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Clustering-Based Federated Learning for Heterogeneous IoT Data
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Federated Learning (FL) can use data from Internet of Things (IoT) devices to collaboratively train a shared model and protect data privacy.
Aug 7, 2023 · In this article, we propose a local differentially private scheme to train clustered FL models on heterogeneous IoT data by using adaptive clipping, weight ...
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Abstract—Federated Learning (FL) can use data from Internet of Things (IoT) devices to collaboratively train a shared model and protect data privacy.
May 4, 2024 · Clustering-Based Federated Learning for Heterogeneous IoT Data ... A Two Layer Model enabled by Federated Learning in the IoT based Smart Grid ...
Experiments on multiple benchmark datasets show that FedPCC can improve the accuracy of the client model and is sufficiently robust in heterogeneous ...
We propose and test a clustered FL architecture for unsupervised anomaly detection IDS model training applied to a network of heterogeneous IoT devices. We test ...
We propose ClusterFL, a clustering-based federated learning system that can provide high model accuracy and low communication overhead for HAR applications.
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What is heterogeneous federated learning?
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What is federated learning in IoT?
Although federated learning has been widely used in collaborative training of machine learning models, its practical uses are still challenged by heterogeneous ...
This scenario, known as statistical heterogeneity of the collected clients' (i.e., IoT devices') datasets, poses a challenge for a federated learning setting. [ ...