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» On-line Algorithms in Machine Learning
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ICML
2007
IEEE
16 years 4 months ago
A bound on the label complexity of agnostic active learning
We study the label complexity of pool-based active learning in the agnostic PAC model. Specifically, we derive general bounds on the number of label requests made by the A2 algori...
Steve Hanneke
109
Voted
ICML
2002
IEEE
16 years 4 months ago
Discovering Hierarchy in Reinforcement Learning with HEXQ
An open problem in reinforcement learning is discovering hierarchical structure. HEXQ, an algorithm which automatically attempts to decompose and solve a model-free factored MDP h...
Bernhard Hengst
95
Voted
ECML
2000
Springer
15 years 8 months ago
Layered Learning
We examine how a network of many knowledge layers can be constructed in an on-line manner, such that the learned units represent building blocks of knowledge that serve to compres...
Peter Stone, Manuela M. Veloso
135
Voted
EWRL
2008
15 years 5 months ago
Variable Metric Reinforcement Learning Methods Applied to the Noisy Mountain Car Problem
Two variable metric reinforcement learning methods, the natural actor-critic algorithm and the covariance matrix adaptation evolution strategy, are compared on a conceptual level a...
Verena Heidrich-Meisner, Christian Igel
158
Voted
ECML
2007
Springer
15 years 5 months ago
Sequence Labeling with Reinforcement Learning and Ranking Algorithms
Many problems in areas such as Natural Language Processing, Information Retrieval, or Bioinformatic involve the generic task of sequence labeling. In many cases, the aim is to assi...
Francis Maes, Ludovic Denoyer, Patrick Gallinari