210 search results - page 29 / 42 » An analysis of reinforcement learning with function approxim... |
115
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NIPS
2001
15 years 1 months ago
2001
We propose a new approach to reinforcement learning which combines least squares function approximation with policy iteration. Our method is model-free and completely off policy. ...
EMMCVPR
2005
Springer
2005
Springer
Exploiting Inference for Approximate Parameter Learning in Discriminative Fields: An Empirical Study
15 years 5 months ago
Abstract. Estimation of parameters of random field models from labeled training data is crucial for their good performance in many image analysis applications. In this paper, we p...
JMLR
2010
14 years 6 months ago
2010
Variational Bayesian (VB) methods are typically only applied to models in the conjugate-exponential family using the variational Bayesian expectation maximisation (VB EM) algorith...
100
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CVPR
2011
IEEE
14 years 8 months ago
2011
IEEE
We present a novel framework for tree-structure embedded density estimation and its fast approximation for mode seeking. The proposed method could find diverse applications in co...
100
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ICML
1994
IEEE
15 years 3 months ago
1994
IEEE
Compositional Q-Learning (CQ-L) (Singh 1992) is a modular approach to learning to performcomposite tasks made up of several elemental tasks by reinforcement learning. Skills acqui...