$DC^2$: A Divide-and-conquer Algorithm for Large-scale Kernel Learning with Application to Clustering

no code implementations • 16 Nov 2019 • Ke Alexander Wang, Xinran Bian, Pan Liu, Donghui Yan

Analysis on $DC^2$ when applied to spectral clustering shows that the loss in clustering accuracy due to data division and reduction is upper bounded by the data approximation error which would vanish with recursive random projections.

Clustering