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 our research we are developing methodologiesand tools to permit stochastic analyses of CSP-based system specifications. In this regard, we have been developing morphismsbetween...
Krishna M. Kavi, Frederick T. Sheldon, Behrooz Shi...
—The inherent support in routers (SNMP counters or NetFlow) is not sufficient to diagnose performance problems in IP networks, especially for flow-specific problems where the ...
Myungjin Lee, Nick G. Duffield, Ramana Rao Kompell...
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...
The paper introduces a method to model embedded dependability-critical systems as AND-composition of Guarded Statecharts which are special UMLstatecharts. With Guarded Statecharts...