记笔记

Subspace Clustering by Integrating Sparseness and Spatial-Closeness Priors

Zhe Li¹Haodong Pei^2,3Liang He¹Jiaming Liu¹Jiaxin Hu¹Dongji Wang^4,5

1. Futian Power Supply Bureau, Shenzhen Power Supply Bureau Co., Ltd 2. Key Laboratory of Intelligent Infrared Perception, Chinese Academy of Sciences 3. Shanghai Institute of Technical Physics of the Chinese Academy of Sciences 4. National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences 5. School of Artificial Intelligence, University of Chinese Academy of Sciences

摘要：How to construct an effective sample affinity matrix is an important problem for subspace clustering, and most existing subspace clustering algorithms pursue the affinity matrix in a single space. In this paper, we propose a novel computational framework for subspace clustering, called Complementary Subspace Clustering（CSC） at first, where the affinity matrix is constructed in a pair of complementary spaces which provide different and complementary constraints on the affinity matrix. Many existing structural priors on self representation and dimensionality reduction can be seamlessly integrated into the CSC framework. Then under this framework, we explore a simple and effective subspace clustering algorithm by respectively introducing two basic priors-sparse representation and spatial closeness-into the referred pair of spaces. Moreover, a kernel variant of the proposed clustering algorithm is present. Extensive experimental results demonstrate that although only basic priors are involved, the explored algorithms from the CSC framework can improve the clustering performances significantly when the number of the sample classes is relatively big.

基金：

supported by the technology project of Shenzhen Power Supply Bureau Co., Ltd （No.0909002019030103FTPW00064）； the Open Research Fund from Key Laboratory of Intelligent Infrared Perception, Chinese Academy of Sciences；

会议名称：

The 2nd International Conference on Artificial Intelligence and Computer Science （AICS 2020）

会议时间：

2020-07-25

会议地点：

中国湖北武汉