most citedA New Clustering-Based Technique for the Acceleration of Deep Convolutional Networks

4 citations · 7 across the 5 of their papers we have counts for

collaborators

5 papers

cs.LG20223 cited

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…

cs.IT2021

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…

cs.CV2021

Accelerating deep neural networks for efficient scene understanding in automotive cyber-physical systems

Stavros Nousias, Erion-Vasilis Pikoulis, Christos Mavrokefalidis +1

Automotive Cyber-Physical Systems (ACPS) have attracted a significant amount of interest in the past few decades, while one of the most critical operations in these systems is the…

cs.LG20214 cited

A New Clustering-Based Technique for the Acceleration of Deep Convolutional Networks

Erion-Vasilis Pikoulis, Christos Mavrokefalidis, Aris S. Lalos

Deep learning and especially the use of Deep Neural Networks (DNNs) provides impressive results in various regression and classification tasks. However, to achieve these results, t…

cs.IT2021

Coalition Formation Games for Improved Cell-Edge User Service in Downlink NOMA and MU-MIMO Small Cell Systems

Panagiotis Georgakopoulos, Tafseer Akhtar, Christos Mavrokefalidis +3

In today's wireless communication systems, the exponentially growing needs of mobile users require the combination of new and existing techniques to meet the demands for reliable a…