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Gábor Lugosi :
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Stéphane Boucheron , Gábor Lugosi , Olivier Bousquet Concentration Inequalities. [Citation Graph (0, 0)][DBLP ] Advanced Lectures on Machine Learning, 2003, pp:208-240 [Conf ] 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 ] András Antos , Gábor Lugosi Strong Minimax Lower Bounds for Learning. [Citation Graph (0, 0)][DBLP ] COLT, 1996, pp:303-309 [Conf ] Peter L. Bartlett , Stéphane Boucheron , Gábor Lugosi Model Selection and Error Estimation. [Citation Graph (0, 0)][DBLP ] COLT, 2000, pp:286-297 [Conf ] 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 ] 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 ] 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 ] Nicolò Cesa-Bianchi , Gábor Lugosi , Gilles Stoltz Minimizing Regret with Label Efficient Prediction. [Citation Graph (0, 0)][DBLP ] COLT, 2004, pp:77-92 [Conf ] Stéphan Clémençon , Gábor Lugosi , Nicolas Vayatis Ranking and Scoring Using Empirical Risk Minimization. [Citation Graph (0, 0)][DBLP ] COLT, 2005, pp:1-15 [Conf ] András György , Tamás Linder , Gábor Lugosi Tracking the Best of Many Experts. [Citation Graph (0, 0)][DBLP ] COLT, 2005, pp:204-216 [Conf ] 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 ] Gábor Lugosi , Márta Pintér A Data-Dependent Skeleton Estimate for Learning. [Citation Graph (0, 0)][DBLP ] COLT, 1996, pp:51-56 [Conf ] Gábor Lugosi , Nicolas Vayatis A Consistent Strategy for Boosting Algorithms. [Citation Graph (0, 0)][DBLP ] COLT, 2002, pp:303-318 [Conf ] Gilles Stoltz , Gábor Lugosi Internal Regret in On-Line Portfolio Selection. [Citation Graph (0, 0)][DBLP ] COLT, 2003, pp:403-417 [Conf ] 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 ] 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 ] 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 ] 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 ] 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 ] 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 ] 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 ] 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 ] 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 ] 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 ] 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 ] 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 ] 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 ] 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 ] Gábor Lugosi Learning with an unreliable teacher. [Citation Graph (0, 0)][DBLP ] Pattern Recognition, 1992, v:25, n:1, pp:79-87 [Journal ] 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 ] 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 ] 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 ] 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 ] 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 ] 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 ] 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 ] 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 ] 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 ] 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 ] 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 ] 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 ] 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 ] 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 ] Gábor Lugosi , Shie Mannor , Gilles Stoltz Strategies for Prediction Under Imperfect Monitoring. [Citation Graph (0, 0)][DBLP ] COLT, 2007, pp:248-262 [Conf ] 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 ] Gábor Lugosi , Shie Mannor , Gilles Stoltz Strategies for prediction under imperfect monitoring [Citation Graph (0, 0)][DBLP ] CoRR, 2007, v:0, n:, pp:- [Journal ] 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 ] Sequential prediction under incomplete feedback. [Citation Graph (, )][DBLP ] Concentration Inequalities. [Citation Graph (, )][DBLP ] On-line Sequential Bin Packing. [Citation Graph (, )][DBLP ] From Ranking to Classification: A Statistical View. [Citation Graph (, )][DBLP ] Online Multi-task Learning with Hard Constraints [Citation Graph (, )][DBLP ] The Longest Minimum-Weight Path in a Complete Graph. [Citation Graph (, )][DBLP ] Search in 0.009secs, Finished in 0.012secs