Nov 23, 2022 · CF4FL aims to accelerate the convergence of FL training process through the innovation of two complementary networking components.
Abstract—Federated Learning (FL) is a promising technique to enhance the safety and efficiency of intelligent transportation systems.
In this paper, we present a communication framework for FL (CF4FL) in transportation systems. CF4FL aims to accelerate the convergence of FL training process ...
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CF4FL A Communication Framework for Federated Learning in Transportation Systems · Certifying Black Box Policies With Stability for Nonlinear Control.
This paper presents a personalized architecture, including an optimized Federated Averaging strategy that leverages FL for efficient and real-time Big Data ...
CF4FL: A Communication Framework for Federated Learning in Transportation Systems · Pedram KheirkhahSangdeh Chengzhang +7 authors. Zeng. Engineering, Computer ...
CF4FL: A Communication Framework for Federated Learning in Transportation Systems. Pedram Kheirkhah Sangdeh ... Y Thomas Hou. IEEE Transactions on Wireless ...
Oct 22, 2024 · Federated learning is a distributed machine learning paradigm, which aims to train a model using the local data of many distributed clients.
By allowing machine learning models to be trained across multiple decentralized devices or servers, FL eliminates the need to move data to a central location.
CF4FL: A Communication Framework for Federated Learning in Transportation Systems · Engineering, Computer Science. IEEE Transactions on Wireless Communications.