Author

Ming Ding

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#federated learning Nov 2026

Toward Fair Federated Edge Learning Through Prototype-Guided Distributed Adversarial Networks

Federated learning (FL) is a privacy-preserving machine learning (ML) paradigm that can learn models from distributed datasets owned by mobile terminals (MTs). However, ML models usually contain bias on some user groups/sensitive attributes (e.g., gender and race), which poses additional challenges on FL in real-world...

Kang Wei, Xin-Nan Yuan, Zi-Cong Hong et al. · IEEE Transactions on Mobile... · 0 citations

Jul 2026

Convergence-Latency-Aware Adaptive Modulation and Resource Allocation in RIS-Assisted Wireless Federated Learning

A wireless FL system operating under RIS-assisted blocked-link propagation scenarios is considered, and a joint convergence-latency optimization problem is cast as a mixed-integer nonlinear programming (MINLP) problem, and solved using a low-complexity hybrid alternating optimization framework.

Liwei Wang, Wen Chen, Jun Li et al. · arXiv.org · 0 citations