In this paper we explore avenues for improving the reliability of dimensionality reduction methods such as Non-Negative Matrix Factorization (NMF) as interpretive exploratory data...
Nikolaos Vasiloglou, Alexander G. Gray, David V. A...
Despite a large body of literature and methods devoted to the Traffic Matrix (TM) estimation problem, the inference of traffic flows volume from aggregated data still represents a ...
For fast classification under real-time constraints, as required in many imagebased pattern recognition applications, linear discriminant functions are a good choice. Linear discr...
Singular Value Decomposition (and Principal Component Analysis) is one of the most widely used techniques for dimensionality reduction: successful and efficiently computable, it ...
We propose a method to demosaick images acquired with a completely arbitrary color filter array (CFA). We adopt a variational approach where the reconstructed image has maximal sm...