509 search results - page 33 / 102 » Using Learning for Approximation in Stochastic Processes |
126
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MLDM
1999
Springer
15 years 6 months ago
1999
Springer
In large content-based image database applications, e cient information retrieval depends heavily on good indexing structures of the extracted features. While indexing techniques f...
108
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ICML
2000
IEEE
16 years 3 months ago
2000
IEEE
This paper discusses theoretical and experimental aspects of gradient-based approaches to the direct optimization of policy performance in controlled ??? ?s. We introduce ??? ?, a...
103
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ICML
2008
IEEE
16 years 3 months ago
2008
IEEE
Partially Observable Markov Decision Processes (POMDPs) have succeeded in planning domains that require balancing actions that increase an agent's knowledge and actions that ...
143
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BMCBI
2006
15 years 2 months ago
2006
Background: Stochastic simulation has become a useful tool to both study natural biological systems and design new synthetic ones. By capturing the intrinsic molecular fluctuation...
123
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NIPS
2004
15 years 3 months ago
2004
Log-concavity is an important property in the context of optimization, Laplace approximation, and sampling; Bayesian methods based on Gaussian process priors have become quite pop...