| 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 |
|---|
| 22 | EE | Claudio Gentile,
Nick Littlestone:
The Robustness of the p-Norm Algorithms.
COLT 1999: 1-11 |
| 1997 |
|---|
| 21 | EE | Adam J. Grove,
Nick Littlestone,
Dale Schuurmans:
General Convergence Results for Linear Discriminant Updates.
COLT 1997: 171-183 |
| 1996 |
|---|
| 20 | EE | Nick 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 |
|---|
| 14 | EE | Nick 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 |
|---|
| 12 | EE | Nick Littlestone:
Redundant Noisy Attributes, Attribute Errors, and Linear-Threshold Learning Using Winnow.
COLT 1991: 147-156 |
| 11 | EE | Avrim 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 |
|---|
| 8 | EE | Nick 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 |
| 6 | EE | Anselm Blumer,
Nick Littlestone:
Learning faster than promised by the Vapnik-Chervonenkis dimension.
Discrete Applied Mathematics 24(1-3): 47-53 (1989) |
| 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) |
