Federated Learning for Mobility Applications
The increasing concern for privacy and the use of machine learning on personal data has
led researchers to introduce new approaches to machine learning. Federated learning is …
led researchers to introduce new approaches to machine learning. Federated learning is …
Federated learning on the road autonomous controller design for connected and autonomous vehicles
The deployment of future intelligent transportation systems is contingent upon seamless and
reliable operation of connected and autonomous vehicles (CAVs). One key challenge in …
reliable operation of connected and autonomous vehicles (CAVs). One key challenge in …
On the convergence of decentralized federated learning under imperfect information sharing
Most of the current literature focused on centralized learning is centered around the
celebrated average-consensus paradigm and less attention is devoted to scenarios where …
celebrated average-consensus paradigm and less attention is devoted to scenarios where …
Blockchain-based decentralized frequency control of microgrids using federated learning fractional-order recurrent neural network
This paper presents a blockchain-based decentralized frequency control of an islanded
microgrid (MG) using a novel federated learning fractional order recurrent neural network …
microgrid (MG) using a novel federated learning fractional order recurrent neural network …
An improved big data analytics architecture using federated learning for IoT-enabled urban intelligent transportation systems
The exponential growth of the Internet of Things has precipitated a revolution in Intelligent
Transportation Systems, notably in urban environments. An ITS leverages advancements in …
Transportation Systems, notably in urban environments. An ITS leverages advancements in …
Combining federated learning and control: A survey
This survey provides an overview of combining federated learning (FL) and control to
enhance adaptability, scalability, generalization, and privacy in (nonlinear) control …
enhance adaptability, scalability, generalization, and privacy in (nonlinear) control …
Personalized Federated Learning Based Adaptive Optical Compensation for Atmospheric Turbulence
Free-space optical (FSO) technologies face significant challenges from atmospheric
turbulence, which can degrade transmission performance. Adaptive optics (AO) techniques …
turbulence, which can degrade transmission performance. Adaptive optics (AO) techniques …
Fedadt: An adaptive method based on derivative term for federated learning
H Gao, Q Wu, X Zhao, J Zhu, M Zhang - Sensors, 2023 - mdpi.com
Federated learning is served as a novel distributed training framework that enables multiple
clients of the internet of things to collaboratively train a global model while the data remains …
clients of the internet of things to collaboratively train a global model while the data remains …
Evaluating the Impact of Mobility on Differentially Private Federated Learning
E Kim, EK Lee - Applied Sciences, 2024 - mdpi.com
This paper investigates differential privacy in federated learning. This topic has been actively
examined in conventional network environments, but few studies have investigated it in the …
examined in conventional network environments, but few studies have investigated it in the …
Comparative Survey of Embedded System Implementations of Convolutional Neural Networks in Autonomous Cars Applications
In the rapidly evolving field of autonomous cars, advanced deep learning systems have
ushered in a new era of innovation, enabling the integration of unique features into vehicles …
ushered in a new era of innovation, enabling the integration of unique features into vehicles …