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cs.LG2026
Q-ShiftDP: A Differentially Private Parameter-Shift Rule for Quantum Machine Learning
Hoang M. Ngo, Nhat Hoang-Xuan, Quan Nguyen +3
Quantum Machine Learning (QML) promises significant computational advantages, but preserving training data privacy remains challenging. Classical approaches like differentially pri…
cs.LG2025
Hephaestus: Mixture Generative Modeling with Energy Guidance for Large-scale QoS Degradation
Nguyen Do, Bach Ngo, Youval Kashuv +3
We study the Quality of Service Degradation (QoSD) problem, in which an adversary perturbs edge weights to degrade network performance. This setting arises in both network infrastr…