Nick Littlestone

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

1	Avrim Blum	[10] [16]
2	Claudio Gentile	[21]
3	Adam J. Grove	[20] [24]
4	David Haussler	[3] [4] [5] [8] [14]
5	Lisa Hellerstein	[10] [16]
6	David P. Helmbold	[12] [22] [23]
7	Michael J. Kearns	[4] [8]
8	Philip M. Long	[9] [12] [13] [17] [22] [23]
9	Chris Mesterharm	[19]
10	Dale Schuurmans	[20] [24]
11	Manfred K. Warmuth	[3] [4] [5] [6] [8] [9] [14] [15] [17]

Colors in the list of coauthors