A Non-Parametric Bootstrap for Spectral Clustering

arXiv:2209.05812v2 Announce Type: replace-cross
Abstract: Finite mixture modelling is a popular method in the field of clustering and is beneficial largely due to its soft cluster membership probabilities. A common method for fitting finite mixture models is to employ spectral clustering, which can utilize the expectation-maximization (EM) algorithm. However, the EM algorithm falls victim to a number of issues, including convergence to sub-optimal solutions. We address this issue by developing two novel algorithms that incorporate the spectral decomposition of the …

abstract algorithm arxiv bootstrap cluster clustering cs.lg expectation-maximization however modelling non-parametric parametric popular stat.ml type