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Deep Federated Learning for Autonomous Driving. (arXiv:2110.05754v2 [cs.LG] UPDATED)
April 20, 2022, 1:12 a.m. | Anh Nguyen, Tuong Do, Minh Tran, Binh X. Nguyen, Chien Duong, Tu Phan, Erman Tjiputra, Quang D. Tran
cs.LG updates on arXiv.org arxiv.org
Autonomous driving is an active research topic in both academia and industry.
However, most of the existing solutions focus on improving the accuracy by
training learnable models with centralized large-scale data. Therefore, these
methods do not take into account the user's privacy. In this paper, we present
a new approach to learn autonomous driving policy while respecting privacy
concerns. We propose a peer-to-peer Deep Federated Learning (DFL) approach to
train deep architectures in a fully decentralized manner and remove the …
arxiv autonomous autonomous driving driving federated learning learning
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