Gábor Lugosi

	2012
77		Nicolò Cesa-Bianchi, Pierre Gaillard, Gábor Lugosi, Gilles Stoltz: A new look at shifting regret CoRR abs/1202.3323: (2012)
76		Jean-Yves Audibert, Sébastien Bubeck, Gábor Lugosi: Regret in Online Combinatorial Optimization CoRR abs/1204.4710: (2012)
	2011
75		Nicolas Broutin, Luc Devroye, Nicolas Fraiman, Gábor Lugosi: Connectivity threshold for Bluetooth graphs CoRR abs/1103.0351: (2011)
74		András György, Tamás Linder, Gábor Lugosi: Efficient Tracking of Large Classes of Experts CoRR abs/1110.2755: (2011)
73		Matthias Hein, Gábor Lugosi, Lorenzo Rosasco, Steve Smale: Mathematical and Computational Foundations of Learning Theory (Dagstuhl Seminar 11291). Dagstuhl Reports 1(7): 53-69 (2011)
72		Jean-Yves Audibert, Sébastien Bubeck, Gábor Lugosi: Minimax Policies for Combinatorial Prediction Games. Journal of Machine Learning Research - Proceedings Track 19: 107-132 (2011)
71		Gábor Lugosi, Sandra Zilles: Preface. Theor. Comput. Sci. 412(19): 1755 (2011)
	2010
70		Louigi Addario-Berry, Nicolas Broutin, Gábor Lugosi: The Longest Minimum-Weight Path in a Complete Graph. Combinatorics, Probability & Computing 19(1): 1-19 (2010)
69		András György, Gábor Lugosi, György Ottucsák: On-Line Sequential Bin Packing. Journal of Machine Learning Research 11: 89-109 (2010)
	2009
68		Ricard Gavaldà, Gábor Lugosi, Thomas Zeugmann, Sandra Zilles: Algorithmic Learning Theory, 20th International Conference, ALT 2009, Porto, Portugal, October 3-5, 2009. Proceedings Springer 2009
67		Nicolò Cesa-Bianchi, Gábor Lugosi: Combinatorial Bandits. COLT 2009
66		Gábor Lugosi, Omiros Papaspiliopoulos, Gilles Stoltz: Online Multi-task Learning with Hard Constraints. COLT 2009
65		Gábor Lugosi, Omiros Papaspiliopoulos, Gilles Stoltz: Online Multi-task Learning with Hard Constraints CoRR abs/0902.3526: (2009)
64		Luc Devroye, Gábor Lugosi, GaHyun Park, Wojciech Szpankowski: Multiple choice tries and distributed hash tables. Random Struct. Algorithms 34(3): 337-367 (2009)
	2008
63		András György, Gábor Lugosi, György Ottucsák: On-line Sequential Bin Packing. COLT 2008: 447-454
62		Gábor Lugosi: Concentration Inequalities. COLT 2008: 7-8
61		Gérard Biau, Luc Devroye, Gábor Lugosi: On the Performance of Clustering in Hilbert Spaces. IEEE Transactions on Information Theory 54(2): 781-790 (2008)
60		András György, Tamás Linder, Gábor Lugosi: Tracking the Best Quantizer. IEEE Transactions on Information Theory 54(4): 1604-1625 (2008)
59		Gérard Biau, Luc Devroye, Gábor Lugosi: Consistency of Random Forests and Other Averaging Classifiers. Journal of Machine Learning Research 9: 2015-2033 (2008)
58		Gábor Lugosi, Shie Mannor, Gilles Stoltz: Strategies for Prediction Under Imperfect Monitoring. Math. Oper. Res. 33(3): 513-528 (2008)
	2007
57		Gábor Lugosi: Sequential prediction under incomplete feedback. CCIA 2007: 3-5
56		Gábor Lugosi, Shie Mannor, Gilles Stoltz: Strategies for Prediction Under Imperfect Monitoring. COLT 2007: 248-262
55		Luc Devroye, Gábor Lugosi, GaHyun Park, Wojciech Szpankowski: Multiple choice tries and distributed hash tables. SODA 2007: 891-899
54		András György, Tamás Linder, Gábor Lugosi, György Ottucsák: The on-line shortest path problem under partial monitoring CoRR abs/0704.1020: (2007)
53		Gábor Lugosi, Shie Mannor, Gilles Stoltz: Strategies for prediction under imperfect monitoring CoRR abs/math/0701419: (2007)
52		Gilles Stoltz, Gábor Lugosi: Learning correlated equilibria in games with compact sets of strategies. Games and Economic Behavior 59(1): 187-208 (2007)
51		Fabrizio Germano, Gábor Lugosi: Global Nash convergence of Foster and Young's regret testing. Games and Economic Behavior 60(1): 135-154 (2007)
50		András György, Tamás Linder, Gábor Lugosi, György Ottucsák: The On-Line Shortest Path Problem Under Partial Monitoring. Journal of Machine Learning Research 8: 2369-2403 (2007)
49		Avrim Blum, Gábor Lugosi, Hans-Ulrich Simon: Introduction to the special issue on COLT 2006. Machine Learning 69(2-3): 75-77 (2007)
	2006
48		Nicolò Cesa-Bianchi, Gábor Lugosi: Prediction, learning, and games. Cambridge University Press 2006: I-XII, 1-394
47		Gábor Lugosi, Hans-Ulrich Simon: Learning Theory, 19th Annual Conference on Learning Theory, COLT 2006, Pittsburgh, PA, USA, June 22-25, 2006, Proceedings Springer 2006
46		Nicolò Cesa-Bianchi, Gábor Lugosi, Gilles Stoltz: Regret Minimization Under Partial Monitoring. Math. Oper. Res. 31(3): 562-580 (2006)
	2005
45		Stéphan Clémençon, Gábor Lugosi, Nicolas Vayatis: Ranking and Scoring Using Empirical Risk Minimization. COLT 2005: 1-15
44		András György, Tamás Linder, Gábor Lugosi: Tracking the Best of Many Experts. COLT 2005: 204-216
43		Stéphan Clémençon, Gábor Lugosi, Nicolas Vayatis: From Ranking to Classification: A Statistical View. GfKl 2005: 214-221
42		Nicolò Cesa-Bianchi, Gábor Lugosi, Gilles Stoltz: Minimizing regret with label efficient prediction. IEEE Transactions on Information Theory 51(6): 2152-2162 (2005)
41		Gilles Stoltz, Gábor Lugosi: Internal Regret in On-Line Portfolio Selection. Machine Learning 59(1-2): 125-159 (2005)
	2004
40		Nicolò Cesa-Bianchi, Gábor Lugosi, Gilles Stoltz: Minimizing Regret with Label Efficient Prediction. COLT 2004: 77-92
39		András György, Tamás Linder, Gábor Lugosi: A "Follow the Perturbed Leader"-type Algorithm for Zero-Delay Quantization of Individual Sequence. Data Compression Conference 2004: 342-351
38		András György, Tamás Linder, Gábor Lugosi: Efficient adaptive algorithms and minimax bounds for zero-delay lossy source coding. IEEE Transactions on Signal Processing 52(8): 2337-2347 (2004)
	2003
37		Olivier Bousquet, Stéphane Boucheron, Gábor Lugosi: Introduction to Statistical Learning Theory. Advanced Lectures on Machine Learning 2003: 169-207
36		Stéphane Boucheron, Gábor Lugosi, Olivier Bousquet: Concentration Inequalities. Advanced Lectures on Machine Learning 2003: 208-240
35		Gilles Stoltz, Gábor Lugosi: Internal Regret in On-Line Portfolio Selection. COLT 2003: 403-417
34		Gilles Blanchard, Gábor Lugosi, Nicolas Vayatis: On the Rate of Convergence of Regularized Boosting Classifiers. Journal of Machine Learning Research 4: 861-894 (2003)
33		Nicolò Cesa-Bianchi, Gábor Lugosi: Potential-Based Algorithms in On-Line Prediction and Game Theory. Machine Learning 51(3): 239-261 (2003)
	2002
32		Gábor Lugosi, Nicolas Vayatis: A Consistent Strategy for Boosting Algorithms. COLT 2002: 303-318
31		Luc Devroye, László Györfi, Gábor Lugosi: A note on robust hypothesis testing. IEEE Transactions on Information Theory 48(7): 2111-2114 (2002)
30		András Antos, Balázs Kégl, Tamás Linder, Gábor Lugosi: Data-dependent margin-based generalization bounds for classification. Journal of Machine Learning Research 3: 73-98 (2002)
29		Peter L. Bartlett, Stéphane Boucheron, Gábor Lugosi: Model Selection and Error Estimation. Machine Learning 48(1-3): 85-113 (2002)
	2001
28		Balázs Kégl, Tamás Linder, Gábor Lugosi: Data-Dependent Margin-Based Generalization Bounds for Classification. COLT/EuroCOLT 2001: 368-384
27		Nicolò Cesa-Bianchi, Gábor Lugosi: Potential-Based Algorithms in Online Prediction and Game Theory. COLT/EuroCOLT 2001: 48-64
26		Tamás Linder, Gábor Lugosi: A zero-delay sequential scheme for lossy coding of individual sequences. IEEE Transactions on Information Theory 47(6): 2533-2538 (2001)
25		Nicolò Cesa-Bianchi, Gábor Lugosi: Worst-Case Bounds for the Logarithmic Loss of Predictors. Machine Learning 43(3): 247-264 (2001)
	2000
24		Peter L. Bartlett, Stéphane Boucheron, Gábor Lugosi: Model Selection and Error Estimation. COLT 2000: 286-297
23		Stéphane Boucheron, Gábor Lugosi, Pascal Massart: A sharp concentration inequality with applications. Random Struct. Algorithms 16(3): 277-292 (2000)
	1999
22		Nicolò Cesa-Bianchi, Gábor Lugosi: Minimax Regret Under log Loss for General Classes of Experts. COLT 1999: 12-18
21		László Györfi, Gábor Lugosi, Gusztáv Morvai: A simple randomized algorithm for sequential prediction of ergodic time series. IEEE Transactions on Information Theory 45(7): 2642-2650 (1999)
	1998
20		Nicolò Cesa-Bianchi, Gábor Lugosi: On Sequential Prediction of Individual Sequences Relative to a Set of Experts. COLT 1998: 1-11
19		Márta Horváth, Gábor Lugosi: Scale-sensitive Dimensions and Skeleton Estimates for Classification. Discrete Applied Mathematics 86(1): 37-61 (1998)
18		Peter L. Bartlett, Tamás Linder, Gábor Lugosi: The Minimax Distortion Redundancy in Empirical Quantizer Design. IEEE Transactions on Information Theory 44(5): 1802-1813 (1998)
17		Sanjeev R. Kulkarni, Gábor Lugosi, Santosh S. Venkatesh: Learning Pattern Classification - A Survey. IEEE Transactions on Information Theory 44(6): 2178-2206 (1998)
16		András Antos, Gábor Lugosi: Strong Minimax Lower Bounds for Learning. Machine Learning 30(1): 31-56 (1998)
	1997
15		Peter L. Bartlett, Tamás Linder, Gábor Lugosi: A Minimax Lower Bound for Empirical Quantizer Design. EuroCOLT 1997: 210-222
14		Tamás Linder, Gábor Lugosi, Kenneth Zeger: Empirical quantizer design in the presence of source noise or channel noise. IEEE Transactions on Information Theory 43(2): 612-623 (1997)
	1996
13		András Antos, Gábor Lugosi: Strong Minimax Lower Bounds for Learning. COLT 1996: 303-309
12		Gábor Lugosi, Márta Pintér: A Data-Dependent Skeleton Estimate for Learning. COLT 1996: 51-56
11		Tamás Linder, Gábor Lugosi, Kenneth Zeger: Designing Vector Quantizers in the Presence of Source Noise or Channel Noise. Data Compression Conference 1996: 33-42
10		Gábor Lugosi, Kenneth Zeger: Concept learning using complexity regularization. IEEE Transactions on Information Theory 42(1): 48-54 (1996)
	1995
9		Tamás Linder, Gábor Lugosi, Kenneth Zeger: Fixed-rate universal lossy source coding and rates of convergence for memoryless sources. IEEE Transactions on Information Theory 41(3): 665-676 (1995)
8		Gábor Lugosi, Kenneth Zeger: Nonparametric estimation via empirical risk minimization. IEEE Transactions on Information Theory 41(3): 677-687 (1995)
7		Luc Devroye, Gábor Lugosi: Lower bounds in pattern recognition and learning. Pattern Recognition 28(7): 1011-1018 (1995)
	1994
6		Gábor Lugosi, Miroslaw Pawlak: On the posterior-probability estimate of the error rate of nonparametric classification rules. IEEE Transactions on Information Theory 40(2): 475-481 (1994)
5		Tamás Linder, Gábor Lugosi, Kenneth Zeger: Rates of convergence in the source coding theorem, in empirical quantizer design, and in universal lossy source coding. IEEE Transactions on Information Theory 40(6): 1728-1740 (1994)
	1993
4		Tamás Linder, Gábor Lugosi, Kenneth Zeger: Universality and Rates of Convergence in Lossy Source Coding. Data Compression Conference 1993: 89-97
3		András Faragó, Tamás Linder, Gábor Lugosi: Fast Nearest-Neighbor Search in Dissimilarity Spaces. IEEE Trans. Pattern Anal. Mach. Intell. 15(9): 957-962 (1993)
2		András Faragó, Gábor Lugosi: Strong universal consistency of neural network classifiers. IEEE Transactions on Information Theory 39(4): 1146-1151 (1993)
	1992
1		Gábor Lugosi: Learning with an unreliable teacher. Pattern Recognition 25(1): 79-87 (1992)

Coauthor Index

1	Louigi Addario-Berry	[70]
2	András Antos	[13] [16] [30]
3	Jean-Yves Audibert	[72] [76]
4	Peter L. Bartlett	[15] [18] [24] [29]
5	Gérard Biau	[59] [61]
6	Gilles Blanchard	[34]
7	Avrim Blum	[49]
8	Stéphane Boucheron	[23] [24] [29] [36] [37]
9	Olivier Bousquet	[36] [37]
10	Nicolas Broutin	[70] [75]
11	Sébastien Bubeck	[72] [76]
12	Nicolò Cesa-Bianchi	[20] [22] [25] [27] [33] [40] [42] [46] [48] [67] [77]
13	Stéphan Clémençon	[43] [45]
14	Luc Devroye	[7] [31] [55] [59] [61] [64] [75]
15	András Faragó (Andras Farago)	[2] [3]
16	Nicolas Fraiman	[75]
17	Pierre Gaillard	[77]
18	Ricard Gavaldà	[68]
19	Fabrizio Germano	[51]
20	László Györfi	[21] [31]
21	András György	[38] [39] [44] [50] [54] [60] [63] [69] [74]
22	Matthias Hein	[73]
23	Márta Horváth	[19]
24	Balázs Kégl	[28] [30]
25	Sanjeev R. Kulkarni	[17]
26	Tamás Linder	[3] [4] [5] [9] [11] [14] [15] [18] [26] [28] [30] [38] [39] [44] [50] [54] [60] [74]
27	Shie Mannor	[53] [56] [58]
28	Pascal Massart	[23]
29	Gusztáv Morvai	[21]
30	György Ottucsák	[50] [54] [63] [69]
31	Omiros Papaspiliopoulos	[65] [66]
32	GaHyun Park	[55] [64]
33	Miroslaw Pawlak	[6]
34	Márta Pintér	[12]
35	Lorenzo Rosasco	[73]
36	Hans Ulrich Simon (Hans-Ulrich Simon)	[47] [49]
37	Steve Smale	[73]
38	Gilles Stoltz	[35] [40] [41] [42] [46] [52] [53] [56] [58] [65] [66] [77]
39	Wojciech Szpankowski	[55] [64]
40	Nicolas Vayatis	[32] [34] [43] [45]
41	Santosh S. Venkatesh	[17]
42	Kenneth Zeger	[4] [5] [8] [9] [10] [11] [14]
43	Thomas Zeugmann	[68]
44	Sandra Zilles	[68] [71]

Colors in the list of coauthors

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