We consider the problem of clustering in domains where the affinity relations are not dyadic (pairwise), but rather triadic, tetradic or higher. The problem is an instance of the ...
Correlation mining has been widely studied due to its ability for discovering the underlying occurrence dependency between objects. However, correlation mining in graph databases ...
Abstract— Making inferences and choosing appropriate responses based on incomplete, uncertainty and noisy data is challenging in financial settings particularly in bankruptcy de...
A distributed estimation algorithm for sensor networks is proposed. A noisy time-varying signal is jointly tracked by a network of sensor nodes, in which each node computes its es...
Alberto Speranzon, Carlo Fischione, Karl Henrik Jo...
Many divide-and-conquer algorithms employ the fact that the vertex set of a graph of bounded treewidth can be separated in two roughly balanced subsets by removing a small subset o...
Fedor V. Fomin, Daniel Lokshtanov, Fabrizio Grando...