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Dongzhu Liu
Dongzhu Liu
Lecturer (Assistant Professor), University of Glasgow
Verified email at glasgow.ac.uk - Homepage
Title
Cited by
Cited by
Year
Toward an intelligent edge: Wireless communication meets machine learning
G Zhu, D Liu, Y Du, C You, J Zhang, K Huang
IEEE communications magazine 58 (1), 19-25, 2020
5502020
Privacy for free: Wireless federated learning via uncoded transmission with adaptive power control
D Liu, O Simeone
IEEE Journal on Selected Areas in Communications 39 (1), 170-185, 2020
1712020
Data-importance aware user scheduling for communication-efficient edge machine learning
D Liu, G Zhu, J Zhang, K Huang
IEEE Transactions on Cognitive Communications and Networking 7 (1), 265-278, 2020
642020
Wireless data acquisition for edge learning: Data-importance aware retransmission
D Liu, G Zhu, Q Zeng, J Zhang, K Huang
IEEE transactions on wireless communications 20 (1), 406-420, 2020
482020
Wireless Data Acquisition for Edge Learning: Importance-Aware Retransmission
D Liu, G Zhu, J Zhang, K Huang
2019 IEEE 20th International Workshop on Signal Processing Advances in …, 2019
222019
Wireless federated langevin monte carlo: Repurposing channel noise for bayesian sampling and privacy
D Liu, O Simeone
IEEE Transactions on Wireless Communications, 2022
162022
Channel-driven monte carlo sampling for bayesian distributed learning in wireless data centers
D Liu, O Simeone
IEEE Journal on Selected Areas in Communications 40 (2), 562-577, 2021
92021
Communication, computing, and learning on the edge
K Huang, G Zhu, C You, J Zhang, Y Du, D Liu
2018 IEEE International Conference on Communication Systems (ICCS), 268-273, 2018
82018
Mitigating interference in content delivery networks by spatial signal alignment: The approach of shot-noise ratio
D Liu, K Huang
IEEE Transactions on Wireless Communications 17 (4), 2305-2318, 2018
5*2018
Leveraging channel noise for sampling and privacy via quantized federated langevin monte carlo
Y Zhang, D Liu, O Simeone
2022 IEEE 23rd International Workshop on Signal Processing Advances in …, 2022
42022
Over-the-air federated edge learning with error-feedback one-bit quantization and power control
Y Liu, D Liu, G Zhu, Q Shi, C Zhong
arXiv preprint arXiv:2303.11319, 2023
22023
Task-oriented integrated sensing, computation and communication for wireless edge AI
H Xing, G Zhu, D Liu, H Wen, K Huang, K Wu
IEEE Network 37 (4), 135-144, 2023
12023
Exploiting Diversity Via Importance-Aware User Scheduling for Fast Edge Learning
D Liu, G Zhu, J Zhang, K Huang
2020 IEEE International Conference on Communications Workshops (ICC …, 2020
12020
Low-Rank Gradient Compression with Error Feedback for MIMO Wireless Federated Learning
M Guo, D Liu, O Simeone, D Wen
arXiv preprint arXiv:2401.07496, 2024
2024
Joint Compression and Deadline Optimization for Wireless Federated Learning
M Zhang, Y Li, D Liu, R Jin, G Zhu, C Zhong, TQS Quek
IEEE Transactions on Mobile Computing, 2023
2023
Bayesian Over-the-Air FedAvg via Channel Driven Stochastic Gradient Langevin Dynamics
B Zhang, D Liu, O Simeone, G Zhu
GLOBECOM 2023-2023 IEEE Global Communications Conference, 5286-5291, 2023
2023
Differentially Private Wireless Federated Learning: from Part II-Wireless Networks for Machine Learning
D Liu, A Sonee, O Simeone, S Rini
Machine Learning and Wireless Communications, 2022
2022
Harnessing Interference in Content Delivery by Spatial Signal Alignment
D Liu, K Huang
GLOBECOM 2017-2017 IEEE Global Communications Conference, 1-6, 2017
2017
17 Differentially Private Wireless Federated Learning
D Liu, A Sonee, O Simeone, S Rini
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Articles 1–19