2103 search results - page 21 / 421 » Approximate Learning of Dynamic Models |
105
Voted
ICML
2008
IEEE
16 years 2 months ago
2008
IEEE
The hierarchical Dirichlet process hidden Markov model (HDP-HMM) is a flexible, nonparametric model which allows state spaces of unknown size to be learned from data. We demonstra...
122
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CDC
2010
IEEE
14 years 9 months ago
2010
IEEE
Approximate policy iteration methods based on temporal differences are popular in practice, and have been tested extensively, dating to the early nineties, but the associated conve...
89
Voted
HICSS
2009
IEEE
15 years 8 months ago
2009
IEEE
One knowledge discovery problem in the rapid response setting is the cost of learning which patterns are indicative of a threat. This typically involves a detailed follow-through,...
116
Voted
CORR
2010
Springer
15 years 2 months ago
2010
Springer
In this paper, we consider the problem of planning and learning in the infinite-horizon discounted-reward Markov decision problems. We propose a novel iterative direct policysearc...
118
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CMSB
2009
Springer
15 years 8 months ago
2009
Springer
Systems of ordinary differential equations (ODEs) are often used to model the dynamics of complex biological pathways. We construct a discrete state model as a probabilistic appro...