14 citations · 32 across the 14 of their papers we have counts for
4 papers · 1 filter
Efficient Quantum One-Class Support Vector Machines for Anomaly Detection Using Randomized Measurements and Variable Subsampling
Michael Kölle, Afrae Ahouzi, Pascal Debus +4
Quantum one-class support vector machines leverage the advantage of quantum kernel methods for semi-supervised anomaly detection. However, their quadratic time complexity with resp…
QUACK: Quantum Aligned Centroid Kernel
Kilian Tscharke, Sebastian Issel, Pascal Debus
Quantum computing (QC) seems to show potential for application in machine learning (ML). In particular quantum kernel methods (QKM) exhibit promising properties for use in supervis…
A Comparative Analysis of Adversarial Robustness for Quantum and Classical Machine Learning Models
Maximilian Wendlinger, Kilian Tscharke, Pascal Debus
Quantum machine learning (QML) continues to be an area of tremendous interest from research and industry. While QML models have been shown to be vulnerable to adversarial attacks m…
Towards Classical Software Verification using Quantum Computers
Sebastian Issel, Kilian Tscharke, Pascal Debus
We explore the possibility of accelerating the formal verification of classical programs with a quantum computer. A common source of security flaws stems from the existence of comm…