5 citations · 7 across the 8 of their papers we have counts for
8 papers
Lightweight Federated Learning over Wireless Edge Networks
Xiangwang Hou, Jingjing Wang, Jun Du +3
With the exponential growth of smart devices connected to wireless networks, data production is increasing rapidly, requiring machine learning (ML) techniques to unlock its value.…
Joint Optimization of Communication Enhancement and Location Privacy Protection in RIS-Assisted Underwater Communication System
Ziqi Chen, Jun Du, Chunxiao Jiang +1
As the demand for underwater communication continues to grow, underwater acoustic RIS (UARIS), as an emerging paradigm in underwater acoustic communication (UAC), can significantly…
Constrained Optimization with Compressed Gradients: A Dynamical Systems Perspective
Zhaoyue Xia, Jun Du, Chunxiao Jiang +2
Gradient compression is of growing interests for solving constrained optimization problems including compressed sensing, noisy recovery and matrix completion under limited communic…
On Inhomogeneous Infinite Products of Stochastic Matrices and Applications
Zhaoyue Xia, Jun Du, Chunxiao Jiang +3
With the growth of magnitude of multi-agent networks, distributed optimization holds considerable significance within complex systems. Convergence, a pivotal goal in this domain, i…
Gradient and Channel Aware Dynamic Scheduling for Over-the-Air Computation in Federated Edge Learning Systems
Jun Du, Bingqing Jiang, Chunxiao Jiang +2
To satisfy the expected plethora of computation-heavy applications, federated edge learning (FEEL) is a new paradigm featuring distributed learning to carry the capacities of low-l…
Convergence Theory of Generalized Distributed Subgradient Method with Random Quantization
Zhaoyue Xia, Jun Du, Yong Ren
The distributed subgradient method (DSG) is a widely discussed algorithm to cope with large-scale distributed optimization problems in the arising machine learning applications. Mo…