2103 search results - page 28 / 421 » Approximate Learning of Dynamic Models |
106
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ICML
2005
IEEE
16 years 2 months ago
2005
IEEE
In many domains, a Bayesian network's topological structure is not known a priori and must be inferred from data. This requires a scoring function to measure how well a propo...
111
Voted
AAAI
2006
15 years 3 months ago
2006
Planning in partially-observable dynamical systems is a challenging problem, and recent developments in point-based techniques such as Perseus significantly improve performance as...
115
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MOC
2010
14 years 8 months ago
2010
We consider temporal approximation of stationary statistical properties of dissipative complex dynamical systems. We demonstrate that stationary statistical properties of the time...
113
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APSCC
2008
IEEE
15 years 8 months ago
2008
IEEE
— We discuss a learning model that enables the creation of optimal learning strategies that suit learners’ needs. A customized learning content is delivered to learners as mana...
137
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ML
2012
ACM
13 years 9 months ago
2012
ACM
Bayesian learning, widely used in many applied data-modeling problems, is often accomplished with approximation schemes because it requires intractable computation of the posterio...