A classical error-rectification algorithm recovers heavy Fourier coefficients from noisy quantum Fourier sampling, enabling efficient noise-tolerant agnostic parity learning and its classical verification.
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Classical Verification of Quantum Learning Advantages with Noises
A classical error-rectification algorithm recovers heavy Fourier coefficients from noisy quantum Fourier sampling, enabling efficient noise-tolerant agnostic parity learning and its classical verification.