To increase the relevancy of local patterns discovered from noisy relations, it makes sense to formalize error-tolerance. Our starting point is to address the limitations of state...
To model combinatorial decision problems involving uncertainty and probability, we introduce stochastic constraint programming. Stochastic constraint programs contain both decision...
Abstract. Finding the optimal selection of an OWL reasoner and service interface for a specific ontology-based application is challenging. Over time it has become more and more di...
We introduce perturbation kernels, a new class of similarity measure for information retrieval that casts word similarity in terms of multi-task learning. Perturbation kernels mode...
This paper is concerned with the estimation of steganographic capacity in digital images, using information theoretic bounds and very large-scale experiments to approximate the dis...