Incomplete Multi-view Clustering with Sample-level Auto-weighted Graph Fusion-Reference-Cited by-同舟云学术

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Incomplete Multi-view Clustering with Sample-level Auto-weighted Graph Fusion

Published:2022 Issue: Volume: Page:1-1
ISSN:1041-4347
Container-title:IEEE Transactions on Knowledge and Data Engineering
language:
Short-container-title:IEEE Trans. Knowl. Data Eng.

Author:

Liang Naiyao¹,Yang Zuyuan²,Xie Shengli³

Affiliation:

1. School of Automation, Guangdong University of Technology, 47870 Guangzhou, Guangdong, China, 510006

2. School of Automation, Guangdong University of Technology - University Town Campus, 47870 Guangzhou, Guangdong, China

3. School of Automation, Guangdong University of Technology, Guangzhou, Guangdong, China

Funder

Key-Area Research and Development Program of Guangdong Province

Guangdong Basic and Applied Basic Research Foundation

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computational Theory and Mathematics,Computer Science Applications,Information Systems

Link

http://xplorestaging.ieee.org/ielx7/69/4358933/09767686.pdf?arnumber=9767686

Reference28 articles.

1. Multi-View Learning With Incomplete Views

2. Measuring Diversity in Graph Learning: A Unified Framework for Structured Multi-view Clustering

3. Partial multi-view clustering;zhi;Proc 28th AAAI Conf Artif Intell,2014

4. Infant Brain Development Prediction With Latent Partial Multi-View Representation Learning

5. Parameter-Free Weighted Multi-View Projected Clustering with Structured Graph Learning

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1. Partially shared federated multiview learning;Knowledge-Based Systems;2024-10

2. Hubness-Enabled Clustering and Recovery for Large-Scale Incomplete Multi-View Data;ACM Transactions on Knowledge Discovery from Data;2024-09-04

3. Complementary incomplete weighted concept factorization methods for multi-view clustering;Knowledge and Information Systems;2024-08-14

4. Low-rank representation induced missing-view recovery for incomplete multi-view clustering;Neurocomputing;2024-08

5. Tensor schatten-p norm guided incomplete multi-view self-representation clustering;Knowledge-Based Systems;2024-06

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