Semi-Synchronous Federated Learning for Energy-Efficient Training and Accelerated Convergence in Cross-Silo Settings. Stripelis, D., Thompson, P. M., & Ambite, J. L. ACM Transactions on Intelligent Systems and Technology, Special Issue on Federated Learning: Algorithms, Systems, and Applications, 13(5):1–29, Association for Computing Machinery, New York, NY, USA, 2022. ![Semi-Synchronous Federated Learning for Energy-Efficient Training and Accelerated Convergence in Cross-Silo Settings [link]](https://bibbase.org/img/filetypes/link.svg "link")
Paper doi bibtex @article{stripelis2022:semisync,
title={Semi-Synchronous Federated Learning for Energy-Efficient Training and Accelerated Convergence in Cross-Silo Settings},
author={Stripelis, Dimitris and Thompson, Paul M. and Ambite, Jos\'{e} Luis},
journal={ACM Transactions on Intelligent Systems and Technology, Special Issue on Federated Learning: Algorithms, Systems, and Applications},
volume = {13},
number = {5},
pages = {1--29},
year = {2022},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
issn = {2157-6904},
url = {https://doi.org/10.1145/3524885},
doi = {10.1145/3524885},
}
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