A new distributed algorithm of data ccompression based on hierarchical cluster model for sensor networks is proposed, the basic ideas of which are as follows, firstly the whole se...
— In this article we tackle the problem of scheduling a dynamically generated DAG of multi-processor tasks (M-tasks). At first, we outline the need of such a scheduling approach...
There are many algorithms to cluster sample data points based on nearness or a similarity measure. Often the implication is that points in different clusters come from different u...
Edward R. Dougherty, Junior Barrera, Marcel Brun, ...
We develop a semi-supervised learning method that constrains the posterior distribution of latent variables under a generative model to satisfy a rich set of feature expectation c...
A maximum-entropy approach to generative similarity-based classifiers model is proposed. First, a descriptive set of similarity statistics is assumed to be sufficient for classifi...