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06/11/2023
Task-Oriented Integrated Sensing, Computation and Communication for Wireless Edge AI
With the advent of emerging IoT applications such as autonomous driving,...
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05/07/2023
Bayesian Over-the-Air FedAvg via Channel Driven Stochastic Gradient Langevin Dynamics
The recent development of scalable Bayesian inference methods has renewe...
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03/20/2023
Over-the-Air Federated Edge Learning with Error-Feedback One-Bit Quantization and Power Control
Over-the-air federated edge learning (Air-FEEL) is a communication-effic...
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02/28/2022
Leveraging Channel Noise for Sampling and Privacy via Quantized Federated Langevin Monte Carlo
For engineering applications of artificial intelligence, Bayesian learni...
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08/17/2021
Wireless Federated Langevin Monte Carlo: Repurposing Channel Noise for Bayesian Sampling and Privacy
Most works on federated learning (FL) focus on the most common frequenti...
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03/01/2021
Channel-Driven Monte Carlo Sampling for Bayesian Distributed Learning in Wireless Data Centers
Conventional frequentist learning, as assumed by existing federated lear...
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06/09/2020
Privacy For Free: Wireless Federated Learning Via Uncoded Transmission With Adaptive Power Control
Federated Learning (FL) refers to distributed protocols that avoid direc...
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10/05/2019
Data-Importance Aware User Scheduling for Communication-Efficient Edge Machine Learning
With the prevalence of intelligent mobile applications, edge learning is...
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12/05/2018
Wireless Data Acquisition for Edge Learning: Importance Aware Retransmission
By deploying machine learning algorithms at the network edge, edge learn...
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09/02/2018