518 search results - page 7 / 104 » Learning associative Markov networks |
ICML
2005
IEEE
14 years 8 months ago
2005
IEEE
Markov logic networks (MLNs) combine logic and probability by attaching weights to first-order clauses, and viewing these as templates for features of Markov networks. In this pap...
SODA
2001
ACM
13 years 9 months ago
2001
ACM
Markov networks are a common class of graphical models used in machine learning. Such models use an undirected graph to capture dependency information among random variables in a ...
ECAI
2008
Springer
13 years 9 months ago
2008
Springer
Many real-world applications of AI require both probability and first-order logic to deal with uncertainty and structural complexity. Logical AI has focused mainly on handling com...
ICDM
2010
IEEE
13 years 5 months ago
2010
IEEE
Traditional Markov network structure learning algorithms perform a search for globally useful features. However, these algorithms are often slow and prone to finding local optima d...
ML
2006
ACM
13 years 7 months ago
2006
ACM
We propose a simple approach to combining first-order logic and probabilistic graphical models in a single representation. A Markov logic network (MLN) is a first-order knowledge b...