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However, in our context, the functions of interest (resolvents) are analytic and bounded inC\Sϵ −0, which allows us to use Vitali’s theorem (cf

Justification of the Derivative Trick Almost sure convergence of a sequence of random functions{fp}to a deterministic functionfdoes not automatically imply the convergence of the

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Double Descent in Quantum Kernel Ridge Regression

quant-ph · 2026-04-19 · unverdicted · novelty 6.0

Quantum kernel ridge regression shows double descent in test risk, with the interpolation peak suppressible by regularization, via random matrix theory asymptotics in the high-dimensional limit.

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  • Double Descent in Quantum Kernel Ridge Regression quant-ph · 2026-04-19 · unverdicted · none · ref 67

    Quantum kernel ridge regression shows double descent in test risk, with the interpolation peak suppressible by regularization, via random matrix theory asymptotics in the high-dimensional limit.