Distributed systems are inherently complex, and therefore difficult to design and develop. Experience shows that new technologies—such as components, aspects, and application f...
The paper introduces a new framework for feature learning in classification motivated by information theory. We first systematically study the information structure and present a n...
To bridge the semantic gap in content-based image retrieval, detecting meaningful visual entities (e.g. faces, sky, foliage, buildings etc) in image content and classifying images...
Abstract. We propose an algorithm for Sparse Bayesian Classification for multi-class problems using Automatic Relevance Determination(ARD). Unlike other approaches which treat mult...
This paper presents SAgent, a general-purpose mobile agent security framework that is designed to protect the computations of mobile agent applications in potentially hostile envi...