ACMFed: Fair Semi-Supervised Federated Learning With Additional Compromise Model
Sign Up to like & getrecommendations! Published in 2025 at "IEEE Access"
DOI: 10.1109/access.2025.3536639
Abstract: One of the major drawbacks of federated learning (FL) is data imbalance and uneven reliability of clients, which adversely impacts model performance and generalization ability. Among these problems, data imbalance can be addressed through semi-supervised… read more here.
Keywords: compromise; semi supervised; acmfed fair; model ... See more keywords
Semi-Supervised Federated Learning via Dual Contrastive Learning and Soft Labeling for Intelligent Fault Diagnosis
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DOI: 10.1109/jiot.2025.3586718
Abstract: intelligent fault diagnosis (IFD) plays a crucial role in ensuring the safe operation of industrial machinery and improving production efficiency. However, traditional supervised deep learning methods require a large amount of training data and labels,… read more here.
Keywords: dual contrastive; semi supervised; intelligent fault; fault diagnosis ... See more keywords
Asynchronous Semi-Supervised Federated Learning with Provable Convergence in Edge Computing
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DOI: 10.1109/mnet.001.2200223
Abstract: Traditional federated learning methods assume that users have fully labeled data in their device for training, but in practice, labels are difficult to obtain due to various reasons such as user privacy concerns, high labeling… read more here.
Keywords: semi supervised; federated learning; provable convergence; supervised federated ... See more keywords
Enhancing Semi-Supervised Federated Learning With Progressive Training in Heterogeneous Edge Computing
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DOI: 10.1109/tmc.2024.3492140
Abstract: Federated learning (FL) is an efficient distributed learning method that facilitates collaborative model training among multiple edge devices (or clients). However, current research always assumes that clients have access to ground-truth data for training, which… read more here.
Keywords: progressive training; training; semi supervised; model ... See more keywords
Semi-Supervised Federated Analytics for Heterogeneous Household Characteristics Identification
Sign Up to like & getrecommendations! Published in 2024 at "IEEE Transactions on Smart Grid"
DOI: 10.1109/tsg.2024.3415504
Abstract: The widespread use of smart meters in households paves the way for retailers to understand household patterns through electricity usage data. This insight helps them offer personalized services and create better demand response strategies. However,… read more here.
Keywords: federated analytics; supervised federated; household characteristics; semi supervised ... See more keywords