Author

T. Vu

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#machine learning Preprint Sep 2026

Proportional-Fair Resource Allocation and Dual-Threshold Early-Exit Inference for Secure Cooperative Multi-Layer Edge Intelligence

Numerical results with early-exit MobileNetV2 and ShuffleNetV2 demonstrate near-perfect UE fairness with aggregate utility close to a Sum-Utility benchmark, reveal security-induced resource fragmentation, and demonstrate the Stage-A scalability from 6 to 144 UEs with median solving time below 0.1~s.

T. Vu, John Le, Tu N. Nguyen et al. · 0 citations

Conference Jul 2026

Learning Depth-Structured Parameterizations for Efficient Optimisation of Deep Quantum Circuits

Parametrized quantum circuits (PQCs) form the computational backbone of variational quantum algorithms, yet their practical utility is increasingly constrained by optimisation failures as circuit depth grows. Gradient signals decay rapidly under standard random initialisation, and existing structured approaches abandon...

Thi Thuy Nga Nguyen, John Le, T. Vu et al. · 2026 IEEE International Conf... · 0 citations