Leiming Chen

Orcid: 0000-0002-7701-6313

According to our database1, Leiming Chen authored at least 13 papers between 2017 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
FedMTL: Adaptive multi-teacher knowledge distillation for federated continual learning.
Knowl. Based Syst., 2026

FedUnit: A Robust and Fair Federated Learning Framework for Malicious Client Detection and Free-Rider Contribution Evaluation.
Appl. Soft Comput., 2026

Cost-efficient Archive Cloud Storage with Tape: Design and Deployment.
Proceedings of the 24th USENIX Conference on File and Storage Technologies, 2026

2025
A Credible and Fair Federated Learning Framework Based on Blockchain.
IEEE Trans. Artif. Intell., February, 2025

FedCGAT: A federated demand prediction method for shared bicycles based on contrastive graph attention mechanism.
J. Intell. Fuzzy Syst., 2025

2024
Dynamic Circular Network-Based Federated Dual-View Learning for Multivariate Time Series Anomaly Detection.
Bus. Inf. Syst. Eng., February, 2024

FedTKD: A Trustworthy Heterogeneous Federated Learning Based on Adaptive Knowledge Distillation.
Entropy, January, 2024

FedDRL: Trustworthy Federated Learning Model Fusion Method Based on Staged Reinforcement Learning.
Comput. Informatics, 2024

2023
Feature-Contrastive Graph Federated Learning: Responsible AI in Graph Information Analysis.
IEEE Trans. Comput. Soc. Syst., December, 2023

Semi-asynchronous personalized federated learning for short-term photovoltaic power forecasting.
Digit. Commun. Networks, October, 2023

FedDRL: A Trustworthy Federated Learning Model Fusion Method Based on Staged Reinforcement Learning.
CoRR, 2023

2021
A Federated Parallel Data Platform for Trustworthy AI.
Proceedings of the IEEE 2nd International Conference on Digital Twins and Parallel Intelligence, 2021

2017
Emotion Recognition from Chinese Speech for Smart Affective Services Using a Combination of SVM and DBN.
Sensors, 2017


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