7 search results - page 1 / 2 » Structure Learning for Markov Logic Networks with Many Descr... |
AAAI
2010
13 years 6 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...
ICML
2007
IEEE
14 years 5 months ago
2007
IEEE
Markov logic networks (MLNs) are a statistical relational model that consists of weighted firstorder clauses and generalizes first-order logic and Markov networks. The current sta...
ECAI
2008
Springer
13 years 6 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...
ICML
2009
IEEE
14 years 5 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...
ICMLA
2009
13 years 2 months ago
2009
Languages that combine predicate logic with probabilities are needed to succinctly represent knowledge in many real-world domains. We consider a formalism based on universally qua...