no code implementations • 11 May 2023 • Timothy Chu, Gary Miller, Noel Walkington
We provide theoretically-informed intuition about spectral clustering on large data sets drawn from probability densities, by proving when a continuous form of spectral clustering considered by past researchers (the unweighted spectral cut of a probability density) finds good clusters of the underlying density itself.