824 search results - page 21 / 165 » Learning probabilistic logic models from probabilistic examp... |
ICML
2005
IEEE
16 years 13 days ago
2005
IEEE
Many real-world domains exhibit rich relational structure and stochasticity and motivate the development of models that combine predicate logic with probabilities. These models de...
116
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BMCBI
2010
14 years 11 months ago
2010
Background: Mocapy++ is a toolkit for parameter learning and inference in dynamic Bayesian networks (DBNs). It supports a wide range of DBN architectures and probability distribut...
127
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ECCV
2004
Springer
16 years 1 months ago
2004
Springer
Abstract. The exploitation of video data requires to extract information at a rather semantic level, and then, methods able to infer "concepts" from low-level video featu...
116
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ASIAN
2003
Springer
15 years 4 months ago
2003
Springer
Protocols for distributed systems make often use of random transitions to achieve a common goal. A popular example are randomized leader election protocols. We introduce probabilis...
NIPS
2001
15 years 1 months ago
2001
To find out how the representations of structured visual objects depend on the co-occurrence statistics of their constituents, we exposed subjects to a set of composite images wit...