This paper proposes a novel framework for mining regional colocation patterns with respect to sets of continuous variables in spatial datasets. The goal is to identify regions in ...
Christoph F. Eick, Jean-Philippe Nicot, Rachana Pa...
In recent years, there is a growing interest in learning Bayesian networks with continuous variables. Learning the structure of such networks is a computationally expensive proced...
This paper presents a local search algorithm based on variable depth search, called the k-opt local search, for the maximum clique problem. The k-opt local search performs add and...
Various algorithms have been developed and applied to structural optimization, in which cross-sectional areas of structure members are assumed to be continuous. In most cases of p...
Given a bipartite graph G = (S, T, E), we consider the problem of finding k bipartite subgraphs, called "clusters", such that each vertex i of S appears in exactly one o...
Stefano Gualandi, Francesco Maffioli, Claudio Magn...