We boost the efficiency and robustness of distributionbased matching by random subsampling which results in the minimum number of samples required to achieve a specified probabili...
Estimation of distribution algorithms (EDAs) are population-based heuristic search methods that use probabilistic models of good solutions to guide their search. When applied to co...
This paper investigates the problem ofautomatically learning declarative models of information sources available on the Internet. We report on ILA, a domain-independent program th...
Abstract. We apply a recent formalization of visualization as information retrieval to linear projections. We introduce a method that optimizes a linear projection for an informati...
We present an information theoretic approach for learning a linear dimension reduction transform for object classification. The theoretic guidance of the approach is that the trans...