Ye Lin Tun

Orcid: 0000-0002-6955-1607

Affiliations:
  • Kyung Hee University, Yongin-si, Korea


According to our database1, Ye Lin Tun authored at least 14 papers between 2021 and 2024.

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

Timeline

Legend:

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PhD thesis 
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Links

Online presence:

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Bibliography

2024
Cross-Modal Prototype based Multimodal Federated Learning under Severely Missing Modality.
CoRR, 2024

OnDev-LCT: On-Device Lightweight Convolutional Transformers towards federated learning.
CoRR, 2024

LW-FedSSL: Resource-efficient Layer-wise Federated Self-supervised Learning.
CoRR, 2024

2023
Contrastive encoder pre-training-based clustered federated learning for heterogeneous data.
Neural Networks, August, 2023

Federated Learning with Diffusion Models for Privacy-Sensitive Vision Tasks.
CoRR, 2023

Training A Semantic Communication System with Federated Learning.
CoRR, 2023

Swin Transformer-Based Dynamic Semantic Communication for Multi-User with Different Computing Capacity.
CoRR, 2023

A Complete Survey on Generative AI (AIGC): Is ChatGPT from GPT-4 to GPT-5 All You Need?
CoRR, 2023

Transformers with Attentive Federated Aggregation for Time Series Stock Forecasting.
Proceedings of the International Conference on Information Networking, 2023

Federated Learning with Intermediate Representation Regularization.
Proceedings of the IEEE International Conference on Big Data and Smart Computing, 2023

2022
Federated Learning with Intermediate Representation Regularization.
CoRR, 2022

Clustering-Based Serverless Edge Computing Assisted Federated Learning for Energy Procurement.
Proceedings of the 23rd Asia-Pacific Network Operations and Management Symposium, 2022

2021
Federated Learning based Energy Demand Prediction with Clustered Aggregation.
Proceedings of the IEEE International Conference on Big Data and Smart Computing, 2021

Attention on Personalized Clinical Decision Support System: Federated Learning Approach.
Proceedings of the IEEE International Conference on Big Data and Smart Computing, 2021


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