Federated Learning With Dataset Splitting and Weighted Mean Using Particle Swarm Optimization

Federated Learning With Dataset Splitting and Weighted Mean Using Particle Swarm Optimization

Federated learning uses the concept of decentralized training of n number of local clients for a small number of epochs say 2-5, and then averaging the learned weights of all local clients, and evaluating on test dataset with the average weights loaded to a global model. The train dataset is split i...

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Bibliographic Details
Main Authors: Mohit Agarwal, Garima Jaiswal, Rohit Kumar Kaliyar, Akansha Singh, Krishna Kant Singh, S. S. Askar, Mohamed Abouhawwash
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Access
Subjects:
Federated learning
particle swarm optimization
optimization
model performance
multimodal
Online Access:https://ieeexplore.ieee.org/document/10731716/
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