We consider principal component analysis (PCA) in decomposable Gaussian graphical models. We exploit the prior information in these models in order to distribute its computation. ...
Buffer overrun vulnerabilities cause significant security problems, and have proven to be difficult to prevent. In this paper we present a novel approach to tackling the problem...
David Llewellyn-Jones, Madjid Merabti, Qi Shi, Bob...
This paper addresses the application of a PCA analysis on categorical data prior to diagnose a patients data set using a Case-Based Reasoning (CBR) system. The particularity is th...
In the paper, we present a new approach to multi-way Blind Source Separation (BSS) and corresponding 3D tensor factorization that has many potential applications in neuroscience an...
Andrzej Cichocki, Anh Huy Phan, Rafal Zdunek, Liqi...
In this paper we present a methodology and set of tools which assist the construction of applications from components, by separating the issues of transmission policy from compone...
Scott M. Walker, Alan Dearle, Graham N. C. Kirby, ...