Bounded Projection Matrix Approximation with Applications to Community Detection
Social and Information Networks
2023-08-16 v1 Machine Learning
Abstract
Community detection is an important problem in unsupervised learning. This paper proposes to solve a projection matrix approximation problem with an additional entrywise bounded constraint. Algorithmically, we introduce a new differentiable convex penalty and derive an alternating direction method of multipliers (ADMM) algorithm. Theoretically, we establish the convergence properties of the proposed algorithm. Numerical experiments demonstrate the superiority of our algorithm over its competitors, such as the semi-definite relaxation method and spectral clustering.
Cite
@article{arxiv.2305.15430,
title = {Bounded Projection Matrix Approximation with Applications to Community Detection},
author = {Zheng Zhai and Hengchao Chen and Qiang Sun},
journal= {arXiv preprint arXiv:2305.15430},
year = {2023}
}