Songyang Zhang

IEEE Trans. Wirel. Commun., August, 2025

DiSC-Med: Diffusion-based Semantic Communications for Robust Medical Image Transmission.

[BibT_eX]

[DOI]

CoRR, August, 2025

Efficient Training of Large-Scale AI Models Through Federated Mixture-of-Experts: A System-Level Approach.

[BibT_eX]

[DOI]

CoRR, July, 2025

TiRE-GAN: Task-Incentivized Generative Learning for Radiomap Estimation.

[BibT_eX]

[DOI]

IEEE Wirel. Commun. Lett., May, 2025

TACO: Rethinking Semantic Communications with Task Adaptation and Context Embedding.

[BibT_eX]

[DOI]

CoRR, May, 2025

Task-Adaptive Semantic Communications with Controllable Diffusion-based Data Regeneration.

[BibT_eX]

[DOI]

CoRR, May, 2025

Physics-Inspired Distributed Radio Map Estimation.

[BibT_eX]

[DOI]

CoRR, February, 2025

Efficient Transmission of Radiomaps via Physics-Enhanced Semantic Communications.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Communications, 2025

Diff-GO<sup>n</sup>: Enhancing Diffusion Models for Goal-Oriented Communications.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Communications, 2025

Mixture-of-Experts for Distributed Edge Computing with Channel-Aware Gating Function.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Communications, 2025

Task-Driven Semantic Quantization and Imitation Learning for Goal-Oriented Communications.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Communications, 2025

DualGFL: Federated Learning with a Dual-Level Coalition-Auction Game.

[BibT_eX]

[DOI]

Proceedings of the AAAI-25, Sponsored by the Association for the Advancement of Artificial Intelligence, February 25, 2025

2024

RadioGAT: A Joint Model-Based and Data-Driven Framework for Multi-Band Radiomap Reconstruction via Graph Attention Networks.

[BibT_eX]

[DOI]

IEEE Trans. Wirel. Commun., November, 2024

Radiomap Inpainting for Restricted Areas Based on Propagation Priority and Depth Map.

[BibT_eX]

[DOI]

IEEE Trans. Wirel. Commun., August, 2024

Physics-Inspired Machine Learning for Radiomap Estimation: Integration of Radio Propagation Models and Artificial Intelligence.

[BibT_eX]

[DOI]

IEEE Commun. Mag., August, 2024

Signal Processing Over Multilayer Graphs: Theoretical Foundations and Practical Applications.

[BibT_eX]

[DOI]

IEEE Internet Things J., January, 2024

Efficient Eigen-Decomposition for Low-Rank Symmetric Matrices in Graph Signal Processing: An Incremental Approach.

[BibT_eX]

[DOI]

IEEE Trans. Signal Process., 2024

PS-FedGAN: An Efficient Federated Learning Framework With Strong Data Privacy.

[BibT_eX]

[DOI]

IEEE Internet Things J., 2024

LaMI-GO: Latent Mixture Integration for Goal-Oriented Communications Achieving High Spectrum Efficiency.

[BibT_eX]

[DOI]

CoRR, 2024

FedSC: Provable Federated Self-supervised Learning with Spectral Contrastive Objective over Non-i.i.d. Data.

[BibT_eX]

[DOI]

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Diff-GO: Diffusion Goal-Oriented Communications with Ultra-High Spectrum Efficiency.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Communications Workshops, 2024

UFed-GAN: Secure Federated Learning over Wireless Sensor Networks with Unlabeled Data.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Communications Workshops, 2024

Split-FL: An Efficient Online Federated Learning Framework with Constrained Computation and Streaming Data.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Communications Workshops, 2024

2023

RME-GAN: A Learning Framework for Radio Map Estimation Based on Conditional Generative Adversarial Network.

[BibT_eX]

[DOI]

IEEE Internet Things J., October, 2023

Diff-GO: Diffusion Goal-Oriented Communications to Achieve Ultra-High Spectrum Efficiency.

[BibT_eX]

[DOI]

CoRR, 2023

PFL-GAN: When Client Heterogeneity Meets Generative Models in Personalized Federated Learning.

[BibT_eX]

[DOI]

CoRR, 2023

UFed-GAN: A Secure Federated Learning Framework with Constrained Computation and Unlabeled Data.

[BibT_eX]

[DOI]

CoRR, 2023

PS-FedGAN: An Efficient Federated Learning Framework Based on Partially Shared Generative Adversarial Networks For Data Privacy.

[BibT_eX]

[DOI]

CoRR, 2023

2022

An Efficient Hypergraph Approach to Robust Point Cloud Resampling.

[BibT_eX]

[DOI]

IEEE Trans. Image Process., 2022

Multilayer graph spectral analysis for hyperspectral images.

[BibT_eX]

[DOI]

EURASIP J. Adv. Signal Process., 2022

Exemplar-Based Radio Map Reconstruction of Missing Areas Using Propagation Priority.

[BibT_eX]

[DOI]

Proceedings of the IEEE Global Communications Conference, 2022

2021

Hypergraph Spectral Analysis and Processing in 3D Point Cloud.

[BibT_eX]

[DOI]

IEEE Trans. Image Process., 2021

Point Cloud Resampling via Hypergraph Signal Processing.

[BibT_eX]

[DOI]

IEEE Signal Process. Lett., 2021

Hyperspectral Image Segmentation based on Graph Processing over Multilayer Networks.

[BibT_eX]

[DOI]

CoRR, 2021

2020

Hypergraph Spectral Clustering for Point Cloud Segmentation.

[BibT_eX]

[DOI]

IEEE Signal Process. Lett., 2020

Introducing Hypergraph Signal Processing: Theoretical Foundation and Practical Applications.

[BibT_eX]

[DOI]

IEEE Internet Things J., 2020

From Spectrum Wavelet to Vertex Propagation: Graph Convolutional Networks Based on Taylor Approximation.

[BibT_eX]

[DOI]

CoRR, 2020

Point Cloud Segmentation based on Hypergraph Spectral Clustering.

[BibT_eX]

[DOI]

Proceedings of the Information Theory and Applications Workshop, 2020

Hypergraph-Based Image Processing.

[BibT_eX]

[DOI]