Yuchang Sun

Orcid: 0000-0001-7881-4723

Affiliations:
  • Hong Kong University of Science and Technology


According to our database1, Yuchang Sun authored at least 16 papers between 2021 and 2024.

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

2024
Feature Matching Data Synthesis for Non-IID Federated Learning.
IEEE Trans. Mob. Comput., October, 2024

Channel and Gradient-Importance Aware Device Scheduling for Over-the-Air Federated Learning.
IEEE Trans. Wirel. Commun., July, 2024

MimiC: Combating Client Dropouts in Federated Learning by Mimicking Central Updates.
IEEE Trans. Mob. Comput., July, 2024

Stochastic Coded Federated Learning: Theoretical Analysis and Incentive Mechanism Design.
IEEE Trans. Wirel. Commun., June, 2024

Exploring Selective Layer Fine-Tuning in Federated Learning.
CoRR, 2024

Dual-Delayed Asynchronous SGD for Arbitrarily Heterogeneous Data.
CoRR, 2024

How to Collaborate: Towards Maximizing the Generalization Performance in Cross-Silo Federated Learning.
CoRR, 2024

2023
Semi-Decentralized Federated Edge Learning With Data and Device Heterogeneity.
IEEE Trans. Netw. Serv. Manag., June, 2023

A Survey of What to Share in Federated Learning: Perspectives on Model Utility, Privacy Leakage, and Communication Efficiency.
CoRR, 2023

DABS: Data-Agnostic Backdoor attack at the Server in Federated Learning.
CoRR, 2023

Probabilistic Device Scheduling for Over-the-Air Federated Learning.
Proceedings of the 23rd IEEE International Conference on Communication Technology, 2023

2022
Semi-Decentralized Federated Edge Learning for Fast Convergence on Non-IID Data.
Proceedings of the IEEE Wireless Communications and Networking Conference, 2022

DReS-FL: Dropout-Resilient Secure Federated Learning for Non-IID Clients via Secret Data Sharing.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Stochastic Coded Federated Learning with Convergence and Privacy Guarantees.
Proceedings of the IEEE International Symposium on Information Theory, 2022

Asynchronous Semi-Decentralized Federated Edge Learning for Heterogeneous Clients.
Proceedings of the IEEE International Conference on Communications, 2022

2021
Semi-Decentralized Federated Edge Learning for Fast Convergence on Non-IID Data.
CoRR, 2021


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