Approximating the joint data distribution of a multi-dimensional data set through a compact and accurate histogram synopsis is a fundamental problem arising in numerous practical ...
Amol Deshpande, Minos N. Garofalakis, Rajeev Rasto...
Abstract: We are developing a new mashup framework for creating flexible applications in which users can selectively browse through mashup items. The framework provides GUI compone...
Numerous recent papers have found important relationships between network structure and risks within networks. These results indicate that network structure can dramatically affec...
Paul Hines, Seth Blumsack, E. Cotilla Sanchez, C. ...
Abstract: Structure learning of dynamic Bayesian networks provide a principled mechanism for identifying conditional dependencies in time-series data. This learning procedure assum...
Abstract— The Publish-Subscribe (P/S) communication paradigm fosters high decoupling among distributed components. This facilitates the design of dynamic applications, but also i...