gilles Stoltz	[48] [71] [87]
77	Nathan R. Sturtevant	[64]
78	Richard S. Sutton	[45] [49] [58] [59] [63] [78]
79	Ivett Szabó	[38]
80	Zoltán Szamonek	[30] [39]
81	István Szita (Istvan Szita)	[79] [84]
82	Olivier Teytaud	[100]
83	Péter Torma	[26] [32] [67]
84	Esko Ukkonen	[96] [97]
85	Kristian Vlahovicek	[14]
86	Eric Wiewiora	[63]
87	Mark H. M. Winands	[35]
88	Hengshuai Yao	[58] [65]
89	Yaoliang Yu	[57]
90	Thomas Zeugmann	[96] [97]
91	Rong Zheng	[94]
92	Sandra Zilles	[52] [69]

Colors in the list of coauthors

Last update Fri May 25 01:42:58 2012 CET by the DBLP Team — Data released under the ODC-BY 1.0 license — See also our legal information page