Unverified50% confidenceFactExact time
Leave-one-out quadratic thresholding locates the signal support in the doubly sparse parameter space by constructing a threshold search based on quadratic statistics, and is more robust to the sparse structure of the noise than purely spectral methods.
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10/19/2026
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Related Claims
UnverifiedThe experiment used a pre-specified two-percentage-point margin for the coverage determination as the criterion for "substantial difference", in order to avoid treating Monte Carlo noise as a conclusion.75% similarUnverifiedWhen interpreting benchmarks that use binary thresholds, one should distinguish between the two signals of threshold pass rate and dimension scores, to avoid misreading threshold luck as a capability gap.74% similarUnverifiedThe first method works best when the intrinsic dimension of the data can be reliably estimated; its robustness is limited by the stability of the intrinsic dimension estimate and may be unstable in high-noise or extremely sparse regions.71% similarUnverifiedThe paper extends the analysis to sub-Gaussian spike priors through two approaches, diagonal thresholding and quadratic thresholding, showing that the basic mechanism of support identification still holds under more general spike distributions.70% similarUnverifiedIf the potential satisfies quadratic coercivity conditions, then every weak accumulation point is a stationary point, and this analysis holds for any initial measure with finite second moment.70% similar
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