Anchor Pseudo-Supervise Large-Scale Incomplete Multi-View Clustering-Reference-Cited by-同舟云学术

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Anchor Pseudo-Supervise Large-Scale Incomplete Multi-View Clustering

Published:2023 Issue: Volume:11 Page:107812-107822
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Zhu Songbai¹^ORCID,Dai Jian²,Yang Guolai¹,Ren Zhenwen³^ORCID

Affiliation:

1. School of Mechanical Engineering, Nanjing University of Science and Technology, Nanjing, China

2. Southwest Automation Research Institute, China South Industries Group Corporation, Mianyang, China

3. School of National Defence Science and Technology, Southwest University of Science and Technology, Mianyang, China

Funder

Project of Guangxi Key Laboratory of Machine Vision and Intelligent Control

Miaozi Project of Sichuan Province

Natural Science Foundation of Sichuan Province

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/10005208/10264091.pdf?arnumber=10264091

Reference43 articles.

1. Cluster center consistency guided sampling learning for multiple kernel clustering

2. Anchors Bring Ease: An Embarrassingly Simple Approach to Partial Multi-View Clustering

3. Enhanced group sparse regularized nonconvex regression for face recognition;zhang;IEEE Trans Pattern Anal Mach Intell,2022

4. Self-Representation Subspace Clustering for Incomplete Multi-view Data

5. Consensus Cluster Center Guided Latent Multi-kernel Clustering

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