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A Framework for Computational Lower Bounds in Nontrivial Norm Approximation

math.ST · 2026-04-01 · unverdicted · novelty 7.0

A framework using reverse detection-estimation gaps proves that low-degree algorithms incur at least p^{d/4-1/2}/polylog(p) distortion when approximating the spectral norm of order-d symmetric tensors, matching upper bounds up to logs under the low-degree conjecture.

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