2073 search results - page 210 / 415 » Learning for Dynamic Subsumption |
ECML
2006
Springer
15 years 6 months ago
2006
Springer
Abstract. In this paper, we review the task of inductive process modeling, which uses domain knowledge to compose explanatory models of continuous dynamic systems. Next we discuss ...
133
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NIPS
2008
15 years 4 months ago
2008
With the increased availability of data for complex domains, it is desirable to learn Bayesian network structures that are sufficiently expressive for generalization while at the ...
113
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NIPS
2008
15 years 4 months ago
2008
Learning in real-time applications, e.g., online approximation of the inverse dynamics model for model-based robot control, requires fast online regression techniques. Inspired by...
171
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EVENT
2001
15 years 4 months ago
2001
Automatically understanding human actions from video sequences is a very challenging problem. This involves the extraction of relevant visual information from a video sequence, re...
138
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UAI
2004
15 years 4 months ago
2004
Bayesian learning in undirected graphical models--computing posterior distributions over parameters and predictive quantities-is exceptionally difficult. We conjecture that for ge...