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» Bottom-up learning of Markov logic network structure
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ICML
2010
IEEE
13 years 5 months ago
Bottom-Up Learning of Markov Network Structure
The structure of a Markov network is typically learned using top-down search. At each step, the search specializes a feature by conjoining it to the variable or feature that most ...
Jesse Davis, Pedro Domingos
AIRS
2010
Springer
13 years 2 months ago
Top-Down and Bottom-Up: A Combined Approach to Slot Filling
The Slot Filling task requires a system to automatically distill information from a large document collection and return answers for a query entity with specified attributes (`slot...
Zheng Chen, Suzanne Tamang, Adam Lee, Xiang Li, Ma...
ICMLA
2010
13 years 2 months ago
Heuristic Method for Discriminative Structure Learning of Markov Logic Networks
Markov Logic Networks (MLNs) combine Markov Networks and first-order logic by attaching weights to firstorder formulas and viewing them as templates for features of Markov Networks...
Quang-Thang Dinh, Matthieu Exbrayat, Christel Vrai...
ICML
2007
IEEE
14 years 5 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