3 papers
stat.ML2025
Central limit theorems for the eigenvalues of graph Laplacians on data clouds
Chenghui Li, Nicolás García Trillos, Housen Li +1
Given i.i.d.\ samples from a distribution supported on a low dimensional manifold embedded in Eucliden space, we consider the graph Laplacian ope…
math.ST2024
Distributional limits of graph cuts on discretized grids
Leo Suchan, Housen Li, Axel Munk
Graph cuts are among the most prominent tools for clustering and classification analysis. While intensively studied from geometric and algorithmic perspectives, graph cut-based sta…
cs.DS2023
A scalable clustering algorithm to approximate graph cuts
Leo Suchan, Housen Li, Axel Munk
Due to their computational complexity, graph cuts for cluster detection and identification are used mostly in the form of convex relaxations. We propose to utilize the original gra…