123 search results - page 2 / 25 » Learning the structure of Markov logic networks |
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...
ICML
2010
IEEE
13 years 5 months ago
2010
IEEE
Markov logic networks (MLNs) use firstorder formulas to define features of Markov networks. Current MLN structure learners can only learn short clauses (4-5 literals) due to extre...
AAAI
2010
13 years 5 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...
AAAI
2007
13 years 6 months ago
2007
Transfer learning addresses the problem of how to leverage knowledge acquired in a source domain to improve the accuracy and speed of learning in a related target domain. This pap...
IJCAI
2007
13 years 5 months ago
2007
A formula in first-order logic can be viewed as a tree, with a logical connective at each node, and a knowledge base can be viewed as a tree whose root is a conjunction. Markov l...