Abstract--This paper presents a framework for privacypreserving Gaussian Mixture Model computations. Specifically, we consider a scenario where a central service wants to learn the...
In this paper, we propose a semi-supervised kernel matching method to address domain adaptation problems where the source distribution substantially differs from the target distri...
Users have been demanding information “anytime, anywhere”. The notion of accessing diverse and autonomous information repositories with different APIs is not accepted. This ha...
In this paper we model relational random variables on the edges of a network using Gaussian processes (GPs). We describe appropriate GP priors, i.e., covariance functions, for dir...
Schema matching is a complex process focusing on matching between concepts describing the data in heterogeneous data sources. There is a shift from manual schema matching, done by...