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2000 – 2009
- 2001
[j10]Adam J. Grove, Nick Littlestone, Dale Schuurmans:
General Convergence Results for Linear Discriminant Updates. Mach. Learn. 43(3): 173-210 (2001)- 2000
- [j9]David P. Helmbold, Nick Littlestone, Philip M. Long:
Apple Tasting. Inf. Comput. 161(2): 85-139 (2000) - [j8]David P. Helmbold, Nick Littlestone, Philip M. Long:
On-Line Learning with Linear Loss Constraints. Inf. Comput. 161(2): 140-171 (2000)
1990 – 1999
- 1999
- [c16]Claudio Gentile, Nick Littlestone:
The Robustness of the p-Norm Algorithms. COLT 1999: 1-11 - 1997
- [c15]Adam J. Grove, Nick Littlestone, Dale Schuurmans:
General Convergence Results for Linear Discriminant Updates. COLT 1997: 171-183 - 1996
- [c14]Nick Littlestone, Chris Mesterharm:
An Apobayesian Relative of Winnow. NIPS 1996: 204-210 - 1995
- [j7]Nick Littlestone, Philip M. Long, Manfred K. Warmuth:
On-line Learning of Linear Functions. Comput. Complex. 5(1): 1-23 (1995) - [j6]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) - [c13]Nick Littlestone:
Comparing Several Linear-threshold Learning Algorithms on Tasks Involving Superfluous Attributes. ICML 1995: 353-361 - 1994
- [j5]Nick Littlestone, Manfred K. Warmuth:
The Weighted Majority Algorithm. Inf. Comput. 108(2): 212-261 (1994) - [j4]David Haussler, Nick Littlestone, Manfred K. Warmuth:
Predicting \0,1\-Functions on Randomly Drawn Points. Inf. Comput. 115(2): 248-292 (1994) - 1993
- [c12]Nick Littlestone, Philip M. Long:
On-Line Learning with Linear Loss Constraints. COLT 1993: 412-421 - 1992
- [c11]David P. Helmbold, Nick Littlestone, Philip M. Long:
Apple Tasting and Nearly One-Sided Learning. FOCS 1992: 493-502 - 1991
- [j3]David Haussler, Michael J. Kearns, Nick Littlestone, Manfred K. Warmuth:
Equivalence of Models for Polynomial Learnability. Inf. Comput. 95(2): 129-161 (1991) - [c10]Nick Littlestone:
Learning simple Boolean concepts. ALT 1991: 6-14 - [c9]Nick Littlestone:
Redundant Noisy Attributes, Attribute Errors, and Linear-Threshold Learning Using Winnow. COLT 1991: 147-156 - [c8]Avrim Blum, Lisa Hellerstein, Nick Littlestone:
Learning in the Presence of Finitely or Infinitely Many Irrelevant Attributes. COLT 1991: 157-166 - [c7]Nick Littlestone, Philip M. Long, Manfred K. Warmuth:
On-Line Learning of Linear Functions. STOC 1991: 465-475
1980 – 1989
- 1989
- [j2]Anselm Blumer, Nick Littlestone:
Learning faster than promised by the Vapnik-Chervonenkis dimension. Discret. Appl. Math. 24(1-3): 47-53 (1989) - [c6]Nick Littlestone:
From On-Line to Batch Learning. COLT 1989: 269-284 - [c5]Nick Littlestone, Manfred K. Warmuth:
The Weighted Majority Algorithm. FOCS 1989: 256-261 - 1988
- [c4]David Haussler, Michael J. Kearns, Nick Littlestone, Manfred K. Warmuth:
Equivalence of Models for Polynomial Learnability. COLT 1988: 42-55 - [c3]David Haussler, Nick Littlestone, Manfred K. Warmuth:
Predicting {0, 1}-Functions on Randomly Drawn Points. COLT 1988: 280-296 - [c2]David Haussler, Nick Littlestone, Manfred K. Warmuth:
Predicting {0,1}-Functions on Randomly Drawn Points (Extended Abstract). FOCS 1988: 100-109 - 1987
- [j1]Nick Littlestone:
Learning Quickly When Irrelevant Attributes Abound: A New Linear-threshold Algorithm. Mach. Learn. 2(4): 285-318 (1987) - [c1]Nick Littlestone:
Learning Quickly When Irrelevant Attributes Abound: A New Linear-Threshold Algorithm (Extended Abstract). FOCS 1987: 68-77
Coauthor Index
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