Accelerating Fair Federated Learning: Adaptive Federated Adam

Federated learning is a distributed and privacy-preserving approach to train a statistical model collaboratively from decentralized data held by different parties. However, when the datasets are not independent and identically distributed, models trained by naive federated algorithms may be biased t...

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الحاوية / القاعدة:	IEEE Transactions on Machine Learning in Communications and Networking
المؤلفون الرئيسيون:	Li Ju, Tianru Zhang, Salman Toor, Andreas Hellander
التنسيق:	مقال
اللغة:	الإنجليزية
منشور في:	IEEE 2024-01-01
الموضوعات:	Distributed learning fair machine learning federated learning federated optimization
الوصول للمادة أونلاين:	https://ieeexplore.ieee.org/document/10584508/