508 search results - page 22 / 102 » Learning for stochastic dynamic programming |
113
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ATAL
2007
Springer
15 years 8 months ago
2007
Springer
Reinforcement learning promises a generic method for adapting agents to arbitrary tasks in arbitrary stochastic environments, but applying it to new real-world problems remains di...
124
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NIPS
1998
15 years 3 months ago
1998
The Expectation Maximization EM algorithm is an iterative procedure for maximum likelihood parameter estimation from data sets with missing or hidden variables 2 . It has been app...
132
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JSAC
2011
14 years 9 months ago
2011
—Various spectrum management schemes have been proposed in recent years to improve the spectrum utilization in cognitive radio networks. However, few of them have considered the ...
145
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ECCB
2003
IEEE
15 years 7 months ago
2003
IEEE
This article deals with the identification of gene regulatory networks from experimental data using a statistical machine learning approach. A stochastic model of gene interactio...
132
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ICMLC
2005
Springer
15 years 7 months ago
2005
Springer
This paper presents a novel approach for adaptive online multi-stroke sketch recognition based on Hidden Markov Model (HMM). The method views the drawing sketch as the result of a ...