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Gábor Lugosi: [Publications] [Author Rank by year] [Co-authors] [Prefers] [Cites] [Cited by]

Publications of Author

  1. Stéphane Boucheron, Gábor Lugosi, Olivier Bousquet
    Concentration Inequalities. [Citation Graph (0, 0)][DBLP]
    Advanced Lectures on Machine Learning, 2003, pp:208-240 [Conf]
  2. Olivier Bousquet, Stéphane Boucheron, Gábor Lugosi
    Introduction to Statistical Learning Theory. [Citation Graph (0, 0)][DBLP]
    Advanced Lectures on Machine Learning, 2003, pp:169-207 [Conf]
  3. András Antos, Gábor Lugosi
    Strong Minimax Lower Bounds for Learning. [Citation Graph (0, 0)][DBLP]
    COLT, 1996, pp:303-309 [Conf]
  4. Peter L. Bartlett, Stéphane Boucheron, Gábor Lugosi
    Model Selection and Error Estimation. [Citation Graph (0, 0)][DBLP]
    COLT, 2000, pp:286-297 [Conf]
  5. Nicolò Cesa-Bianchi, Gábor Lugosi
    Potential-Based Algorithms in Online Prediction and Game Theory. [Citation Graph (0, 0)][DBLP]
    COLT/EuroCOLT, 2001, pp:48-64 [Conf]
  6. Nicolò Cesa-Bianchi, Gábor Lugosi
    On Sequential Prediction of Individual Sequences Relative to a Set of Experts. [Citation Graph (0, 0)][DBLP]
    COLT, 1998, pp:1-11 [Conf]
  7. Nicolò Cesa-Bianchi, Gábor Lugosi
    Minimax Regret Under log Loss for General Classes of Experts. [Citation Graph (0, 0)][DBLP]
    COLT, 1999, pp:12-18 [Conf]
  8. Nicolò Cesa-Bianchi, Gábor Lugosi, Gilles Stoltz
    Minimizing Regret with Label Efficient Prediction. [Citation Graph (0, 0)][DBLP]
    COLT, 2004, pp:77-92 [Conf]
  9. Stéphan Clémençon, Gábor Lugosi, Nicolas Vayatis
    Ranking and Scoring Using Empirical Risk Minimization. [Citation Graph (0, 0)][DBLP]
    COLT, 2005, pp:1-15 [Conf]
  10. András György, Tamás Linder, Gábor Lugosi
    Tracking the Best of Many Experts. [Citation Graph (0, 0)][DBLP]
    COLT, 2005, pp:204-216 [Conf]
  11. Balázs Kégl, Tamás Linder, Gábor Lugosi
    Data-Dependent Margin-Based Generalization Bounds for Classification. [Citation Graph (0, 0)][DBLP]
    COLT/EuroCOLT, 2001, pp:368-384 [Conf]
  12. Gábor Lugosi, Márta Pintér
    A Data-Dependent Skeleton Estimate for Learning. [Citation Graph (0, 0)][DBLP]
    COLT, 1996, pp:51-56 [Conf]
  13. Gábor Lugosi, Nicolas Vayatis
    A Consistent Strategy for Boosting Algorithms. [Citation Graph (0, 0)][DBLP]
    COLT, 2002, pp:303-318 [Conf]
  14. Gilles Stoltz, Gábor Lugosi
    Internal Regret in On-Line Portfolio Selection. [Citation Graph (0, 0)][DBLP]
    COLT, 2003, pp:403-417 [Conf]
  15. András György, Tamás Linder, Gábor Lugosi
    A "Follow the Perturbed Leader"-type Algorithm for Zero-Delay Quantization of Individual Sequence. [Citation Graph (0, 0)][DBLP]
    Data Compression Conference, 2004, pp:342-351 [Conf]
  16. Tamás Linder, Gábor Lugosi, Kenneth Zeger
    Universality and Rates of Convergence in Lossy Source Coding. [Citation Graph (0, 0)][DBLP]
    Data Compression Conference, 1993, pp:89-97 [Conf]
  17. Tamás Linder, Gábor Lugosi, Kenneth Zeger
    Designing Vector Quantizers in the Presence of Source Noise or Channel Noise. [Citation Graph (0, 0)][DBLP]
    Data Compression Conference, 1996, pp:33-42 [Conf]
  18. Peter L. Bartlett, Tamás Linder, Gábor Lugosi
    A Minimax Lower Bound for Empirical Quantizer Design. [Citation Graph (0, 0)][DBLP]
    EuroCOLT, 1997, pp:210-222 [Conf]
  19. Márta Horváth, Gábor Lugosi
    Scale-sensitive Dimensions and Skeleton Estimates for Classification. [Citation Graph (0, 0)][DBLP]
    Discrete Applied Mathematics, 1998, v:86, n:1, pp:37-61 [Journal]
  20. András Antos, Balázs Kégl, Tamás Linder, Gábor Lugosi
    Data-dependent margin-based generalization bounds for classification. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2002, v:3, n:, pp:73-98 [Journal]
  21. Gilles Blanchard, Gábor Lugosi, Nicolas Vayatis
    On the Rate of Convergence of Regularized Boosting Classifiers. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2003, v:4, n:, pp:861-894 [Journal]
  22. András Antos, Gábor Lugosi
    Strong Minimax Lower Bounds for Learning. [Citation Graph (0, 0)][DBLP]
    Machine Learning, 1998, v:30, n:1, pp:31-56 [Journal]
  23. Peter L. Bartlett, Stéphane Boucheron, Gábor Lugosi
    Model Selection and Error Estimation. [Citation Graph (0, 0)][DBLP]
    Machine Learning, 2002, v:48, n:1-3, pp:85-113 [Journal]
  24. Nicolò Cesa-Bianchi, Gábor Lugosi
    Worst-Case Bounds for the Logarithmic Loss of Predictors. [Citation Graph (0, 0)][DBLP]
    Machine Learning, 2001, v:43, n:3, pp:247-264 [Journal]
  25. Nicolò Cesa-Bianchi, Gábor Lugosi
    Potential-Based Algorithms in On-Line Prediction and Game Theory. [Citation Graph (0, 0)][DBLP]
    Machine Learning, 2003, v:51, n:3, pp:239-261 [Journal]
  26. Gilles Stoltz, Gábor Lugosi
    Internal Regret in On-Line Portfolio Selection. [Citation Graph (0, 0)][DBLP]
    Machine Learning, 2005, v:59, n:1-2, pp:125-159 [Journal]
  27. András Faragó, Tamás Linder, Gábor Lugosi
    Fast Nearest-Neighbor Search in Dissimilarity Spaces. [Citation Graph (0, 0)][DBLP]
    IEEE Trans. Pattern Anal. Mach. Intell., 1993, v:15, n:9, pp:957-962 [Journal]
  28. Luc Devroye, Gábor Lugosi
    Lower bounds in pattern recognition and learning. [Citation Graph (0, 0)][DBLP]
    Pattern Recognition, 1995, v:28, n:7, pp:1011-1018 [Journal]
  29. Gábor Lugosi
    Learning with an unreliable teacher. [Citation Graph (0, 0)][DBLP]
    Pattern Recognition, 1992, v:25, n:1, pp:79-87 [Journal]
  30. Stéphane Boucheron, Gábor Lugosi, Pascal Massart
    A sharp concentration inequality with applications. [Citation Graph (0, 0)][DBLP]
    Random Struct. Algorithms, 2000, v:16, n:3, pp:277-292 [Journal]
  31. Peter L. Bartlett, Tamás Linder, Gábor Lugosi
    The Minimax Distortion Redundancy in Empirical Quantizer Design. [Citation Graph (0, 0)][DBLP]
    IEEE Transactions on Information Theory, 1998, v:44, n:5, pp:1802-1813 [Journal]
  32. Nicolò Cesa-Bianchi, Gábor Lugosi, Gilles Stoltz
    Minimizing regret with label efficient prediction. [Citation Graph (0, 0)][DBLP]
    IEEE Transactions on Information Theory, 2005, v:51, n:6, pp:2152-2162 [Journal]
  33. Luc Devroye, László Györfi, Gábor Lugosi
    A note on robust hypothesis testing. [Citation Graph (0, 0)][DBLP]
    IEEE Transactions on Information Theory, 2002, v:48, n:7, pp:2111-2114 [Journal]
  34. András Faragó, Gábor Lugosi
    Strong universal consistency of neural network classifiers. [Citation Graph (0, 0)][DBLP]
    IEEE Transactions on Information Theory, 1993, v:39, n:4, pp:1146-1151 [Journal]
  35. László Györfi, Gábor Lugosi, Gusztáv Morvai
    A simple randomized algorithm for sequential prediction of ergodic time series. [Citation Graph (0, 0)][DBLP]
    IEEE Transactions on Information Theory, 1999, v:45, n:7, pp:2642-2650 [Journal]
  36. Sanjeev R. Kulkarni, Gábor Lugosi, Santosh S. Venkatesh
    Learning Pattern Classification - A Survey. [Citation Graph (0, 0)][DBLP]
    IEEE Transactions on Information Theory, 1998, v:44, n:6, pp:2178-2206 [Journal]
  37. Tamás Linder, Gábor Lugosi
    A zero-delay sequential scheme for lossy coding of individual sequences. [Citation Graph (0, 0)][DBLP]
    IEEE Transactions on Information Theory, 2001, v:47, n:6, pp:2533-2538 [Journal]
  38. Tamás Linder, Gábor Lugosi, Kenneth Zeger
    Rates of convergence in the source coding theorem, in empirical quantizer design, and in universal lossy source coding. [Citation Graph (0, 0)][DBLP]
    IEEE Transactions on Information Theory, 1994, v:40, n:6, pp:1728-1740 [Journal]
  39. Tamás Linder, Gábor Lugosi, Kenneth Zeger
    Fixed-rate universal lossy source coding and rates of convergence for memoryless sources. [Citation Graph (0, 0)][DBLP]
    IEEE Transactions on Information Theory, 1995, v:41, n:3, pp:665-676 [Journal]
  40. Tamás Linder, Gábor Lugosi, Kenneth Zeger
    Empirical quantizer design in the presence of source noise or channel noise. [Citation Graph (0, 0)][DBLP]
    IEEE Transactions on Information Theory, 1997, v:43, n:2, pp:612-623 [Journal]
  41. Gábor Lugosi, Miroslaw Pawlak
    On the posterior-probability estimate of the error rate of nonparametric classification rules. [Citation Graph (0, 0)][DBLP]
    IEEE Transactions on Information Theory, 1994, v:40, n:2, pp:475-481 [Journal]
  42. Gábor Lugosi, Kenneth Zeger
    Nonparametric estimation via empirical risk minimization. [Citation Graph (0, 0)][DBLP]
    IEEE Transactions on Information Theory, 1995, v:41, n:3, pp:677-687 [Journal]
  43. Gábor Lugosi, Kenneth Zeger
    Concept learning using complexity regularization. [Citation Graph (0, 0)][DBLP]
    IEEE Transactions on Information Theory, 1996, v:42, n:1, pp:48-54 [Journal]
  44. Gábor Lugosi, Shie Mannor, Gilles Stoltz
    Strategies for Prediction Under Imperfect Monitoring. [Citation Graph (0, 0)][DBLP]
    COLT, 2007, pp:248-262 [Conf]
  45. Luc Devroye, Gábor Lugosi, GaHyun Park, Wojciech Szpankowski
    Multiple choice tries and distributed hash tables. [Citation Graph (0, 0)][DBLP]
    SODA, 2007, pp:891-899 [Conf]
  46. Gábor Lugosi, Shie Mannor, Gilles Stoltz
    Strategies for prediction under imperfect monitoring [Citation Graph (0, 0)][DBLP]
    CoRR, 2007, v:0, n:, pp:- [Journal]
  47. András György, Tamás Linder, Gábor Lugosi, György Ottucsák
    The on-line shortest path problem under partial monitoring [Citation Graph (0, 0)][DBLP]
    CoRR, 2007, v:0, n:, pp:- [Journal]

  48. Sequential prediction under incomplete feedback. [Citation Graph (, )][DBLP]


  49. Concentration Inequalities. [Citation Graph (, )][DBLP]


  50. On-line Sequential Bin Packing. [Citation Graph (, )][DBLP]


  51. From Ranking to Classification: A Statistical View. [Citation Graph (, )][DBLP]


  52. Online Multi-task Learning with Hard Constraints [Citation Graph (, )][DBLP]


  53. The Longest Minimum-Weight Path in a Complete Graph. [Citation Graph (, )][DBLP]


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