9 citations · 14 across the 6 of their papers we have counts for
7 papers
Beyond Task Relevance: Interaction-Aware Semantic Communication for Wireless Agent Collaboration
Yiru Wang, Pengxin Guan, Xiumei Deng +1
Semantic communication in multi-agent systems often assumes that task-relevant information benefits the team once delivered. Yet semantic sharing can alter the receiver's decision…
Trustworthy DNN Partition for Blockchain-enabled Digital Twin in Wireless IIoT Networks
Xiumei Deng, Jun Li, Long Shi +5
Digital twin (DT) has emerged as a promising solution to enhance manufacturing efficiency in industrial Internet of Things (IIoT) networks. To promote the efficiency and trustworth…
Towards Communication-efficient Federated Learning via Sparse and Aligned Adaptive Optimization
Xiumei Deng, Jun Li, Kang Wei +6
Adaptive moment estimation (Adam), as a Stochastic Gradient Descent (SGD) variant, has gained widespread popularity in federated learning (FL) due to its fast convergence. However,…
Energy-Efficient Wireless Federated Learning via Doubly Adaptive Quantization
Xuefeng Han, Wen Chen, Jun Li +5
Federated learning (FL) has been recognized as a viable distributed learning paradigm for training a machine learning model across distributed clients without uploading raw data. H…
Mobility-Aware Joint User Scheduling and Resource Allocation for Low Latency Federated Learning
Kecheng Fan, Wen Chen, Jun Li +3
As an efficient distributed machine learning approach, Federated learning (FL) can obtain a shared model by iterative local model training at the user side and global model aggrega…
Low-latency Federated Learning with DNN Partition in Distributed Industrial IoT Networks
Xiumei Deng, Jun Li, Chuan Ma +4
Federated Learning (FL) empowers Industrial Internet of Things (IIoT) with distributed intelligence of industrial automation thanks to its capability of distributed machine learnin…
Blockchain Assisted Federated Learning over Wireless Channels: Dynamic Resource Allocation and Client Scheduling
Xiumei Deng, Jun Li, Chuan Ma +5
The blockchain technology has been extensively studied to enable distributed and tamper-proof data processing in federated learning (FL). Most existing blockchain assisted FL (BFL)…