Gábor Lugosi

2009
56	EE	Gábor Lugosi, Omiros Papaspiliopoulos, Gilles Stoltz: Online Multi-task Learning with Hard Constraints CoRR abs/0902.3526: (2009)
55	EE	Luc Devroye, Gábor Lugosi, GaHyun Park, Wojciech Szpankowski: Multiple choice tries and distributed hash tables. Random Struct. Algorithms 34(3): 337-367 (2009)
2008
54	EE	András György, Gábor Lugosi, György Ottucsák: On-line Sequential Bin Packing. COLT 2008: 447-454
53	EE	Gábor Lugosi: Concentration Inequalities. COLT 2008: 7-8
52	EE	Gérard Biau, Luc Devroye, Gábor Lugosi: On the Performance of Clustering in Hilbert Spaces. IEEE Transactions on Information Theory 54(2): 781-790 (2008)
51	EE	András György, Tamás Linder, Gábor Lugosi: Tracking the Best Quantizer. IEEE Transactions on Information Theory 54(4): 1604-1625 (2008)
2007
50		Gábor Lugosi: Sequential prediction under incomplete feedback. CCIA 2007: 3-5
49	EE	Gábor Lugosi, Shie Mannor, Gilles Stoltz: Strategies for Prediction Under Imperfect Monitoring. COLT 2007: 248-262
48	EE	Luc Devroye, Gábor Lugosi, GaHyun Park, Wojciech Szpankowski: Multiple choice tries and distributed hash tables. SODA 2007: 891-899
47	EE	András György, Tamás Linder, Gábor Lugosi, György Ottucsák: The on-line shortest path problem under partial monitoring CoRR abs/0704.1020: (2007)
46	EE	Gábor Lugosi, Shie Mannor, Gilles Stoltz: Strategies for prediction under imperfect monitoring CoRR abs/math/0701419: (2007)
45	EE	Avrim Blum, Gábor Lugosi, Hans-Ulrich Simon: Introduction to the special issue on COLT 2006. Machine Learning 69(2-3): 75-77 (2007)
2006
44		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
2005
43	EE	Stéphan Clémençon, Gábor Lugosi, Nicolas Vayatis: Ranking and Scoring Using Empirical Risk Minimization. COLT 2005: 1-15
42	EE	András György, Tamás Linder, Gábor Lugosi: Tracking the Best of Many Experts. COLT 2005: 204-216
41	EE	Nicolò Cesa-Bianchi, Gábor Lugosi, Gilles Stoltz: Minimizing regret with label efficient prediction. IEEE Transactions on Information Theory 51(6): 2152-2162 (2005)
40	EE	Gilles Stoltz, Gábor Lugosi: Internal Regret in On-Line Portfolio Selection. Machine Learning 59(1-2): 125-159 (2005)
2004
39	EE	Nicolò Cesa-Bianchi, Gábor Lugosi, Gilles Stoltz: Minimizing Regret with Label Efficient Prediction. COLT 2004: 77-92
38	EE	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
2003
37	EE	Olivier Bousquet, Stéphane Boucheron, Gábor Lugosi: Introduction to Statistical Learning Theory. Advanced Lectures on Machine Learning 2003: 169-207
36	EE	Stéphane Boucheron, Gábor Lugosi, Olivier Bousquet: Concentration Inequalities. Advanced Lectures on Machine Learning 2003: 208-240
35	EE	Gilles Stoltz, Gábor Lugosi: Internal Regret in On-Line Portfolio Selection. COLT 2003: 403-417
34	EE	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	EE	Nicolò Cesa-Bianchi, Gábor Lugosi: Potential-Based Algorithms in On-Line Prediction and Game Theory. Machine Learning 51(3): 239-261 (2003)
2002
32	EE	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	EE	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	EE	Balázs Kégl, Tamás Linder, Gábor Lugosi: Data-Dependent Margin-Based Generalization Bounds for Classification. COLT/EuroCOLT 2001: 368-384
27	EE	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	EE	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	EE	Nicolò Cesa-Bianchi, Gábor Lugosi: On Sequential Prediction of Individual Sequences Relative to a Set of Experts. COLT 1998: 1-11
19	EE	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	EE	András Antos, Gábor Lugosi: Strong Minimax Lower Bounds for Learning. COLT 1996: 303-309
12	EE	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	EE	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	EE	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	EE	Gábor Lugosi: Learning with an unreliable teacher. Pattern Recognition 25(1): 79-87 (1992)

Coauthor Index

1	András Antos	[13] [16] [30]
2	Peter L. Bartlett	[15] [18] [24] [29]
3	Gérard Biau	[52]
4	Gilles Blanchard	[34]
5	Avrim Blum	[45]
6	Stéphane Boucheron	[23] [24] [29] [36] [37]
7	Olivier Bousquet	[36] [37]
8	Nicolò Cesa-Bianchi	[20] [22] [25] [27] [33] [39] [41]
9	Stéphan Clémençon	[43]
10	Luc Devroye	[7] [31] [48] [52] [55]
11	András Faragó	[2] [3]
12	László Györfi	[21] [31]
13	András György	[38] [42] [47] [51] [54]
14	Márta Horváth	[19]
15	Balázs Kégl	[28] [30]
16	Sanjeev R. Kulkarni	[17]
17	Tamás Linder	[3] [4] [5] [9] [11] [14] [15] [18] [26] [28] [30] [38] [42] [47] [51]
18	Shie Mannor	[46] [49]
19	Pascal Massart	[23]
20	Gusztáv Morvai	[21]
21	György Ottucsák	[47] [54]
22	Omiros Papaspiliopoulos	[56]
23	GaHyun Park	[48] [55]
24	Miroslaw Pawlak	[6]
25	Márta Pintér	[12]
26	Hans-Ulrich Simon	[44] [45]
27	Gilles Stoltz	[35] [39] [40] [41] [46] [49] [56]
28	Wojciech Szpankowski	[48] [55]
29	Nicolas Vayatis	[32] [34] [43]
30	Santosh S. Venkatesh	[17]
31	Kenneth Zeger	[4] [5] [8] [9] [10] [11] [14]

Colors in the list of coauthors