Zikang Jia

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.