2 papers
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…
quant-ph2026
Guaranteeing Privacy in Hybrid Quantum Learning through Theoretical Mechanisms
Hoang M. Ngo, Tre' R. Jeter, Incheol Shin +3
Quantum Machine Learning (QML) is becoming increasingly prevalent due to its potential to enhance classical machine learning (ML) tasks, such as classification. Although quantum no…