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ECCV
2008
Springer
13 years 7 months ago
Event Modeling and Recognition Using Markov Logic Networks
Abstract. We address the problem of visual event recognition in surveillance where noise and missing observations are serious problems. Common sense domain knowledge is exploited t...
Son Dinh Tran, Larry S. Davis
ML
2006
ACM
131views Machine Learning» more  ML 2006»
13 years 5 months ago
Markov logic networks
We propose a simple approach to combining first-order logic and probabilistic graphical models in a single representation. A Markov logic network (MLN) is a first-order knowledge b...
Matthew Richardson, Pedro Domingos
ICML
2007
IEEE
14 years 6 months ago
Bottom-up learning of Markov logic network structure
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...
Lilyana Mihalkova, Raymond J. Mooney
ECAI
2008
Springer
13 years 7 months ago
Structure Learning of Markov Logic Networks through Iterated Local Search
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...
Marenglen Biba, Stefano Ferilli, Floriana Esposito
AAAI
2008
13 years 7 months ago
Hybrid Markov Logic Networks
Markov logic networks (MLNs) combine first-order logic and Markov networks, allowing us to handle the complexity and uncertainty of real-world problems in a single consistent fram...
Jue Wang, Pedro Domingos