Zobrazeno 1 - 10
of 11 331
pro vyhledávání: '"Aris, P."'
Autor:
Pavlidis, Nikolaos, Perifanis, Vasileios, Yilmaz, Selim F., Wilhelmi, Francesc, Miozzo, Marco, Efraimidis, Pavlos S., Koutsiamanis, Remous-Aris, Mulinka, Pavol, Dini, Paolo
The increasing demand for efficient resource allocation in mobile networks has catalyzed the exploration of innovative solutions that could enhance the task of real-time cellular traffic prediction. Under these circumstances, federated learning (FL)
Externí odkaz:
http://arxiv.org/abs/2412.04081
The ROC curve is a statistical tool that analyses the accuracy of a diagnostic test in which a variable is used to decide whether an individual is healthy or not. Along with that diagnostic variable it is usual to have information of some other covar
Externí odkaz:
http://arxiv.org/abs/2411.17464
Autor:
G., Daniel M. Jimenez, Solans, David, Heikkila, Mikko, Vitaletti, Andrea, Kourtellis, Nicolas, Anagnostopoulos, Aris, Chatzigiannakis, Ioannis
Recent advances in machine learning have highlighted Federated Learning (FL) as a promising approach that enables multiple distributed users (so-called clients) to collectively train ML models without sharing their private data. While this privacy-pr
Externí odkaz:
http://arxiv.org/abs/2411.12377
In this paper we propose a methodology combining Federated Learning (FL) with Cross-view Image Geo-localization (CVGL) techniques. We address the challenges of data privacy and heterogeneity in autonomous vehicle environments by proposing a personali
Externí odkaz:
http://arxiv.org/abs/2411.04692
This paper proposes a novel localization framework based on collaborative training or federated learning paradigm, for highly accurate localization of autonomous vehicles. More specifically, we build on the standard approach of KalmanNet, a recurrent
Externí odkaz:
http://arxiv.org/abs/2411.05847
Autor:
Gkillas, Alexandros, Lalos, Aris
Anomaly and missing data constitute a thorny problem in industrial applications. In recent years, deep learning enabled anomaly detection has emerged as a critical direction, however the improved detection accuracy is achieved with the utilization of
Externí odkaz:
http://arxiv.org/abs/2411.03996
Autor:
Aristorenas, Aris J.
This study presents a machine learning framework for assessing similarity between audio content and predicting sentiment score. We construct a dataset containing audio samples from music covers on YouTube along with the audio of the original song, an
Externí odkaz:
http://arxiv.org/abs/2411.00195
MIMO MAC Empowered by Reconfigurable Intelligent Surfaces: Capacity Region and Large System Analysis
Smart wireless environments enabled by multiple distributed Reconfigurable Intelligent Surfaces (RISs) have recently attracted significant research interest as a wireless connectivity paradigm for sixth Generation (6G) networks. In this paper, using
Externí odkaz:
http://arxiv.org/abs/2410.07389
Autor:
Tatli, Dimitra, Papapanagiotou, Vasileios, Liakos, Aris, Tsapas, Apostolos, Delopoulos, Anastasios
Prediabetes is a common health condition that often goes undetected until it progresses to type 2 diabetes. Early identification of prediabetes is essential for timely intervention and prevention of complications. This research explores the feasibili
Externí odkaz:
http://arxiv.org/abs/2410.02692
Low Earth Orbit Satellite Networks (LSNs) are integral to supporting a broad range of modern applications, which are typically modeled as Service Function Chains (SFCs). Each SFC is composed of Virtual Network Functions (VNFs), where each VNF perform
Externí odkaz:
http://arxiv.org/abs/2409.05025