MUNPE:Multi-view uncorrelated neighborhood preserving embedding for unsupervised feature extraction-Reference-Cited by-同舟云学术

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MUNPE:Multi-view uncorrelated neighborhood preserving embedding for unsupervised feature extraction

Published:2024-03 Issue: Volume:287 Page:111421
ISSN:0950-7051
Container-title:Knowledge-Based Systems
language:en
Short-container-title:Knowledge-Based Systems

Author:

Jayashree ^ORCID,T. Shiva Prakash,K.R. Venugopal

Funder

Google

Publisher

Elsevier BV

Reference65 articles.

1. Deep multi-view learning methods: A review;Yan;Neurocomputing,2021

2. A unified robust framework for multi-view feature extraction with L2, 1-norm constraint;Zhang;Neural Netw.,2020

3. Multi-view learning overview: Recent progress and new challenges;Zhao;Inf. Fusion,2017

4. A survey on multiview clustering;Chao;IEEE Trans. Artif. Intell.,2021

5. A survey of multi-view representation learning;Li;IEEE Trans. Knowl. Data Eng.,2019

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Dual-enhanced generative model with graph attention network and contrastive learning for aspect sentiment triplet extraction;Knowledge-Based Systems;2024-10

2. Visible-hidden hybrid automatic feature engineering via multi-agent reinforcement learning;Knowledge-Based Systems;2024-09

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