This is the code for the Neurocomputing 2019 paper "Subspace clustering via structure-enforced dictionary learning" by Jinjoo Song, Gangjoon Yoon, Kwangsoo Hahn and Sang Min Yoon.
Our proposed method learns the reduced dimensional dictionary and coefficient matrices using the structural information as well as sparsity of data. Then, the affinity matrix is constructed from inner product of the learned dictionary coefficient vectors, which shows the correlation among data points.
The most important parameter, which denotes the number of the dicioanry atoms, is r.
The experiment results on three benchmark datasets are below. (mean±std)
The "SSPCA" code can be downloaded at http://rodolphejenatton.com/.