Deep multiview clustering via iteratively self-supervised universal and specific space learning

• Main Authors: ZHANG, Yue, HUANG, Qinjian, ZHANG, Bin, HE, Shengfeng, DAN, Tingting, PENG, Hong, CAI, Hongmin
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2021
• Subjects: Feature extraction; Tensors; Kernel; Correlation; Task analysis; Numerical models; Training; Deep autoencoder; multiview clustering; self-supervised; universal and specific space learning; Information Security
• Online Access: https://ink.library.smu.edu.sg/sis_research/7851
• Institution: Singapore Management University

Multiview clustering seeks to partition objects via leveraging cross-view relations to provide a comprehensive description of the same objects. Most existing methods assume that different views are linear transformable or merely sampling from a common latent space. Such rigid assumptions betray real...