Search Results for author:
Found 6 papers, 1 papers with code
Low-Rank Gradient Compression with Error Feedback for MIMO Wireless Federated Learning
This paper presents a novel approach to enhance the communication efficiency of federated learning (FL) in multiple input and multiple output (MIMO) wireless systems.
Task-Oriented Integrated Sensing, Computation and Communication for Wireless Edge AI
With the advent of emerging IoT applications such as autonomous driving, digital-twin and metaverse etc.
Bayesian Over-the-Air FedAvg via Channel Driven Stochastic Gradient Langevin Dynamics
The recent development of scalable Bayesian inference methods has renewed interest in the adoption of Bayesian learning as an alternative to conventional frequentist learning that offers improved model calibration via uncertainty quantification.
Privacy For Free: Wireless Federated Learning Via Uncoded Transmission With Adaptive Power Control
When FL is implemented in wireless systems via uncoded transmission, the channel noise can directly act as a privacy-inducing mechanism.
Information Theory Networking and Internet Architecture Signal Processing Information Theory
Wireless Data Acquisition for Edge Learning: Data-Importance Aware Retransmission
To solve the problem, a new retransmission protocol called data-importance aware automatic-repeat-request (importance ARQ) is proposed.
Towards an Intelligent Edge: Wireless Communication Meets Machine Learning
Accordingly, a new research area, called edge learning, emerges, which crosses and revolutionizes two disciplines: wireless communication and machine learning.
