137 citations · 241 across the 7 of their papers we have counts for
7 papers
Weak lensing mass reconstruction using sparsity and a Gaussian random field
J. -L. Starck, K. E. Themelis, N. Jeffrey +2
We introduce a novel approach to reconstruct dark matter mass maps from weak gravitational lensing measurements. The cornerstone of the proposed method lies in a new modelling of t…
Online Low-Rank Subspace Learning from Incomplete Data: A Bayesian View
Paris V. Giampouras, Athanasios A. Rontogiannis, Konstantinos E. Themelis +1
Extracting the underlying low-dimensional space where high-dimensional signals often reside has long been at the center of numerous algorithms in the signal processing and machine…
Simultaneously sparse and low-rank abundance matrix estimation for hyperspectral image unmixing
Paris Giampouras, Konstantinos Themelis, Athanasios Rontogiannis +1
In a plethora of applications dealing with inverse problems, e.g. in image processing, social networks, compressive sensing, biological data processing etc., the signal of interest…
Semisupervised hyperspectral image unmixing using a variational Bayes algorithm
Konstantinos E. Themelis, Athanasios A. Rontogiannis, Konstantinos D. Koutroumbas
This technical report presents a variational Bayes algorithm for semisupervised hyperspectral image unmixing. The presented Bayesian model employs a heavy tailed, nonnegatively tru…
A variational Bayes framework for sparse adaptive estimation
Konstantinos E. Themelis, Athanasios A. Rontogiannis, Konstantinos D. Koutroumbas
Recently, a number of mostly -norm regularized least squares type deterministic algorithms have been proposed to address the problem of \emph{sparse} adaptive signal estima…
Approximating the mean of a truncated normal distribution
Konstantinos D. Koutroumbas, Konstantinos E. Themelis, Athanasios A. Rontogiannis
A non trivial problem that arises in several applications is the estimation of the mean of a truncated normal distribution. In this paper, an iterative deterministic scheme for app…
On the unmixing of MEx/OMEGA hyperspectral data
Konstantinos E. Themelis, Frédéric Schmidt, Olga Sykioti +3
This article presents a comparative study of three different types of estimators used for supervised linear unmixing of two MEx/OMEGA hyperspectral cubes. The algorithms take into…