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KR
1992
Springer
14 years 2 months ago
Learning Useful Horn Approximations
While the task of answering queries from an arbitrary propositional theory is intractable in general, it can typicallybe performed e ciently if the theory is Horn. This suggests t...
Russell Greiner, Dale Schuurmans
AAAI
1996
13 years 11 months ago
Post-Analysis of Learned Rules
Rule induction research implicitly assumes that after producing the rules from a dataset, these rules will be used directly by an expert system or a human user. In real-life appli...
Bing Liu, Wynne Hsu
ICSE
2005
IEEE-ACM
14 years 3 months ago
Observations and lessons learned from automated testing
This report addresses some of our observations made in a dozen of projects in the area of software testing, and more specifically, in automated testing. It documents, analyzes and...
Stefan Berner, Roland Weber, Rudolf K. Keller
LREC
2008
110views Education» more  LREC 2008»
13 years 11 months ago
Unsupervised and Domain Independent Ontology Learning: Combining Heterogeneous Sources of Evidence
Acquiring knowledge from the Web to build domain ontologies has become a common practice in the Ontological Engineering field. The vast amount of freely available information allo...
David Manzano-Macho, Asunción Gómez-...
CVPR
2009
IEEE
1081views Computer Vision» more  CVPR 2009»
15 years 5 months ago
Learning Real-Time MRF Inference for Image Denoising
Many computer vision problems can be formulated in a Bayesian framework with Markov Random Field (MRF) or Conditional Random Field (CRF) priors. Usually, the model assumes that ...
Adrian Barbu (Florida State University)