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» Learning parities in the mistake-bound model
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COLT
1999
Springer
15 years 1 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
15 years 6 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
14 years 9 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
14 years 10 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
15 years 10 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