In this study, the problem of computing a sparse representation of multi-dimensional visual
data is considered. In general, such data eg, hyperspectral images, color images or video …

The problem of learning a common dictionary by following a federated learning framework,
in a network where each edge user may have statistically different data, is considered. In …

A federated dictionary learning problem, in which the edge devices have data with different
statistical properties, is considered. A dictionary learning cost function that can lead to …

The problem of computing a proper sparse representation matrix for a signal matrix that
obeys some local smoothness property, given an over-complete dictionary, is considered …

In this paper, we propose a novel methodology for addressing the hyperspectral image
deconvolution problem. This problem is highly ill-posed, and thus, requires proper priors …

The rapid advancements in technology and the proliferation of digital devices have led to an
unprecedented explosion of data [14]. This data is generated continuously by a myriad of …