A Framework for Energy and Carbon Footprint Analysis of Distributed and
Federated Edge Learning

A Framework for Energy and Carbon Footprint Analysis of Distributed and Federated Edge Learning

18 March 2021

Papers citing "A Framework for Energy and Carbon Footprint Analysis of Distributed and Federated Edge Learning"

9 / 9 papers shown

Title
Energy-Aware Decentralized Learning with Intermittent Model Training Akash Dhasade Paolo Dini Elia Guerra Anne-Marie Kermarrec M. Miozzo Rafael Pires Rishi Sharma M. Vos 38 0 0 01 Jul 2024
Training Machine Learning models at the Edge: A Survey Aymen Rayane Khouas Mohamed Reda Bouadjenek Hakim Hacid Sunil Aryal 29 10 0 05 Mar 2024
An effective and efficient green federated learning method for one-layer neural networks O. Fontenla-Romero Berta Guijarro-Berdiñas Elena Hernández-Pereira Beatriz Pérez-Sánchez FedML 9 0 0 22 Dec 2023
Coordination-free Decentralised Federated Learning on Complex Networks: Overcoming Heterogeneity Lorenzo Valerio C. Boldrini A. Passarella János Kertész Márton Karsai Gerardo Iniguez FedML 20 5 0 07 Dec 2023
DeepEn2023: Energy Datasets for Edge Artificial Intelligence Xiaolong Tu Anik Mallik Haoxin Wang Jiang Xie 25 1 0 30 Nov 2023
An Energy and Carbon Footprint Analysis of Distributed and Federated Learning S. Savazzi V. Rampa Sanaz Kianoush M. Bennis 17 42 0 21 Jun 2022
Caring Without Sharing: A Federated Learning Crowdsensing Framework for Diversifying Representation of Cities Mi-Gyoung Cho A. Mashhadi FedML 31 1 0 20 Jan 2022
On the Tradeoff between Energy, Precision, and Accuracy in Federated Quantized Neural Networks Minsu Kim Walid Saad Mohammad Mozaffari Merouane Debbah FedML MQ 14 23 0 15 Nov 2021
Opportunities of Federated Learning in Connected, Cooperative and Automated Industrial Systems S. Savazzi M. Nicoli M. Bennis Sanaz Kianoush Luca Barbieri FedML AIFin AI4CE 40 125 0 09 Jan 2021