4 accepted papers
Extracting information from functional magnetic resonance images (fMRI) has been a major area of research for more than two decades. The goal of this work is to present a new method for the analysis of fMRI data sets, that is capable to incorporate a priori available information, via an efficient op…
This paper proposes a novel algorithm for online distributed dictionary learning, where a set of nodes is requested to collectively estimate a common dictionary via sequentially received data vectors. At each time instance, in which a new datum becomes available, the sparse representation of the dat…
A promising approach when dealing with massive data sets is to apply randomized dimensionality reduction and then operate in lower dimensions. This paper deals with the randomized linear regression task in the case where the available data are sporadically corrupted. Instead of relying to minimizati…
This paper presents pattern classification to a predefined set of classes as a missing data task. This is achieved by first augmenting the feature vector of each training pattern with the corresponding binary codeword representing its class. A Restricted Boltzmann Machine (RBM) or a Dictionary Learn…