Mengyuan Lee

According to our database1, Mengyuan Lee authored at least 16 papers between 2018 and 2022.

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



In proceedings 
PhD thesis 




A Graph Neural Network Based Decentralized Learning Scheme.
Sensors, 2022

Multicell Power Control Under QoS Requirements With CNet.
IEEE Commun. Lett., 2022

Privacy-Preserving Decentralized Inference with Graph Neural Networks in Wireless Networks.
CoRR, 2022

Learning to Optimize Resource in Dynamic Wireless Environment via Meta-Gating Graph Neural Network.
Proceedings of the 18th International Symposium on Wireless Communication Systems, 2022

Design of Retransmission Mechanism for Decentralized Inference with Graph Neural Networks.
Proceedings of the 27th Asia Pacific Conference on Communications, 2022

Graph Embedding-Based Wireless Link Scheduling With Few Training Samples.
IEEE Trans. Wirel. Commun., 2021

Accelerating Generalized Benders Decomposition for Wireless Resource Allocation.
IEEE Trans. Wirel. Commun., 2021

Decentralized Inference with Graph Neural Networks in Wireless Communication Systems.
CoRR, 2021

Device Sampling for Heterogeneous Federated Learning: Theory, Algorithms, and Implementation.
Proceedings of the 40th IEEE Conference on Computer Communications, 2021

Learning to Branch: Accelerating Resource Allocation in Wireless Networks.
IEEE Trans. Veh. Technol., 2020

User Association for Millimeter-Wave Networks: A Machine Learning Approach.
IEEE Trans. Commun., 2020

A Fast Graph Neural Network-Based Method for Winner Determination in Multi-Unit Combinatorial Auctions.
CoRR, 2020

Wireless D2D Network Link Scheduling based on Graph Embedding.
Proceedings of the 92nd IEEE Vehicular Technology Conference, 2020

Wireless Link Scheduling for D2D Communications with Graph Embedding Technique.
Proceedings of the 2020 IEEE International Conference on Communications, 2020

Accelerating Resource Allocation for D2D Communications Using Imitation Learning.
Proceedings of the 90th IEEE Vehicular Technology Conference, 2019

Deep Neural Networks for Linear Sum Assignment Problems.
IEEE Wirel. Commun. Lett., 2018