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Shu-Juan Tian

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Sep 2026

ZMASA: Robust Aggregation for Federated Learning Against Byzantine Attacks.

Federated learning (FL) enables collaborative model training without sharing raw data, but its robustness is vulnerable to Byzantine clients, especially under non-identically distributed (non-IID) data. In heterogeneous FL, benign client updates may become multimodal and statistically diverse, making it difficult for m...

Shu-Juan Tian, Shu-Huan Xiang, Gang Liu et al. · 0 citations
#edge computing Sep 2026

Utility-Aware Resource Allocation for Hybrid NOMA in MEC: A Matching-Coalition Game Approach

The massive influx of uplink task offloading in Multi-access Edge Computing (MEC) systems poses a significant challenge to the capacity of wireless networks. This challenge highlights a fundamental trade-off between Orthogonal Multiple Access (OMA), which provides interference-free but spectrally inefficient communicat...

Haolin Liu, Hao Yin, Haibo Zhou et al. · 0 citations

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