Lun Wang

Orcid: 0000-0002-9436-7924

Affiliations:
  • University of Science and Technology of China, Suzhou, Jiangsu, China


According to our database1, Lun Wang authored at least 20 papers between 2022 and 2026.

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

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

Online presence:

On csauthors.net:

Bibliography

2026
Accelerating Decentralized Federated Learning With Probabilistic Communication in Heterogeneous Edge Computing.
IEEE Trans. Netw., 2026

2025
PairingFL: Efficient Federated Learning With Model Splitting and Client Pairing.
IEEE Trans. Netw., 2025

FedSNN: Training Slimmable Neural Network With Federated Learning in Edge Computing.
IEEE Trans. Netw., 2025

2024
Overcoming Noisy Labels and Non-IID Data in Edge Federated Learning.
IEEE Trans. Mob. Comput., December, 2024

Asynchronous Decentralized Federated Learning for Heterogeneous Devices.
IEEE/ACM Trans. Netw., October, 2024

Ferrari: A Personalized Federated Learning Framework for Heterogeneous Edge Clients.
IEEE Trans. Mob. Comput., October, 2024

Decentralized Federated Learning With Adaptive Configuration for Heterogeneous Participants.
IEEE Trans. Mob. Comput., June, 2024

BOSE: Block-Wise Federated Learning in Heterogeneous Edge Computing.
IEEE/ACM Trans. Netw., April, 2024

Enhancing Federated Learning With Server-Side Unlabeled Data by Adaptive Client and Data Selection.
IEEE Trans. Mob. Comput., April, 2024

Accelerating Federated Learning With Data and Model Parallelism in Edge Computing.
IEEE/ACM Trans. Netw., February, 2024

Towards Communication-Efficient Federated Graph Learning: An Adaptive Client Selection Perspective.
Proceedings of the 32nd IEEE/ACM International Symposium on Quality of Service, 2024

MergeSFL: Split Federated Learning with Feature Merging and Batch Size Regulation.
Proceedings of the 40th IEEE International Conference on Data Engineering, 2024

Federated Semi-Supervised Learning with Local and Global Updating Frequency Optimization.
Proceedings of the 24th IEEE International Symposium on Cluster, 2024

2023
Joint Model Pruning and Topology Construction for Accelerating Decentralized Machine Learning.
IEEE Trans. Parallel Distributed Syst., October, 2023

Adaptive Control of Local Updating and Model Compression for Efficient Federated Learning.
IEEE Trans. Mob. Comput., October, 2023

Accelerating Decentralized Federated Learning in Heterogeneous Edge Computing.
IEEE Trans. Mob. Comput., September, 2023

Adaptive Asynchronous Federated Learning in Resource-Constrained Edge Computing.
IEEE Trans. Mob. Comput., 2023

Adaptive Configuration for Heterogeneous Participants in Decentralized Federated Learning.
Proceedings of the IEEE INFOCOM 2023, 2023

2022
Decentralized Machine Learning Through Experience-Driven Method in Edge Networks.
IEEE J. Sel. Areas Commun., 2022

Enhancing Federated Learning with In-Cloud Unlabeled Data.
Proceedings of the 38th IEEE International Conference on Data Engineering, 2022


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