Effect of Clustering in Federated Learning on Non-IID Electricity Consumption Prediction
Author:
Affiliation:
1. The University of Manchester,Department of Computer Science,UK
2. (ESAT-ELECTA) & EnergyVille,Dept. of Electrical Engineering,Leuven,KU,Belgium
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9960142/9960289/09960569.pdf?arnumber=9960569
Reference20 articles.
1. Federated learning with hierarchical clustering of local updates to improve training on non-IID data
2. Robust and communication-efficient federated learning from non-iid data;sattler;IEEE Trans on NNLS,2019
3. Federated learning for short-term residential energy demand forecasting;briggs;arXiv 2105 13325,2021
4. Federated learning with hyperparameter-based clustering for electrical load forecasting
5. Federated Learning based Energy Demand Prediction with Clustered Aggregation
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