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Nick Littlestone

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2001
25 Adam J. Grove, Nick Littlestone, Dale Schuurmans: General Convergence Results for Linear Discriminant Updates. Machine Learning 43(3): 173-210 (2001)
2000
24 David P. Helmbold, Nick Littlestone, Philip M. Long: On-Line Learning with Linear Loss Constraints. Inf. Comput. 161(2): 140-171 (2000)
23 David P. Helmbold, Nick Littlestone, Philip M. Long: Apple Tasting. Inf. Comput. 161(2): 85-139 (2000)
1999
22EEClaudio Gentile, Nick Littlestone: The Robustness of the p-Norm Algorithms. COLT 1999: 1-11
1997
21EEAdam J. Grove, Nick Littlestone, Dale Schuurmans: General Convergence Results for Linear Discriminant Updates. COLT 1997: 171-183
1996
20EENick Littlestone, Chris Mesterharm: An Apobayesian Relative of Winnow. NIPS 1996: 204-210
1995
19 Nick Littlestone: Comparing Several Linear-threshold Learning Algorithms on Tasks Involving Superfluous Attributes. ICML 1995: 353-361
18 Nick Littlestone, Philip M. Long, Manfred K. Warmuth: On-line Learning of Linear Functions. Computational Complexity 5(1): 1-23 (1995)
17 Avrim Blum, Lisa Hellerstein, Nick Littlestone: Learning in the Presence of Finitely or Infinitely Many Irrelevant Attributes. J. Comput. Syst. Sci. 50(1): 32-40 (1995)
1994
16 Nick Littlestone, Manfred K. Warmuth: The Weighted Majority Algorithm Inf. Comput. 108(2): 212-261 (1994)
15 David Haussler, Nick Littlestone, Manfred K. Warmuth: Predicting \0,1\-Functions on Randomly Drawn Points Inf. Comput. 115(2): 248-292 (1994)
1993
14EENick Littlestone, Philip M. Long: On-Line Learning with Linear Loss Constraints. COLT 1993: 412-421
1992
13 David P. Helmbold, Nick Littlestone, Philip M. Long: Apple Tasting and Nearly One-Sided Learning FOCS 1992: 493-502
1991
12EENick Littlestone: Redundant Noisy Attributes, Attribute Errors, and Linear-Threshold Learning Using Winnow. COLT 1991: 147-156
11EEAvrim Blum, Lisa Hellerstein, Nick Littlestone: Learning in the Presence of Finitely or Infinitely Many Irrelevant Attributes. COLT 1991: 157-166
10 Nick Littlestone, Philip M. Long, Manfred K. Warmuth: On-Line Learning of Linear Functions STOC 1991: 465-475
9 David Haussler, Michael J. Kearns, Nick Littlestone, Manfred K. Warmuth: Equivalence of Models for Polynomial Learnability Inf. Comput. 95(2): 129-161 (1991)
1989
8EENick Littlestone: From On-Line to Batch Learning. COLT 1989: 269-284
7 Nick Littlestone, Manfred K. Warmuth: The Weighted Majority Algorithm FOCS 1989: 256-261
6EEAnselm Blumer, Nick Littlestone: Learning faster than promised by the Vapnik-Chervonenkis dimension. Discrete Applied Mathematics 24(1-3): 47-53 (1989)
1988
5EEDavid Haussler, Nick Littlestone, Manfred K. Warmuth: Predicting {0, 1}-Functions on Randomly Drawn Points. COLT 1988: 280-296
4EEDavid Haussler, Michael J. Kearns, Nick Littlestone, Manfred K. Warmuth: Equivalence of Models for Polynomial Learnability. COLT 1988: 42-55
3 David Haussler, Nick Littlestone, Manfred K. Warmuth: Predicting {0,1}-Functions on Randomly Drawn Points (Extended Abstract) FOCS 1988: 100-109
1987
2 Nick Littlestone: Learning Quickly When Irrelevant Attributes Abound: A New Linear-Threshold Algorithm (Extended Abstract) FOCS 1987: 68-77
1 Nick Littlestone: Learning Quickly When Irrelevant Attributes Abound: A New Linear-threshold Algorithm. Machine Learning 2(4): 285-318 (1987)

Coauthor Index

1Avrim Blum [11] [17]
2Anselm Blumer [6]
3Claudio Gentile [22]
4Adam J. Grove [21] [25]
5David Haussler [3] [4] [5] [9] [15]
6Lisa Hellerstein [11] [17]
7David P. Helmbold [13] [23] [24]
8Michael J. Kearns [4] [9]
9Philip M. Long [10] [13] [14] [18] [23] [24]
10Chris Mesterharm [20]
11Dale Schuurmans [21] [25]
12Manfred K. Warmuth [3] [4] [5] [7] [9] [10] [15] [16] [18]

Colors in the list of coauthors

Copyright © Sun May 17 03:24:02 2009 by Michael Ley (ley@uni-trier.de)