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ICML
2010
IEEE
13 years 8 months ago
Learning Markov Logic Networks Using Structural Motifs
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...
Stanley Kok, Pedro Domingos
ICML
2009
IEEE
14 years 8 months ago
Learning Markov logic network structure via hypergraph lifting
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...
Stanley Kok, Pedro Domingos
DSS
2011
12 years 11 months ago
Estimating the effect of word of mouth on churn and cross-buying in the mobile phone market with Markov logic networks
Abstract: Much has been written about word of mouth and customer behavior. Telephone call detail records provide a novel way to understand the strength of the relationship between ...
Torsten Dierkes, Martin Bichler, Ramayya Krishnan
AAAI
2010
13 years 9 months ago
Structure Learning for Markov Logic Networks with Many Descriptive Attributes
Many machine learning applications that involve relational databases incorporate first-order logic and probability. Markov Logic Networks (MLNs) are a prominent statistical relati...
Hassan Khosravi, Oliver Schulte, Tong Man, Xiaoyua...
PKDD
2010
Springer
148views Data Mining» more  PKDD 2010»
13 years 6 months ago
Exploiting Causal Independence in Markov Logic Networks: Combining Undirected and Directed Models
Abstract. A new method is proposed for compiling causal independencies into Markov logic networks (MLNs). An MLN can be viewed as compactly representing a factorization of a joint ...
Sriraam Natarajan, Tushar Khot, Daniel Lowd, Prasa...