Communication-efficient distributed deep learning: A comprehensive survey

Z Tang, S Shi, W Wang, B Li, X Chu - ar** via calibrated compensation
H Wang, W Xu, Y Fan, R Li… - IEEE INFOCOM 2023-IEEE …, 2023 - ieeexplore.ieee.org
Federated Learning enables collaboratively model training among a number of distributed
devices with the coordination of a centralized server, where each device alternatively …

Distributed differentially-private learning with communication efficiency

TT Phuong - Journal of Systems Architecture, 2022 - Elsevier
In this paper, we propose a new algorithm for learning over distributed data such as in the
IoT environment, in a privacy-preserving way. Our algorithm is a differentially private variant …

Adaptive decentralized federated learning in resource-constrained IoT networks

M Du, H Zheng, M Gao, X Feng - IEEE Internet of Things …, 2023 - ieeexplore.ieee.org
Decentralized federated learning (DFL) is a novel distributed machine-learning paradigm
where participants collaborate to train machine-learning models without the assistance of …