518 search results - page 8 / 104 » Learning associative Markov networks |
ICML
2009
IEEE
14 years 8 months ago
2009
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. Learning ML...
ICASSP
2009
IEEE
14 years 2 months ago
2009
IEEE
Recently proposed l1-regularized maximum-likelihood optimization methods for learning sparse Markov networks result into convex problems that can be solved optimally and efficien...
ECAI
2010
Springer
13 years 5 months ago
2010
Springer
Abstract. Statistical relational models, such as Markov logic networks, seek to compactly describe properties of relational domains by representing general principles about objects...
ICML
2010
IEEE
13 years 9 months ago
2010
IEEE
The structure of a Markov network is typically learned using top-down search. At each step, the search specializes a feature by conjoining it to the variable or feature that most ...
AAAI
2010
13 years 9 months ago
2010
Many machine learning applications that involve relational databases incorporate first-order logic and probability. Markov Logic Networks (MLNs) are a prominent statistical relati...