7 search results - page 1 / 2 » Structure Learning for Markov Logic Networks with Many Descr... |
AAAI
2010
14 years 11 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
15 years 10 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
14 years 11 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
15 years 10 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...
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ICMLA
2009
14 years 7 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...