Dongzhu Liu

Orcid: 0000-0001-7820-9531

According to our database1, Dongzhu Liu authored at least 21 papers between 2017 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
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Other 

Links

On csauthors.net:

Bibliography

2024
Joint Compression and Deadline Optimization for Wireless Federated Learning.
IEEE Trans. Mob. Comput., July, 2024

Low-Rank Gradient Compression with Error Feedback for MIMO Wireless Federated Learning.
CoRR, 2024

2023
Wireless Federated Langevin Monte Carlo: Repurposing Channel Noise for Bayesian Sampling and Privacy.
IEEE Trans. Wirel. Commun., May, 2023

Task-Oriented Integrated Sensing, Computation and Communication for Wireless Edge AI.
IEEE Netw., 2023

Joint Compression and Deadline Optimization for Wireless Federated Learning.
CoRR, 2023

Over-the-Air Federated Edge Learning with Error-Feedback One-Bit Quantization and Power Control.
CoRR, 2023

Bayesian Over-the-Air FedAvg via Channel Driven Stochastic Gradient Langevin Dynamics.
Proceedings of the IEEE Global Communications Conference, 2023

Joint Compression and Deadline Optimization for Communication-Efficient Federated Edge Learning.
Proceedings of the IEEE Globecom Workshops 2023, 2023

2022
Channel-Driven Monte Carlo Sampling for Bayesian Distributed Learning in Wireless Data Centers.
IEEE J. Sel. Areas Commun., 2022

Leveraging Channel Noise for Sampling and Privacy via Quantized Federated Langevin Monte Carlo.
Proceedings of the 23rd IEEE International Workshop on Signal Processing Advances in Wireless Communication, 2022

2021
Wireless Data Acquisition for Edge Learning: Data-Importance Aware Retransmission.
IEEE Trans. Wirel. Commun., 2021

Data-Importance Aware User Scheduling for Communication-Efficient Edge Machine Learning.
IEEE Trans. Cogn. Commun. Netw., 2021

Privacy for Free: Wireless Federated Learning via Uncoded Transmission With Adaptive Power Control.
IEEE J. Sel. Areas Commun., 2021

2020
Toward an Intelligent Edge: Wireless Communication Meets Machine Learning.
IEEE Commun. Mag., 2020

Exploiting Diversity Via Importance-Aware User Scheduling for Fast Edge Learning.
Proceedings of the 2020 IEEE International Conference on Communications Workshops, 2020

2019
Wireless Data Acquisition for Edge Learning: Importance-Aware Retransmission.
Proceedings of the 20th IEEE International Workshop on Signal Processing Advances in Wireless Communications, 2019

2018
Mitigating Interference in Content Delivery Networks by Spatial Signal Alignment: The Approach of Shot-Noise Ratio.
IEEE Trans. Wirel. Commun., 2018

Towards an Intelligent Edge: Wireless Communication Meets Machine Learning.
CoRR, 2018

Communication, Computing, and Learning on the Edge.
Proceedings of the IEEE International Conference on Communication Systems, 2018

2017
Spatial Alignment of Coding and Modulation Helps Content Delivery.
CoRR, 2017

Harnessing Interference in Content Delivery by Spatial Signal Alignment.
Proceedings of the 2017 IEEE Global Communications Conference, 2017


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