We propose an approximate Bayesian approach for unsupervised feature selection and density estimation, where the importance of the features for clustering is used as the measure f...
The main purpose of this paper is to propose a Multi-Agent Autonomic and Bio-Inspired based framework with selfmanaging capabilities to solve complex scheduling problems using coo...
We present a framework for modeling the spread of pathogens throughout a population and generating policies that minimize the impact of those pathogens on the population. This fra...
—Cognitive Radio Networks (CRNs) have recently emerged as a promising technology to improve spectrum utilization by allowing secondary users to dynamically access idle primary ch...
We present a simple but efficient model for object segmentation in video scenes that integrates motion and color information in a joint probabilistic framework. Optical flow is mo...