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» A Framework for Belief Update
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106
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ECML
2003
Springer
15 years 5 months ago
Robust k-DNF Learning via Inductive Belief Merging
A central issue in logical concept induction is the prospect of inconsistency. This problem may arise due to noise in the training data, or because the target concept does not fit...
Frédéric Koriche, Joël Quinquet...
94
Voted
TPLP
2010
115views more  TPLP 2010»
14 years 11 months ago
Towards closed world reasoning in dynamic open worlds
The need for integration of ontologies with nonmonotonic rules has been gaining importance in a number of areas, such as the Semantic Web. A number of researchers addressed this p...
Martin Slota, João Leite
SYNTHESE
2010
129views more  SYNTHESE 2010»
14 years 11 months ago
Belief and contextual acceptance
I develop a strategy for representing epistemic states and epistemic changes that seeks to be sensitive to the difference between voluntary and involuntary aspects of our epistemi...
Eleonora Cresto
99
Voted
ICDM
2006
IEEE
138views Data Mining» more  ICDM 2006»
15 years 6 months ago
Belief Propagation in Large, Highly Connected Graphs for 3D Part-Based Object Recognition
We describe a part-based object-recognition framework, specialized to mining complex 3D objects from detailed 3D images. Objects are modeled as a collection of parts together with...
Frank DiMaio, Jude W. Shavlik
103
Voted
CPAIOR
2008
Springer
15 years 2 months ago
Leveraging Belief Propagation, Backtrack Search, and Statistics for Model Counting
We consider the problem of estimating the model count (number of solutions) of Boolean formulas, and present two techniques that compute estimates of these counts, as well as eith...
Lukas Kroc, Ashish Sabharwal, Bart Selman