Preprint
Aug 2026
A Theory of Finite-Noise Optima and Generalization in Quantum Machine Learning
A statistical learning theory connecting microscopic noise processes to macroscopic learning performance is developed, derived from a surrogate model analysis, that predicts the noise-induced reduction in model complexity and the consequent reduction in the generalization gap.
Zi-Yu Zhang, Zikang Jia, Xiao-Song Li et al.
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