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ICLP
2009
Springer
14 years 5 months ago
Using Histograms to Better Answer Queries to Probabilistic Logic Programs
Probabilistic logic programs (PLPs) define a set of probability distribution functions (PDFs) over the set of all Herbrand interpretations of the underlying logical language. When...
Matthias Broecheler, Gerardo I. Simari, V. S. Subr...
ICLP
2010
Springer
13 years 8 months ago
Tabling and Answer Subsumption for Reasoning on Logic Programs with Annotated Disjunctions
Probabilistic Logic Programming is an active field of research, with many proposals for languages, semantics and reasoning algorithms. One such proposal, Logic Programming with A...
Fabrizio Riguzzi, Terrance Swift
PVLDB
2010
252views more  PVLDB 2010»
12 years 11 months ago
Efficient and Effective Similarity Search over Probabilistic Data based on Earth Mover's Distance
Probabilistic data is coming as a new deluge along with the technical advances on geographical tracking, multimedia processing, sensor network and RFID. While similarity search is...
Jia Xu, Zhenjie Zhang, Anthony K. H. Tung, Ge Yu
ML
2006
ACM
131views Machine Learning» more  ML 2006»
13 years 4 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
JAR
2002
83views more  JAR 2002»
13 years 4 months ago
Mathematical Programming Embeddings of Logic
Abstract. Can theorem proving in mathematical logic be addressed by classical mathematical techniques like the calculus of variations? The answer is surprisingly in the affirmative...
Vivek S. Borkar, Vijay Chandru, Sanjoy K. Mitter