On Matrix Factorizations in Subspace Clustering

Code

• github.com/reeshadarian/RCUR
  OfficialIn papernone★ 0

Abstract

This article explores subspace clustering algorithms using CUR decompositions, and examines the effect of various hyperparameters in these algorithms on clustering performance on two real-world benchmark datasets, the Hopkins155 motion segmentation dataset and the Yale face dataset. Extensive experiments are done for a variety of sampling methods and oversampling parameters for these datasets, and some guidelines for parameter choices are given for practical applications.

Tasks

Reproductions