A spectral inverse theorem and a spectral regularity theorem show that leading eigenvectors of Fourier-denoised matrices recover quadratic Fourier structure, giving new algorithms for quadratic denoising and character decomposition.
Candela, Notes on compact nilspaces, Discrete Anal
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
citation-role summary
method 1
citation-polarity summary
fields
math.CO 1years
2025 1verdicts
CONDITIONAL 1roles
method 1polarities
use method 1representative citing papers
citing papers explorer
-
Spectral algorithms in higher-order Fourier analysis
A spectral inverse theorem and a spectral regularity theorem show that leading eigenvectors of Fourier-denoised matrices recover quadratic Fourier structure, giving new algorithms for quadratic denoising and character decomposition.