Empirical Evaluation of Quantum Kernel Methods for Classification: A Comparative Study with Classical Kernels

Paper recorded by Signals 4 on 2026-10-30 in cs.LG. Abstract reproduced from arXiv; link to the original below.

Published 2026-10-30 on arXiv · recorded by Signals 4 on 2026-11-02

Category: cs.LG · 机器学习 · first seen 2026-11-02

Abstract

Quantum kernel methods are the most concrete near-term proposal for quantum machine learning on classical data, yet published benchmarks disagree on whether they outperform tuned classical kernels, and the disagreement cannot be resolved from the literature because the comparisons are not protocol-controlled. We argue that the obstacle is one of measurement, not theory: the usual setup fixes the q

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