We present an incremental refinement algorithm for approximate compilation of constraint satisfaction models into multivalued decision diagrams (MDDs). The algorithm uses a vertex ...
Tarik Hadzic, John N. Hooker, Barry O'Sullivan, Pe...
In the propositional setting, a well-studied family of merging operators are distance-based ones: the models of the merged base are the closest interpretations to the given profile...
We identify four types of errors that unsupervised induction systems make and study each one in turn. Our contributions include (1) using a meta-model to analyze the incorrect bia...
A major problem in magnetic resonance imaging (MRI) is the lack of a pulse sequence dependent standardized intensity scale like the Hounsfield units in computed tomography. This af...
Abstract. We propose a new matrix learning scheme to extend Generalized Relevance Learning Vector Quantization (GRLVQ). By introducing a full matrix of relevance factors in the dis...