Vijaysherly V.

Quantum Kernel Concentration Under Class Imbalance: Empirical Characterisation with Discrimination Ratio and Quantum Imbalance Vulnerability Score

Quantum kernel methods are a candidate approach for machine learning on near-term quantum hardware, but two practical problems limit their deployment: kernel values concentrate exponentially as the qubit count grows, and real-world datasets are often severely class-imbalanced. We present the first systematic empirical...