9 citations · 18 across the 9 of their papers we have counts for
9 papers
Convergence-Latency-Aware Adaptive Modulation and Resource Allocation in RIS-Assisted Wireless Federated Learning
Liwei Wang, Wen Chen, Jun Li +4
Federated learning (FL) over wireless networks suffers from significant training latency and degraded convergence due to unreliable wireless transmission, especially under blocked…
Hierarchical Federated Learning for Social Network with Mobility
Zeyu Chen, Wen Chen, Jun Li +5
Federated Learning (FL) offers a decentralized solution that allows collaborative local model training and global aggregation, thereby protecting data privacy. In conventional FL f…
Analysis and Optimization of Wireless Multimodal Federated Learning on Modal Heterogeneity
Xuefeng Han, Wen Chen, Jun Li +6
Multimodal federated learning (MFL) is a distributed framework for training multimodal models without uploading local multimodal data of clients, thereby effectively protecting cli…
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…
Robust Model Aggregation for Heterogeneous Federated Learning: Analysis and Optimizations
Yumeng Shao, Jun Li, Long Shi +6
Conventional synchronous federated learning (SFL) frameworks suffer from performance degradation in heterogeneous systems due to imbalanced local data size and diverse computing po…
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,…
Industrial Metaverse: Enabling Technologies, Open Problems, and Future Trends
Shiying Zhang, Jun Li, Long Shi +4
As an emerging technology that enables seamless integration between the physical and virtual worlds, the Metaverse has great potential to be deployed in the industrial production f…
Communication-Efficient Model Aggregation with Layer Divergence Feedback in Federated Learning
Liwei Wang, Jun Li, Wen Chen +2
Federated Learning (FL) facilitates collaborative machine learning by training models on local datasets, and subsequently aggregating these local models at a central server. Howeve…
Private Knowledge Sharing in Distributed Learning: A Survey
Yasas Supeksala, Dinh C. Nguyen, Ming Ding +5
The rise of Artificial Intelligence (AI) has revolutionized numerous industries and transformed the way society operates. Its widespread use has led to the distribution of AI and i…