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Csaba Szepesvári: [Publications] [Author Rank by year] [Co-authors] [Prefers] [Cites] [Cited by]

Publications of Author

  1. Csaba Szepesvári
    Shortest Path Discovery Problems: A Framework, Algorithms and Experimental Results. [Citation Graph (0, 0)][DBLP]
    AAAI, 2004, pp:550-555 [Conf]
  2. Levente Kocsis, Csaba Szepesvári, Mark H. M. Winands
    RSPSA: Enhanced Parameter Optimization in Games. [Citation Graph (0, 0)][DBLP]
    ACG, 2006, pp:39-56 [Conf]
  3. András Antos, Csaba Szepesvári, Rémi Munos
    Learning Near-Optimal Policies with Bellman-Residual Minimization Based Fitted Policy Iteration and a Single Sample Path. [Citation Graph (0, 0)][DBLP]
    COLT, 2006, pp:574-588 [Conf]
  4. Csaba Szepesvári, András Kocsor, Kornél Kovács
    Kernel Machine Based Feature Extraction Algorithms for Regression Problems. [Citation Graph (0, 0)][DBLP]
    ECAI, 2004, pp:1091-1092 [Conf]
  5. Péter Torma, Csaba Szepesvári
    Enhancing Particle Filters Using Local Likelihood Sampling. [Citation Graph (0, 0)][DBLP]
    ECCV (1), 2004, pp:16-27 [Conf]
  6. Levente Kocsis, Csaba Szepesvári
    Bandit Based Monte-Carlo Planning. [Citation Graph (0, 0)][DBLP]
    ECML, 2006, pp:282-293 [Conf]
  7. András Kocsor, Kornél Kovács, Csaba Szepesvári
    Margin Maximizing Discriminant Analysis. [Citation Graph (0, 0)][DBLP]
    ECML, 2004, pp:227-238 [Conf]
  8. Csaba Szepesvári
    Learning and Exploitation Do Not Conflict Under Minimax Optimality. [Citation Graph (0, 0)][DBLP]
    ECML, 1997, pp:242-249 [Conf]
  9. Zsolt Kalmár, Csaba Szepesvári, András Lörincz
    Module Based Reinforcement Learning: An Application to a Real Robot. [Citation Graph (0, 0)][DBLP]
    EWLR, 1997, pp:29-45 [Conf]
  10. Csaba Szepesvári, András Lörincz
    Inverse Dynamics Controllers for Robust Control: Consequences for Neurocontrollers. [Citation Graph (0, 0)][DBLP]
    ICANN, 1996, pp:791-796 [Conf]
  11. Zoltán Szamonek, Csaba Szepesvári
    X-mHMM: An Efficient Algorithm for Training Mixtures of HMMs When the Number of Mixtures Is Unknown. [Citation Graph (0, 0)][DBLP]
    ICDM, 2005, pp:434-441 [Conf]
  12. Zoltán Gábor, Zsolt Kalmár, Csaba Szepesvári
    Multi-criteria Reinforcement Learning. [Citation Graph (0, 0)][DBLP]
    ICML, 1998, pp:197-205 [Conf]
  13. Michael L. Littman, Csaba Szepesvári
    A Generalized Reinforcement-Learning Model: Convergence and Applications. [Citation Graph (0, 0)][DBLP]
    ICML, 1996, pp:310-318 [Conf]
  14. Csaba Szepesvári, Rémi Munos
    Finite time bounds for sampling based fitted value iteration. [Citation Graph (0, 0)][DBLP]
    ICML, 2005, pp:880-887 [Conf]
  15. Csaba Szepesvári, William D. Smart
    Interpolation-based Q-learning. [Citation Graph (0, 0)][DBLP]
    ICML, 2004, pp:- [Conf]
  16. András György, Levente Kocsis, Ivett Szabó, Csaba Szepesvári
    Continuous Time Associative Bandit Problems. [Citation Graph (0, 0)][DBLP]
    IJCAI, 2007, pp:830-835 [Conf]
  17. István Bíró, Zoltán Szamonek, Csaba Szepesvári
    Sequence Prediction Exploiting Similary Information. [Citation Graph (0, 0)][DBLP]
    IJCAI, 2007, pp:1576-1581 [Conf]
  18. Csaba Szepesvári
    The Asymptotic Convergence-Rate of Q-learning. [Citation Graph (0, 0)][DBLP]
    NIPS, 1997, pp:- [Conf]
  19. György Balogh, Ervin Dobler, Tamás Gröbler, Béla Smodics, Csaba Szepesvári
    FlexVoice: A Parametric Approach to High-Quality Speech Synthesis. [Citation Graph (0, 0)][DBLP]
    TSD, 2000, pp:189-194 [Conf]
  20. Zsolt Kalmár, Csaba Szepesvári, András Lörincz
    Modular Reinforcement Learning: A Case Study in a Robot Domain. [Citation Graph (0, 0)][DBLP]
    Acta Cybern., 2000, v:14, n:3, pp:507-522 [Journal]
  21. Csaba Szepesvári
    Non-Markovian Policies in Sequential Decision Problems. [Citation Graph (0, 0)][DBLP]
    Acta Cybern., 1998, v:13, n:3, pp:305-318 [Journal]
  22. Csaba Szepesvári
    Efficient approximate planning in continuous space Markovian Decision Problems. [Citation Graph (0, 0)][DBLP]
    AI Commun., 2001, v:14, n:3, pp:163-176 [Journal]
  23. Zsolt Kalmár, Csaba Szepesvári, András Lörincz
    Module-Based Reinforcement Learning: Experiments with a Real Robot. [Citation Graph (0, 0)][DBLP]
    Auton. Robots, 1998, v:5, n:3-4, pp:273-295 [Journal]
  24. Tibor Fomin, Tamás Rozgonyi, Csaba Szepesvári, András Lörincz
    Self-Organizing Multi-Resolution Grid for Motion Planning and Control. [Citation Graph (0, 0)][DBLP]
    Int. J. Neural Syst., 1996, v:7, n:6, pp:757-0 [Journal]
  25. András Lörincz, György Hévízi, Csaba Szepesvári
    Ockham's Razor Modeling of the Matrisome Channels of the Basal Ganglia Thalamocortical Loops. [Citation Graph (0, 0)][DBLP]
    Int. J. Neural Syst., 2001, v:11, n:2, pp:125-143 [Journal]
  26. Csaba Szepesvári, András Lörincz
    Approximate geometry representations and sensory fusion. [Citation Graph (0, 0)][DBLP]
    Neurocomputing, 1996, v:12, n:2-3, pp:267-287 [Journal]
  27. Zsolt Kalmár, Csaba Szepesvári, András Lörincz
    Module-Based Reinforcement Learning: Experiments with a Real Robot. [Citation Graph (0, 0)][DBLP]
    Machine Learning, 1998, v:31, n:1-3, pp:55-85 [Journal]
  28. Levente Kocsis, Csaba Szepesvári
    Universal parameter optimisation in games based on SPSA. [Citation Graph (0, 0)][DBLP]
    Machine Learning, 2006, v:63, n:3, pp:249-286 [Journal]
  29. Satinder P. Singh, Tommi Jaakkola, Michael L. Littman, Csaba Szepesvári
    Convergence Results for Single-Step On-Policy Reinforcement-Learning Algorithms. [Citation Graph (0, 0)][DBLP]
    Machine Learning, 2000, v:38, n:3, pp:287-308 [Journal]
  30. 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. [Citation Graph (0, 0)][DBLP]
    Nucleic Acids Research, 1999, v:27, n:1, pp:257-259 [Journal]
  31. Csaba Szepesvári, Michael L. Littman
    A Unified Analysis of Value-Function-Based Reinforcement Learning Algorithms. [Citation Graph (0, 0)][DBLP]
    Neural Computation, 1999, v:11, n:8, pp:2017-2060 [Journal]
  32. Zsolt Kalmár, Zsolt Marczell, Csaba Szepesvári, András Lörincz
    Parallel and robust skeletonization built on self-organizing elements. [Citation Graph (0, 0)][DBLP]
    Neural Networks, 1999, v:12, n:1, pp:163-173 [Journal]
  33. Csaba Szepesvári, Szabolcs Cimmer, András Lörincz
    Neurocontroller using dynamic state feedback for compensatory control. [Citation Graph (0, 0)][DBLP]
    Neural Networks, 1997, v:10, n:9, pp:1691-1708 [Journal]
  34. Jean-Yves Audibert, Rémi Munos, Csaba Szepesvári
    Tuning Bandit Algorithms in Stochastic Environments. [Citation Graph (0, 0)][DBLP]
    ALT, 2007, pp:150-165 [Conf]
  35. Peter Auer, Ronald Ortner, Csaba Szepesvári
    Improved Rates for the Stochastic Continuum-Armed Bandit Problem. [Citation Graph (0, 0)][DBLP]
    COLT, 2007, pp:454-468 [Conf]
  36. Amir Massoud Farahmand, Csaba Szepesvári, Jean-Yves Audibert
    Manifold-adaptive dimension estimation. [Citation Graph (0, 0)][DBLP]
    ICML, 2007, pp:265-272 [Conf]

  37. Toward a Classification of Finite Partial-Monitoring Games. [Citation Graph (, )][DBLP]

  38. Active Learning in Multi-armed Bandits. [Citation Graph (, )][DBLP]

  39. Active Learning of Group-Structured Environments. [Citation Graph (, )][DBLP]

  40. Empirical Bernstein stopping. [Citation Graph (, )][DBLP]

  41. Fast gradient-descent methods for temporal-difference learning with linear function approximation. [Citation Graph (, )][DBLP]

  42. Workshop summary: On-line learning with limited feedback. [Citation Graph (, )][DBLP]

  43. Learning when to stop thinking and do something! [Citation Graph (, )][DBLP]

  44. Learning to segment from a few well-selected training images. [Citation Graph (, )][DBLP]

  45. Model-based reinforcement learning with nearly tight exploration complexity bounds. [Citation Graph (, )][DBLP]

  46. Toward Off-Policy Learning Control with Function Approximation. [Citation Graph (, )][DBLP]

  47. Budgeted Distribution Learning of Belief Net Parameters. [Citation Graph (, )][DBLP]

  48. Model-based and model-free reinforcement learning for visual servoing. [Citation Graph (, )][DBLP]

  49. Fitted Q-iteration in continuous action-space MDPs. [Citation Graph (, )][DBLP]

  50. Regularized Policy Iteration. [Citation Graph (, )][DBLP]

  51. Online Optimization in X-Armed Bandits. [Citation Graph (, )][DBLP]

  52. A Convergent O(n) Temporal-difference Algorithm for Off-policy Learning with Linear Function Approximation. [Citation Graph (, )][DBLP]

  53. Speeding Up Planning in Markov Decision Processes via Automatically Constructed Abstraction. [Citation Graph (, )][DBLP]

  54. Dyna-Style Planning with Linear Function Approximation and Prioritized Sweeping. [Citation Graph (, )][DBLP]

  55. Regularized Fitted Q-Iteration: Application to Planning. [Citation Graph (, )][DBLP]

  56. LMS-2: Towards an algorithm that is as cheap as LMS and almost as efficient as RLS. [Citation Graph (, )][DBLP]

  57. X-Armed Bandits [Citation Graph (, )][DBLP]

  58. Estimation of Rényi Entropy and Mutual Information Based on Generalized Nearest-Neighbor Graphs [Citation Graph (, )][DBLP]

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