Deep Multiple Auto-Encoder-Based Multi-view Clustering

• Published in: Data Science and Engineering Vol. 6; no. 3; pp. 323 - 338
• Main Authors: Du, Guowang, Zhou, Lihua, Yang, Yudi, Lü, Kevin, Wang, Lizhen
• Format: Journal Article
• Language: English
• Published: Singapore Springer Singapore 01.09.2021; Springer; Springer Nature B.V
• Subjects: Algorithm Analysis and Problem Complexity; Algorithms; Analysis; Artificial Intelligence; Chemistry and Earth Sciences; Clustering; Coders; Computer Science; Data Mining and Knowledge Discovery; Database Management; Physics; Representations; Statistics for Engineering; Systems and Data Security; Multi-view Clustering; Local geometrical information; Auto-encoder; Consistent information; Complementary information

Multi-view clustering (MVC), which aims to explore the underlying structure of data by leveraging heterogeneous information of different views, has brought along a growth of attention. Multi-view clustering algorithms based on different theories have been proposed and extended in various application...