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cs.LG2024★ 1 cited
Towards Resource-Efficient Federated Learning in Industrial IoT for Multivariate Time Series Analysis
Alexandros Gkillas, Aris Lalos
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, howev…
cs.LG2023
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…