دورية أكاديمية

A composition–decomposition based federated learning

التفاصيل البيبلوغرافية
العنوان: A composition–decomposition based federated learning
المؤلفون: Chaoli Sun, Xiaojun Wang, Junwei Ma, Gang Xie
المصدر: Complex & Intelligent Systems, Vol 10, Iss 1, Pp 1027-1042 (2023)
بيانات النشر: Springer, 2023.
سنة النشر: 2023
المجموعة: LCC:Electronic computers. Computer science
LCC:Information technology
مصطلحات موضوعية: Federated learning, Composition and decomposition, Clustering, Electronic computers. Computer science, QA75.5-76.95, Information technology, T58.5-58.64
الوصف: Abstract Federated learning has been shown to be efficient for training a global model without needing to collect all data from multiple entities to the centralized server. However, the model performance, communication traffic, and data privacy and security are still the focus of federated learning after it has been developed. In this paper, a composition–decomposition based federated learning, denoted as CD-FL, is proposed. In the CD-FL approach, the global model, composed of K sub-models with the same framework, will be decomposed and broadcast to all clients. Each client will randomly choose a sub-model, update its parameters using its own dataset, and upload this sub-model to the server. All sub-models, including the sub-models before and after updating, will be clustered into K clusters to form the global model of the next round. Experimental results on Fashion-MNIST, CIFAR-10, EMNIST, and Tiny-IMAGENET datasets show the efficiency of the model performance and communication traffic of the proposed method.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 2199-4536
2198-6053
Relation: https://doaj.org/toc/2199-4536; https://doaj.org/toc/2198-6053
DOI: 10.1007/s40747-023-01198-x
URL الوصول: https://doaj.org/article/99faf0789dde4c3a97c9d00e6d840fd1
رقم الأكسشن: edsdoj.99faf0789dde4c3a97c9d00e6d840fd1
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:21994536
21986053
DOI:10.1007/s40747-023-01198-x