We study runtime distributions of subsumption testing. On graph data randomly sampled from two different generative models we observe a gradual growth of the tails of the distribut...
Abstract. We consider the problem of aligning two metabolic pathways. Unlike traditional approaches, we do not restrict the alignment to one-to-one mappings between the molecules o...
We introduce a multi-stage ensemble framework, ErrorDriven Generalist+Expert or Edge, for improved classification on large-scale text categorization problems. Edge first trains a ...
We study the problem of learning an optimal Bayesian network in a constrained search space; skeletons are compelled to be subgraphs of a given undirected graph called the super-st...
Kaname Kojima, Eric Perrier, Seiya Imoto, Satoru M...
—In this paper, we investigate the problem of supporting keyword-based searching for the discovery of software resources that are installed on the nodes of largescale, federated ...
George Pallis, Asterios Katsifodimos, Marios D. Di...