4 papers
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…
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…
QUPID: A Partitioned Quantum Neural Network for Anomaly Detection in Smart Grid
Hoang M. Ngo, Tre' R. Jeter, Jung Taek Seo +1
Smart grid infrastructures have revolutionized energy distribution, but their day-to-day operations require robust anomaly detection methods to counter risks associated with cyber-…
FIDDLE: Reinforcement Learning for Quantum Fidelity Enhancement
Hoang M. Ngo, Tamer Kahveci, My T. Thai
Quantum computing has the potential to revolutionize fields like quantum optimization and quantum machine learning. However, current quantum devices are hindered by noise, reducing…