96 citations · 206 across the 14 of their papers we have counts for
14 papers
A Deep Unrolling Model with Hybrid Optimization Structure for Hyperspectral Image Deconvolution
Alexandros Gkillas, Dimitris Ampeliotis, Kostas Berberidis
In recent literature there are plenty of works that combine handcrafted and learnable regularizers to solve inverse imaging problems. While this hybrid approach has demonstrated pr…
Deep Equilibrium Models Meet Federated Learning
Alexandros Gkillas, Dimitris Ampeliotis, Kostas Berberidis
In this study the problem of Federated Learning (FL) is explored under a new perspective by utilizing the Deep Equilibrium (DEQ) models instead of conventional deep learning networ…
Efficient Fully Distributed Federated Learning with Adaptive Local Links
Evangelos Georgatos, Christos Mavrokefalidis, Kostas Berberidis
Nowadays, data-driven, machine and deep learning approaches have provided unprecedented performance in various complex tasks, including image classification and object detection, a…
Connections between Deep Equilibrium and Sparse Representation Models with Application to Hyperspectral Image Denoising
Alexandros Gkillas, Dimitris Ampeliotis, Kostas Berberidis
In this study, the problem of computing a sparse representation of multi-dimensional visual data is considered. In general, such data e.g., hyperspectral images, color images or vi…
Graph Laplacian Diffusion Localization of Connected and Automated Vehicles
Nikos Piperigkos, Aris S. Lalos, Kostas Berberidis
In this paper, we design distributed multi-modal localization approaches for Connected and Automated vehicles. We utilize information diffusion on graphs formed by moving vehicles,…
A Distributed Sparse Channel Estimation Technique for mmWave Massive MIMO Systems
Maria Trigka, Christos Mavrokefalidis, Kostas Berberidis
In this paper, we study the problem of sparse channel estimation via a collaborative and fully distributed approach. The estimation problem is formulated in the angular domain by e…