Incorporating semantic features from the WordNet lexical database is among one of the many approaches that have been tried to improve the predictive performance of text classifica...
Background: Graph theory provides a computational framework for modeling a variety of datasets including those emerging from genomics, proteomics, and chemical genetics. Networks ...
Joshua J. Forman, Paul A. Clemons, Stuart L. Schre...
Many techniques for the verification of reactive systems rely on the analysis of their reachable state spaces. In this paper, a new algorithm for the symbolic generation of the sta...
We show how to use unlabeled data and a deep belief net (DBN) to learn a good covariance kernel for a Gaussian process. We first learn a deep generative model of the unlabeled da...
—In this paper, we proposed a reduced polynomial neural swarm net (RPNSN) for the task of classification. Classification task is one of the most studied tasks of data mining. In ...