This paper proposes a global and local structure preserving nonnegative subspace clustering method, which learns data similarities and cluster indicators in a ...

To overcome these problems, this paper proposes a global and local structure preserving nonnegative subspace clustering method, which learns data similarities ...

To overcome these problems, this paper proposes a global and local structure preserving nonnegative subspace clustering method, which learns data similarities ...

The existing subspace clustering methods can be divided into five categories: iterative models [10]; statistical models [11]; algebraic models [12]; spectral ...

Global and local structure preserving nonnegative subspace clustering ... Authors: Hongjie Jia; Dongxia Zhu; Longxia Huang; Qirong Mao; Liangjun Wang; Heping Song ...

In this paper, we propose a global and local structure preserving sparse subspace learning (GLoSS) model for unsupervised feature selection. The model can ...

Oct 25, 2022 · Spectral Clustering (SC) is widely used for clustering data on a nonlinear manifold. SC aims to cluster data by considering the preservation ...

Local structure preserving has been widely adopted to learn subspace which reflects the intrinsic attributes of samples. In this chapter, inspired by the idea ...

Hence, GLRR can capture both the global structure (due to the LRR framework) and local structure (due to the graph regularization) of the data. It is easy to ...

The main contributions of this paper are: (1) By learning the global and local structural relationships on the latent representation, the within-class and ...