In the Bayesian mixture modeling framework it is possible to infer the necessary number of components to model the data and therefore it is unnecessary to explicitly restrict the n...
A Multivariate Gaussian random number generator (MVGRNG) is an essential block for many hardware designs, including Monte Carlo simulations. These simulations are usually used in a...
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...
Many scientific and engineering applications, which are increasingly being ported from software to reconfigurable platforms, require Gaussian-distributed random numbers. Thus, the...
Hassan Edrees, Brian Cheung, McCullen Sandora, Dav...
The estimation of high-dimensional probability density functions (PDFs) is not an easy task for many image processing applications. The linear models assumed by widely used transf...