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189
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ICML
2000
IEEE
15 years 11 months ago
2000
IEEE
The reinforcement learning problem can be decomposed into two parallel types of inference: (i) estimating the parameters of a model for the underlying process; (ii) determining be...
191
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ECML
2006
Springer
15 years 10 months ago
2006
Springer
Reinforcement learning in real-world domains suffers from three curses of dimensionality: explosions in state and action spaces, and high stochasticity. We present approaches that ...
178
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COLT
2008
Springer
15 years 8 months ago
2008
Springer
We study distribution-dependent, data-dependent, learning in the limit with adversarial disturbance. We consider an optimization-based approach to learning binary classifiers from...
168
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ML
1998
ACM
15 years 6 months ago
1998
ACM
We review the application of statistical mechanics methods to the study of online learning of a drifting concept in the limit of large systems. The model where a feed-forward netwo...
156
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PCM
2010
Springer
15 years 5 months ago
2010
Springer
Abstract. The semantic contextual information is shown to be an important resource for improving the scene and image recognition, but is seldom explored in the literature of previo...