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ICLP
2009
Springer
16 years 7 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...
EUROPAR
2000
Springer
15 years 10 months ago
Novel Models for Or-Parallel Logic Programs: A Performance Analysis
One of the advantages of logic programming is the fact that it offers many sources of implicit parallelism, such as and-parallelism and or-parallelism. Arguably, or-parallel system...
Vítor Santos Costa, Ricardo Rocha, Fernando...
CVPR
2012
IEEE
13 years 8 months ago
A grammar for hierarchical object descriptions in logic programs
Modeling objects using formal grammars has recently regained much attention in computer vision. Probabilistic logic programming, such as Bilattice based Logical Reasoning (BLR), i...
Toufiq Parag, Claus Bahlmann, Vinay D. Shet, Manee...
CORR
2000
Springer
120views Education» more  CORR 2000»
15 years 6 months ago
Scaling Up Inductive Logic Programming by Learning from Interpretations
When comparing inductive logic programming (ILP) and attribute-value learning techniques, there is a trade-off between expressive power and efficiency. Inductive logic programming ...
Hendrik Blockeel, Luc De Raedt, Nico Jacobs, Bart ...
AI
2004
Springer
15 years 6 months ago
Order-sorted logic programming with predicate hierarchy
Order-sorted logic has been formalized as first-order logic with sorted terms where sorts are ordered to build a hierarchy (called a sort-hierarchy). These sorted logics lead to u...
Ken Kaneiwa