Background: The post-genomic era has brought new challenges regarding the understanding of the organization and function of the human genome. Many of these challenges are centered...
We present a probabilistic model-based framework for distributed learning that takes into account privacy restrictions and is applicable to scenarios where the different sites ha...
: In this paper we present our work on applying Belief Augmented Frames to the text classification problem. We formulate the problem in two alternative ways, and we evaluate the pe...
People accessing documents via the Internet typically experience latencies in retrieving content. We discuss continual-computation policies that dictate strategies for prefetching...
This paper introduces a novel statistical mixture model for probabilistic clustering of histogram data and, more generally, for the analysis of discrete co occurrence data. Adoptin...