A DQN-Based Multi-Objective Participant Selection for Efficient Federated Learning

A DQN-Based Multi-Objective Participant Selection for Efficient Federated Learning

As a new distributed machine learning (ML) approach, federated learning (FL) shows great potential to preserve data privacy by enabling distributed data owners to collaboratively build a global model without sharing their raw data. However, the heterogeneity in terms of data distribution and hardwar...

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Bibliographic Details
Main Authors: Tongyang Xu, Yuan Liu, Zhaotai Ma, Yiqiang Huang, Peng Liu
Format: Article
Language:English
Published: MDPI AG 2023-06-01
Series:Future Internet
Subjects:
federated learning
node selection
deep reinforcement learning
multi-objective
model performance
Online Access:https://www.mdpi.com/1999-5903/15/6/209

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https://www.mdpi.com/1999-5903/15/6/209

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