Nick Littlestone

26 papers A* 14B 1Journal 10Unranked 1
YearRankTypeTitle / Venue / Authors
2001 J jnl
General Convergence Results for Linear Discriminant Updates.
Mach. Learn.
Adam J. Grove, Nick Littlestone, Dale Schuurmans
2000 J jnl
Apple Tasting.
Inf. Comput.
David P. Helmbold, Nick Littlestone, Philip M. Long
2000 J jnl
On-Line Learning with Linear Loss Constraints.
Inf. Comput.
David P. Helmbold, Nick Littlestone, Philip M. Long
1999 A* conf
The Robustness of the
COLT
Claudio Gentile, Nick Littlestone
1997 A* conf
General Convergence Results for Linear Discriminant Updates.
COLT
Adam J. Grove, Nick Littlestone, Dale Schuurmans
1996 — conf
An Apobayesian Relative of Winnow.
NIPS
Nick Littlestone, Chris Mesterharm
1995 A* conf
Comparing Several Linear-threshold Learning Algorithms on Tasks Involving Superfluous Attributes.
ICML
Nick Littlestone
1995 J jnl
Learning in the Presence of Finitely or Infinitely Many Irrelevant Attributes.
J. Comput. Syst. Sci.
Avrim Blum, Lisa Hellerstein, Nick Littlestone
1995 J jnl
On-line Learning of Linear Functions.
Comput. Complex.
Nick Littlestone, Philip M. Long, Manfred K. Warmuth
1994 J jnl
Predicting \0,1\-Functions on Randomly Drawn Points
Inf. Comput.
David Haussler, Nick Littlestone, Manfred K. Warmuth
1994 J jnl
The Weighted Majority Algorithm
Inf. Comput.
Nick Littlestone, Manfred K. Warmuth
1993 A* conf
On-Line Learning with Linear Loss Constraints.
COLT
Nick Littlestone, Philip M. Long
1992 A* conf
Apple Tasting and Nearly One-Sided Learning
FOCS
David P. Helmbold, Nick Littlestone, Philip M. Long
1991 J jnl
Equivalence of Models for Polynomial Learnability
Inf. Comput.
David Haussler, Michael J. Kearns, Nick Littlestone, Manfred K. Warmuth
1991 A* conf
Learning in the Presence of Finitely or Infinitely Many Irrelevant Attributes.
COLT
Avrim Blum, Lisa Hellerstein, Nick Littlestone
1991 B conf
Learning simple Boolean concepts.
ALT
Nick Littlestone
1991 A* conf
On-Line Learning of Linear Functions
STOC
Nick Littlestone, Philip M. Long, Manfred K. Warmuth
1991 A* conf
Redundant Noisy Attributes, Attribute Errors, and Linear-Threshold Learning Using Winnow.
COLT
Nick Littlestone
1989 A* conf
From On-Line to Batch Learning.
COLT
Nick Littlestone
1989 J jnl
Learning faster than promised by the Vapnik-Chervonenkis dimension.
Discret. Appl. Math.
Anselm Blumer, Nick Littlestone
1989 A* conf
The Weighted Majority Algorithm
FOCS
Nick Littlestone, Manfred K. Warmuth
1988 A* conf
Equivalence of Models for Polynomial Learnability.
COLT
David Haussler, Michael J. Kearns, Nick Littlestone, Manfred K. Warmuth
1988 A* conf
Predicting {0, 1}-Functions on Randomly Drawn Points.
COLT
David Haussler, Nick Littlestone, Manfred K. Warmuth
1988 A* conf
Predicting {0,1}-Functions on Randomly Drawn Points (Extended Abstract)
FOCS
David Haussler, Nick Littlestone, Manfred K. Warmuth
1987 A* conf
Learning Quickly When Irrelevant Attributes Abound: A New Linear-Threshold Algorithm (Extended Abstract)
FOCS
Nick Littlestone
1987 J jnl
Learning Quickly When Irrelevant Attributes Abound: A New Linear-threshold Algorithm.
Mach. Learn.
Nick Littlestone