Paper ID: 2411.18794

Graph Max Shift: A Hill-Climbing Method for Graph Clustering

Ery Arias-Castro, Elizabeth Coda, Wanli Qiao

We present a method for graph clustering that is analogous with gradient ascent methods previously proposed for clustering points in space. We show that, when applied to a random geometric graph with data iid from some density with Morse regularity, the method is asymptotically consistent. Here, consistency is understood with respect to a density-level clustering defined by the partition of the support of the density induced by the basins of attraction of the density modes.

Submitted: Nov 27, 2024