We address the problem of learning a kernel for a given supervised learning task. Our approach consists in searching within the convex hull of a prescribed set of basic kernels fo...
Andreas Argyriou, Raphael Hauser, Charles A. Micch...
Modern applications requiring spatial network processing pose many interesting query optimization challenges. In many cases, query processing depends on the corresponding graph si...
Eleftherios Tiakas, Apostolos N. Papadopoulos, Ale...
This article is devoted to adverse selection problems in which individual private information is a whole utility function and cannot be reduced to some finite-dimensional parameter...
Abstract. In this paper, we propose a new constraint-handling technique for evolutionary algorithms which is based on multiobjective optimization concepts. The approach uses Pareto...
Cost-based query optimizers need to estimate the selectivity of conjunctive predicates when comparing alternative query execution plans. To this end, advanced optimizers use multi...
Volker Markl, Nimrod Megiddo, Marcel Kutsch, Tam M...