We present a hybrid approach to Distributed Constraint Satisfaction which combines incomplete, fast, penalty-based local search with complete, slower systematic search. Thus, we pr...
General-purpose ontologies (e.g. WordNet) are convenient, but they are not always scientifically valid. We draw on techniques from semantic class learning to improve the scientific...
We introduce a new class of compiler heuristics: hybrid optimizations. Hybrid optimizations choose dynamically at compile time which optimization algorithm to apply from a set of d...
John Cavazos, J. Eliot B. Moss, Michael F. P. O'Bo...
Approaches analyzing local characteristics of an image prevail in image restoration. However, they are less effective in cases of restoring images degraded by large size point spr...
We present a weakly supervised approach to automatic Ontology Population from text and compare it with other two unsupervised approaches. In our experiments we populate a part of ...