5 citations · 7 across the 6 of their papers we have counts for
6 papers
Federated Learning in Mobile Networks: A Comprehensive Case Study on Traffic Forecasting
Nikolaos Pavlidis, Vasileios Perifanis, Selim F. Yilmaz +6
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 t…
Intelligent Client Selection for Federated Learning using Cellular Automata
Nikolaos Pavlidis, Vasileios Perifanis, Theodoros Panagiotis Chatzinikolaou +2
Federated Learning (FL) has emerged as a promising solution for privacy-enhancement and latency minimization in various real-world applications, such as transportation, communicati…
Towards Energy-Aware Federated Traffic Prediction for Cellular Networks
Vasileios Perifanis, Nikolaos Pavlidis, Selim F. Yilmaz +6
Cellular traffic prediction is a crucial activity for optimizing networks in fifth-generation (5G) networks and beyond, as accurate forecasting is essential for intelligent network…
Federated Learning for Early Dropout Prediction on Healthy Ageing Applications
Christos Chrysanthos Nikolaidis, Vasileios Perifanis, Nikolaos Pavlidis +1
The provision of social care applications is crucial for elderly people to improve their quality of life and enables operators to provide early interventions. Accurate predictions…
Predicting Early Dropouts of an Active and Healthy Ageing App
Vasileios Perifanis, Ioanna Michailidi, Giorgos Stamatelatos +2
In this work, we present a machine learning approach for predicting early dropouts of an active and healthy ageing app. The presented algorithms have been submitted to the IFMBE Sc…
FedPOIRec: Privacy Preserving Federated POI Recommendation with Social Influence
Vasileios Perifanis, George Drosatos, Giorgos Stamatelatos +1
With the growing number of Location-Based Social Networks, privacy preserving location prediction has become a primary task for helping users discover new points-of-interest (POIs)…