Shared Latent Embedding Learning for Multi-View Subspace Clustering Article Swipe

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Liu Zhao-hu , Peng Song , Jinshuai Mu , Wenming Zheng ·

YOU? · · 2023 · Open Access · · DOI: https://doi.org/10.1587/transinf.2023edl8044

Most existing multi-view subspace clustering approaches only capture the inter-view similarities between different views and ignore the optimal local geometric structure of the original data. To this end, in this letter, we put forward a novel method named shared latent embedding learning for multi-view subspace clustering (SLE-MSC), which can efficiently capture a better latent space. To be specific, we introduce a pseudo-label constraint to capture the intra-view similarities within each view. Meanwhile, we utilize a novel optimal graph Laplacian to learn the consistent latent representation, in which the common manifold is considered as the optimal manifold to obtain a more reasonable local geometric structure. Comprehensive experimental results indicate the superiority and effectiveness of the proposed method.

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Computer Science

Cluster Analysis

Nonlinear Dimensionality Reduction

Artificial Intelligence

Feature Learning

Theoretical Computer Science

Mechanical Engineering

Politics

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Subspace topology Computer science Cluster analysis Embedding Nonlinear dimensionality reduction Representation (politics) Constraint (computer-aided design) Artificial intelligence Manifold (fluid mechanics) Graph Feature learning Theoretical computer science Machine learning Pattern recognition (psychology) Mathematics Dimensionality reduction Geometry Engineering Political science Law Mechanical engineering Politics

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Type: article
Language: en
Landing Page: https://doi.org/10.1587/transinf.2023edl8044
PDF: https://www.jstage.jst.go.jp/article/transinf/E107.D/1/E107.D_2023EDL8044/_pdf
OA Status: diamond
Cited By: 1
References: 14
Related Works: 10
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DOI: https://doi.org/10.1587/transinf.2023edl8044

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Title: Shared Latent Embedding Learning for Multi-View Subspace Clustering

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Type: article

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Language: en

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Publication year: 2023

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Publication date: 2023-12-31

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Authors: Liu Zhao-hu, Peng Song, Jinshuai Mu, Wenming Zheng

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Landing page: https://doi.org/10.1587/transinf.2023edl8044

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Concepts: Subspace topology, Computer science, Cluster analysis, Embedding, Nonlinear dimensionality reduction, Representation (politics), Constraint (computer-aided design), Artificial intelligence, Manifold (fluid mechanics), Graph, Feature learning, Theoretical computer science, Machine learning, Pattern recognition (psychology), Mathematics, Dimensionality reduction, Geometry, Engineering, Political science, Law, Mechanical engineering, Politics

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Cited by: 1

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abstract_inverted_index.obtain	97
abstract_inverted_index.shared	38
abstract_inverted_index.space.	54
abstract_inverted_index.within	68
abstract_inverted_index.between	11
abstract_inverted_index.capture	7, 50, 64
abstract_inverted_index.forward	33
abstract_inverted_index.letter,	30
abstract_inverted_index.method.	115
abstract_inverted_index.optimal	17, 76, 94
abstract_inverted_index.results	106
abstract_inverted_index.utilize	73
abstract_inverted_index.existing	1
abstract_inverted_index.indicate	107
abstract_inverted_index.learning	41
abstract_inverted_index.manifold	89, 95
abstract_inverted_index.original	23
abstract_inverted_index.proposed	114
abstract_inverted_index.subspace	3, 44
abstract_inverted_index.Laplacian	78
abstract_inverted_index.different	12
abstract_inverted_index.embedding	40
abstract_inverted_index.geometric	19, 102
abstract_inverted_index.introduce	59
abstract_inverted_index.specific,	57
abstract_inverted_index.structure	20
abstract_inverted_index.(SLE-MSC),	46
abstract_inverted_index.Meanwhile,	71
abstract_inverted_index.approaches	5
abstract_inverted_index.clustering	4, 45
abstract_inverted_index.considered	91
abstract_inverted_index.consistent	82
abstract_inverted_index.constraint	62
abstract_inverted_index.inter-view	9
abstract_inverted_index.intra-view	66
abstract_inverted_index.multi-view	2, 43
abstract_inverted_index.reasonable	100
abstract_inverted_index.structure.	103
abstract_inverted_index.efficiently	49
abstract_inverted_index.superiority	109
abstract_inverted_index.experimental	105
abstract_inverted_index.pseudo-label	61
abstract_inverted_index.similarities	10, 67
abstract_inverted_index.Comprehensive	104
abstract_inverted_index.effectiveness	111
abstract_inverted_index.representation,	84
cited_by_percentile_year.max	94
cited_by_percentile_year.min	90
countries_distinct_count	1
institutions_distinct_count	4
citation_normalized_percentile.value	0.49364994
citation_normalized_percentile.is_in_top_1_percent	False
citation_normalized_percentile.is_in_top_10_percent	False