Federated Learning: Collaborative Machine Learning Without Data Sharing
Keywords:
Privacy-Preserving Machine Learning, Decentralized Model Training, Secure Multi-Party Computation, Data Sovereignty, Edge Computing IntelligenceAbstract
Federated learning is a radically new model of machine learning methods, which allows the developmentof models on top of cooperative distributed devices or institutions without the need to centralize raw data. This new method ensures
References
H. Brendan McMahan et al. "Communication-Efficient Learning of Deep Networks from
Decentralized Data," arXiv:1602.05629, 2023. https://arxiv.org/abs/1602.05629
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Published
2024-12-02
How to Cite
Sudhakar Kandhikonda. (2024). Federated Learning: Collaborative Machine Learning Without Data Sharing . Journal of Computational Analysis and Applications (JoCAAA), 34(12), 10–20. Retrieved from https://eudoxuspress.com/index.php/pub/article/view/4285
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