In this paper, we present the results of a project that seeks to transform low-level features to a higher level of meaning. This project concerns a technique, latent semantic inde...
This perspective paper explores principles of unsupervised learning and how they relate to face recognition. Dependency coding and information maximization appear to be central pr...
In this paper we present a clustered, multiple-clock domain (CMCD) microarchitecture that combines the benefits of both clustering and Globally Asynchronous Locally Synchronous (G...
The existence of good probabilistic models for the job arrival process and job characteristics is important for the improved understanding of grid systems and the prediction of th...
Michael Oikonomakos, Kostas Christodoulopoulos, Em...
Abstract--This paper is focusing on exact Bayesian reasoning in systems of agents, which represent weakly coupled processing modules supporting collaborative inference through mess...