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Published in 2025 at "IEEE Internet of Things Journal"
DOI: 10.1109/jiot.2025.3528624
Abstract: In the advancement of collaborative intelligence within the Internet of Things (IoT), federated learning (FL) enables clients to collaboratively train a global model without centralizing raw data. However, the non-independent and identically distributed (non-IID) nature…
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Keywords:
clustered federated;
model;
federated learning;
cfl ... See more keywords
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Published in 2024 at "IEEE Transactions on Communications"
DOI: 10.1109/tcomm.2024.3366394
Abstract: Clustered federated learning is a popular paradigm to tackle data heterogeneity in federated learning, by training personalized models for groups of users with similar data distributions. A critical challenge is to protect the privacy of…
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Keywords:
information;
clustered federated;
secure aggregation;
user updates ... See more keywords
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Published in 2023 at "IEEE transactions on neural networks and learning systems"
DOI: 10.1109/tnnls.2023.3264740
Abstract: Federated learning (FL) is a distributed machine learning framework that allows resource-constrained clients to train a global model jointly without compromising data privacy. Although FL is widely adopted, high degrees of systems and statistical heterogeneity…
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Keywords:
heterogeneity;
clustered federated;
federated learning;
statistical heterogeneity ... See more keywords
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Published in 2025 at "Energies"
DOI: 10.3390/en18092380
Abstract: Explainable Artificial Intelligence (XAI) is a well-established and dynamic field defined by an active research community that has developed numerous effective methods for explaining and interpreting the predictions of advanced machine learning models, including deep…
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Keywords:
clustered federated;
explainable clustered;
explainability;
solar energy ... See more keywords