A Bayesian belief network is a model of a joint distribution over a finite set of variables, with a DAG structure representing immediate dependencies among the variables. For each...
— Kernel mapping is one of the most used approaches to intrinsically derive nonlinear classifiers. The idea is to use a kernel function which maps the original nonlinearly separ...
Given k sorted arrays, the t-Threshold problem, which is motivated by indexed search engines, consists of finding the elements which are present in at least t of the arrays. We pr...
In this paper we present a technique to optimize queries on deductive databases that use aggregate operations such as min, max, and “largest Ic values.” Our approach is based ...
In a variety of applications, ranging from data integration to distributed query evaluation, there is a need to obtain sets of data items from several sources (peers) and compute ...