PAC-Bayes applied to low-sharpness flat minima yields non-vacuous generalization bounds for boolean functions whose Fourier spectra are sparse and low-degree, with parameters estimable by property testing.
half-layer
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.LG 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
A Sharper Picture of Generalization in Transformers
PAC-Bayes applied to low-sharpness flat minima yields non-vacuous generalization bounds for boolean functions whose Fourier spectra are sparse and low-degree, with parameters estimable by property testing.