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» Learning parities in the mistake-bound model
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COLT
1999
Springer
13 years 11 months ago
Drifting Games
We consider the problem of learning to predict as well as the best in a group of experts making continuous predictions. We assume the learning algorithm has prior knowledge of the ...
Robert E. Schapire
ALT
2008
Springer
14 years 4 months ago
Learning with Continuous Experts Using Drifting Games
We consider the problem of learning to predict as well as the best in a group of experts making continuous predictions. We assume the learning algorithm has prior knowledge of the ...
Indraneel Mukherjee, Robert E. Schapire
SIGIR
2002
ACM
13 years 7 months ago
A new family of online algorithms for category ranking
We describe a new family of topic-ranking algorithms for multi-labeled documents. The motivation for the algorithms stems from recent advances in online learning algorithms. The a...
Koby Crammer, Yoram Singer
ICML
2010
IEEE
13 years 8 months ago
Generalizing Apprenticeship Learning across Hypothesis Classes
This paper develops a generalized apprenticeship learning protocol for reinforcementlearning agents with access to a teacher who provides policy traces (transition and reward obse...
Thomas J. Walsh, Kaushik Subramanian, Michael L. L...
ICML
2003
IEEE
14 years 8 months ago
Using Linear-threshold Algorithms to Combine Multi-class Sub-experts
We present a new type of multi-class learning algorithm called a linear-max algorithm. Linearmax algorithms learn with a special type of attribute called a sub-expert. A sub-exper...
Chris Mesterharm