Towards efficient communications in federated learning: A contemporary survey

Z Zhao, Y Mao, Y Liu, L Song, Y Ouyang… - Journal of the Franklin …, 2023 - Elsevier
In the traditional distributed machine learning scenario, the user's private data is transmitted
between clients and a central server, which results in significant potential privacy risks. In …

Towards Efficient Communications in Federated Learning: A Contemporary Survey

Z Zhao, Y Mao, Y Liu, L Song, Y Ouyang… - arXiv preprint arXiv …, 2022 - arxiv.org
In the traditional distributed machine learning scenario, the user's private data is transmitted
between clients and a central server, which results in significant potential privacy risks. In …

Towards efficient communications in federated learning: A contemporary survey

Z Zhao, Y Mao, Y Liu, L Song, Y Ouyang… - Journal of the …, 2023 - scholars.cityu.edu.hk
In the traditional distributed machine learning scenario, the user's private data is transmitted
between clients and a central server, which results in significant potential privacy risks. In …

Towards Efficient Communications in Federated Learning: A Contemporary Survey

Z Zhao, Y Mao, Y Liu, L Song, Y Ouyang… - arXiv e …, 2022 - ui.adsabs.harvard.edu
In the traditional distributed machine learning scenario, the user's private data is transmitted
between clients and a central server, which results in significant potential privacy risks. In …

Towards efficient communications in federated learning: A contemporary survey

Z Zhao, Y Mao, Y Liu, L Song, Y Ouyang… - Journal of the Franklin …, 2023 - Elsevier
In the traditional distributed machine learning scenario, the user's private data is transmitted
between clients and a central server, which results in significant potential privacy risks. In …