We present a framework that enables the use of traditional feature selection algorithms in a new context - for building a set of subsets of specified properties. During the course...
With a few exceptions, discriminative training in statistical machine translation (SMT) has been content with tuning weights for large feature sets on small development data. Evid...
With increasing interest in bioinformatics, sophisticated tools are required to efficiently analyze gene information. The classification of gene expression profiles is crucial in ...
Deciding what to sense is a crucial task, made harder by dependencies and by a nonadditive utility function. We develop approximation algorithms for selecting an optimal set of me...
This paper describes a new algorithm to solve the decision making problem in Influence Diagrams based on algorithms for credal networks. Decision nodes are associated to imprecise...