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ICML
2010
IEEE
15 years 2 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
CORR
2004
Springer
128views Education» more  CORR 2004»
15 years 1 months ago
Specialization of Functional Logic Programs Based on Needed Narrowing
Many functional logic languages are based on narrowing, a unification-based goal-solving mechanism which subsumes the reduction mechanism of functional languages and the resolutio...
María Alpuente, Michael Hanus, Salvador Luc...
AAAI
1998
15 years 2 months ago
Machine Learning of Generic and User-Focused Summarization
A key problem in text summarization is finding a salience function which determines what information in the source should be included in the summary. This paper describes the use ...
Inderjeet Mani, Eric Bloedorn
ICFP
2002
ACM
16 years 1 months ago
A compiled implementation of strong reduction
Motivated by applications to proof assistants based on dependent types, we develop and prove correct a strong reducer and equivalence checker for the -calculus with products, sums...
Benjamin Grégoire, Xavier Leroy
CORR
2007
Springer
127views Education» more  CORR 2007»
15 years 1 months ago
Learning Phonotactics Using ILP
This paper describes experiments on learning Dutch phonotactic rules using Inductive Logic Programming, a machine learning approach based on the notion of inverting resolution. Di...
Stasinos Konstantopoulos