14.2.6.3.1 Multi-View Subspace Clustering, Multi-View Subspace Learning

Chen, N.[Ning], Zhu, J.[Jun], Sun, F.C.[Fu-Chun], Xing, E.P.[Eric Poe],
Large-Margin Predictive Latent Subspace Learning for Multiview Data Analysis,
PAMI(34), No. 12, December 2012, pp. 2365-2378.
IEEE DOI 1210
BibRef

Wang, Y.[Yang], Lin, X.M.[Xue-Min], Wu, L.[Lin], Zhang, W.J.[Wen-Jie], Zhang, Q.[Qing], Huang, X.D.[Xiao-Di],
Robust Subspace Clustering for Multi-View Data by Exploiting Correlation Consensus,
IP(24), No. 11, November 2015, pp. 3939-3949.
IEEE DOI 1509
compressed sensing BibRef

Yin, Q.Y.[Qi-Yue], Wu, S.[Shu], Wang, L.[Liang],
Unified subspace learning for incomplete and unlabeled multi-view data,
PR(67), No. 1, 2017, pp. 313-327.
Elsevier DOI 1704
Multi-view learning BibRef

Brbic, M.[Maria], Kopriva, I.[Ivica],
Multi-view low-rank sparse subspace clustering,
PR(73), No. 1, 2018, pp. 247-258.
Elsevier DOI 1709
Subspace clustering BibRef

Chen, X.J.[Xiao-Jun], Yang, M.[Min], Huang, J.Z.[Joshua Zhexue], Ming, Z.[Zhong],
TWCC: Automated Two-way Subspace Weighting Partitional Co-Clustering,
PR(76), No. 1, 2018, pp. 404-415.
Elsevier DOI 1801
Data mining BibRef

You, X.G.[Xin-Ge], Xu, J.M.[Jia-Miao], Yuan, W.[Wei], Jing, X.Y.[Xiao-Yuan], Tao, D.C.[Da-Cheng], Zhang, T.P.[Tai-Ping],
Multi-view common component discriminant analysis for cross-view classification,
PR(92), 2019, pp. 37-51.
Elsevier DOI 1905
Cross-view classification, Local geometry preservation, Multi-view learning, Subspace learning BibRef

Chen, Y.Y.[Yong-Yong], Xiao, X.L.[Xiao-Lin], Zhou, Y.C.[Yi-Cong],
Jointly Learning Kernel Representation Tensor and Affinity Matrix for Multi-View Clustering,
MultMed(22), No. 8, August 2020, pp. 1985-1997.
IEEE DOI 2007
Tensors, Kernel, Symmetric matrices, Sparse matrices, Matrix decomposition, Correlation, Clustering algorithms, adaptive weight
See also Generalized Nonconvex Low-Rank Tensor Approximation for Multi-View Subspace Clustering. BibRef

Chen, Y.Y.[Yong-Yong], Xiao, X.L.[Xiao-Lin], Zhou, Y.C.[Yi-Cong],
Multi-View Subspace Clustering via Simultaneously Learning the Representation Tensor and Affinity Matrix,
PR(106), 2020, pp. 107441.
Elsevier DOI 2006
Multi-view subspace clustering, Low-rank tensor representation, Local manifold BibRef

Xiao, X.L.[Xiao-Lin], Gong, Y.J.[Yue-Jiao], Hua, Z.Y.[Zhong-Yun], Chen, W.N.[Wei-Neng],
On Reliable Multi-View Affinity Learning for Subspace Clustering,
MultMed(23), 2021, pp. 4555-4566.
IEEE DOI 2112
Tensors, Sparse matrices, Data structures, Correlation, Data models, Robustness, Manifolds, Affinity learning, self-representation BibRef

Chen, Y.Y.[Yong-Yong], Xiao, X.L.[Xiao-Lin], Peng, C.[Chong], Lu, G.M.[Guang-Ming], Zhou, Y.C.[Yi-Cong],
Low-Rank Tensor Graph Learning for Multi-View Subspace Clustering,
CirSysVideo(32), No. 1, January 2022, pp. 92-104.
IEEE DOI 2201
Tensors, Matrix decomposition, Clustering methods, Adaptation models, Correlation, Clustering algorithms, graph learning BibRef

Kang, K.[Kehan], Chen, C.L.Z.[Cheng-Li-Zhao], Peng, C.[Chong],
Consensus Low-Rank Multi-View Subspace Clustering With Cross-View Diversity Preserving,
SPLetters(30), 2023, pp. 1512-1516.
IEEE DOI 2311
BibRef

Wang, S.Q.[Shu-Qin], Lin, Z.P.[Zhi-Ping], Cao, Q.[Qi], Cen, Y.G.[Yi-Gang], Chen, Y.Y.[Yong-Yong],
Bi-Nuclear Tensor Schatten-p Norm Minimization for Multi-View Subspace Clustering,
IP(32), 2023, pp. 4059-4072.
IEEE DOI 2307
Tensors, Clustering methods, Correlation, Minimization, Estimation, Computational complexity, Optimization, Schatten-p norm BibRef

Xiao, X.L.[Xiao-Lin], Wu, Y.[Yue], Gong, Y.J.[Yue-Jiao],
Relative Comparison-Based Consensus Learning for Multi-View Subspace Clustering,
CirSysVideo(34), No. 12, December 2024, pp. 12376-12387.
IEEE DOI 2501
Clustering algorithms, Data models, Kernel, Computational modeling, Vectors, Tensors, Symmetric matrices, Consensus learning, relative comparison BibRef

Zhu, W.C.[Wen-Cheng], Lu, J.W.[Ji-Wen], Zhou, J.[Jie],
Structured general and specific multi-view subspace clustering,
PR(93), 2019, pp. 392-403.
Elsevier DOI 1906
Subspace clustering, Multi-view learning, Structure consistence, Diversity BibRef

Xie, Y.[Yuan], Tao, D.C.[Da-Cheng], Zhang, W.S.[Wen-Sheng], Liu, Y.[Yan], Zhang, L.[Lei], Qu, Y.Y.[Yan-Yun],
On Unifying Multi-view Self-Representations for Clustering by Tensor Multi-rank Minimization,
IJCV(126), No. 11, November 2018, pp. 1157-1179.
Springer DOI 1809
multi-view subspace clustering problem BibRef

Wang, X.B.[Xiao-Bo], Lei, Z.[Zhen], Guo, X.J.[Xiao-Jie], Zhang, C.Q.[Chang-Qing], Shi, H.L.[Hai-Lin], Li, S.Z.[Stan Z.],
Multi-view subspace clustering with intactness-aware similarity,
PR(88), 2019, pp. 50-63.
Elsevier DOI 1901
Intact space, Intactness-aware similarity, Multi-view subspace clustering BibRef

Xue, Z., Du, J., Du, D., Li, G., Huang, Q., Lyu, S.,
Deep Constrained Low-Rank Subspace Learning for Multi-View Semi-Supervised Classification,
SPLetters(26), No. 8, August 2019, pp. 1177-1181.
IEEE DOI 1908
learning (artificial intelligence), matrix decomposition, pattern classification, semi-supervised classification BibRef

Yang, Z., Xu, Q., Zhang, W., Cao, X., Huang, Q.,
Split Multiplicative Multi-View Subspace Clustering,
IP(28), No. 10, October 2019, pp. 5147-5160.
IEEE DOI 1909
Clustering methods, Sparse matrices, Optimization, Periodic structures, Information security, Computer security, image representation BibRef

Zhang, C.Q.[Chang-Qing], Fu, H.Z.[Hua-Zhu], Hu, Q.H.[Qing-Hua], Cao, X.C.[Xiao-Chun], Xie, Y.[Yuan], Tao, D.C.[Da-Cheng], Xu, D.[Dong],
Generalized Latent Multi-View Subspace Clustering,
PAMI(42), No. 1, January 2020, pp. 86-99.
IEEE DOI 1912
Clustering methods, Correlation, Neural networks, Task analysis, Clustering algorithms, Minimization, neural networks BibRef

Zhang, C.Q.[Chang-Qing], Fu, H.Z.[Hua-Zhu], Liu, S.[Si], Liu, G., Cao, X.C.[Xiao-Chun],
Low-Rank Tensor Constrained Multiview Subspace Clustering,
ICCV15(1582-1590)
IEEE DOI 1602
Aerospace electronics BibRef

Li, R.H.[Rui-Huang], Zhang, C.Q.[Chang-Qing], Fu, H.Z.[Hua-Zhu], Peng, X.[Xi], Zhou, J.T.Y.[Joey Tian-Yi], Hu, Q.H.[Qing-Hua],
Reciprocal Multi-Layer Subspace Learning for Multi-View Clustering,
ICCV19(8171-8179)
IEEE DOI 2004
learning (artificial intelligence), optimisation, pattern clustering, multiview clustering, high-dimensional data BibRef

Cao, X.C.[Xiao-Chun], Zhang, C.Q.[Chang-Qing], Fu, H.Z.[Hua-Zhu], Liu, S.[Si], Zhang, H.[Hua],
Diversity-induced Multi-view Subspace Clustering,
CVPR15(586-594)
IEEE DOI 1510
BibRef

Zhang, C.Q.[Chang-Qing], Hu, Q.H.[Qing-Hua], Fu, H.Z.[Hua-Zhu], Zhu, P., Cao, X.C.[Xiao-Chun],
Latent Multi-view Subspace Clustering,
CVPR17(4333-4341)
IEEE DOI 1711
Clustering algorithms, Clustering methods, Erbium, Kernel, Linear programming, Optimization, Robustness BibRef

Zhang, C.Q.[Chang-Qing], Fu, H.Z.[Hua-Zhu], Wang, J.[Jing], Li, W.[Wen], Cao, X.C.[Xiao-Chun], Hu, Q.H.[Qing-Hua],
Tensorized Multi-view Subspace Representation Learning,
IJCV(128), No. 8-9, September 2020, pp. 2344-2361.
Springer DOI 2008
BibRef

Yan, F.[Fei], Wang, X.D.[Xiao-Dong], Zeng, Z.Q.[Zhi-Qiang], Hong, C.Q.[Chao-Qun],
Adaptive multi-view subspace clustering for high-dimensional data,
PRL(130), 2020, pp. 299-305.
Elsevier DOI 2002
Subspace clustering, Multi-view clustering, Adaptive learning, Feature selection BibRef

Tao, H.[Hong], Hou, C.P.[Chen-Ping], Qian, Y.H.[Yu-Hua], Zhu, J.B.[Ju-Bo], Yi, D.Y.[Dong-Yun],
Latent Complete Row Space Recovery for Multi-View Subspace Clustering,
IP(29), 2020, pp. 8083-8096.
IEEE DOI 2008
Clustering algorithms, Clustering methods, Video surveillance, Sparse matrices, Tensile stress, Unsupervised learning, row space recovery BibRef

Fan, R.D.[Rui-Dong], Luo, T.J.[Ting-Jin], Zhuge, W.Z.[Wen-Zhang], Qiang, S.[Sheng], Hou, C.P.[Chen-Ping],
Multi-view subspace learning via bidirectional sparsity,
PR(108), 2020, pp. 107524.
Elsevier DOI 2008
Multi-view clustering, Subspace learning, Bidirectional sparsity, Non-convex optimization BibRef

Paul, D.[Dipanjyoti], Saha, S.[Sriparna], Kumar, A.[Abhishek], Mathew, J.[Jimson],
Evolutionary multi-objective optimization based overlapping subspace clustering,
PRL(145), 2021, pp. 208-215.
Elsevier DOI 2104
Subspace clustering, Multi-objective optimization, ICC-index, PSM-index, MNR-index BibRef

Mitra, S.[Sayantan], Saha, S.[Sriparna],
A Multi-task Multi-view based Multi-objective Clustering Algorithm,
ICPR21(4720-4727)
IEEE DOI 2105
Clustering algorithms, Classification algorithms, Indexes, Task analysis, Optimization, Cluster validity index BibRef

Chumachenko, K.[Kateryna], Raitoharju, J.[Jenni], Iosifidis, A.[Alexandros], Gabbouj, M.[Moncef],
Speed-up and multi-view extensions to subclass discriminant analysis,
PR(111), 2021, pp. 107660.
Elsevier DOI 2012
Subclass discriminant analysis, Spectral regression, Multi-view learning, Kernel regression, Subspace learning BibRef

Wu, Z.J.[Zhi-Jian], Li, J.[Jun], Xu, J.H.[Jian-Hua], Yang, W.K.[Wan-Kou],
Beyond ITQ: Efficient binary multi-view subspace learning for instance retrieval,
JVCIR(79), 2021, pp. 103234.
Elsevier DOI 2109
Instance retrieval, Multi-view fusion, Hamming subspace, Unsupervised learning BibRef

Ma, J.[Junbo], Wang, R.[Ruili], Ji, W.T.[Wan-Ting], Zhao, J.W.[Jia-Wei], Zong, M.[Ming], Gilman, A.[Andrew],
Robust multi-view continuous subspace clustering,
PRL(150), 2021, pp. 306-312.
Elsevier DOI 2109
Multi-view learning, Clustering, Common subspace, Representation, Big data analysis BibRef

Hu, Y.L.[Yong-Li], Luo, C.C.[Cui-Cui], Wang, B.Y.[Bo-Yue], Gao, J.B.[Jun-Bin], Sun, Y.F.[Yan-Feng], Yin, B.C.[Bao-Cai],
Complete/incomplete multi-view subspace clustering via soft block-diagonal-induced regulariser,
IET-CV(15), No. 8, 2021, pp. 618-632.
DOI Link 2110
BibRef

Qin, Y.[Yalan], Wu, H.Z.[Han-Zhou], Zhang, X.P.[Xin-Peng], Feng, G.R.[Guo-Rui],
Semi-Supervised Structured Subspace Learning for Multi-View Clustering,
IP(31), 2022, pp. 1-14.
IEEE DOI 2112
Image reconstruction, Image coding, Clustering algorithms, Deep learning, Clustering methods, Unsupervised learning, enhanced structural consistency BibRef

Si, X.M.[Xiao-Meng], Yin, Q.Y.[Qi-Yue], Zhao, X.J.[Xiao-Jie], Yao, L.[Li],
Consistent and diverse multi-View subspace clustering with structure constraint,
PR(121), 2022, pp. 108196.
Elsevier DOI 2109
Subspace self-representation, Multi-view clustering, Consistency, Diversity, Clustering structure BibRef

An, J.[Jing], Liu, X.X.[Xiao-Xia], Shi, M.[Mei], Guo, J.[Jun], Gong, X.Q.[Xiao-Qing], Li, Z.H.[Zhi-Hui],
Weighted multi-view common subspace learning method,
PRL(151), 2021, pp. 355-361.
Elsevier DOI 2110
Weighted parameter, Multi-view learning, Common subspace learning, Supervised learning BibRef

Wang, Q.Q.[Qian-Qian], Cheng, J.F.[Jia-Feng], Gao, Q.X.[Quan-Xue], Zhao, G.S.[Guo-Shuai], Jiao, L.C.[Li-Cheng],
Deep Multi-View Subspace Clustering With Unified and Discriminative Learning,
MultMed(23), 2021, pp. 3483-3493.
IEEE DOI 2110
Clustering methods, Correlation, Decoding, Feature extraction, Intserv networks, Convolution, Databases, Multi-view clustering, discriminative learning BibRef

Zhao, L.[Liang], Zhang, J.[Jie], Wang, Q.H.[Qiu-Hao], Chen, Z.K.[Zhi-Kui],
Dual Alignment Self-Supervised Incomplete Multi-View Subspace Clustering Network,
SPLetters(28), 2021, pp. 2122-2126.
IEEE DOI 2112
Data models, Manifolds, Kernel, Decoding, Clustering algorithms, Software, Semantics, Incomplete multi-view clustering, auto-encoders BibRef

Yuan, X.[Xu], Gu, S.K.[Shao-Kui], Liu, Z.J.[Zhen-Jiao], Zhao, L.[Liang],
Mining Multi-View Clustering Space With Interpretable Space Search Constraint,
SPLetters(30), 2023, pp. 1422-1426.
IEEE DOI 2310
BibRef

Chen, Z.K.[Zhi-Kui], Li, Y.[Yue], Lou, K.[Kai], Zhao, L.[Liang],
Incomplete Multi-View Clustering With Complete View Guidance,
SPLetters(30), 2023, pp. 1247-1251.
IEEE DOI 2310
BibRef

Chen, Y.Y.[Yong-Yong], Wang, S.Q.[Shu-Qin], Peng, C.[Chong], Hua, Z.Y.[Zhong-Yun], Zhou, Y.C.[Yi-Cong],
Generalized Nonconvex Low-Rank Tensor Approximation for Multi-View Subspace Clustering,
IP(30), 2021, pp. 4022-4035.
IEEE DOI 2104
Tensors, Correlation, Sparse matrices, Clustering methods, Task analysis, Estimation, Pairwise error probability, subspace clustering
See also Jointly Learning Kernel Representation Tensor and Affinity Matrix for Multi-View Clustering. BibRef

Wang, S.W.[Si-Wei], Liu, X.W.[Xin-Wang], Zhu, X.Z.[Xin-Zhong], Zhang, P.[Pei], Zhang, Y.[Yi], Gao, F.[Feng], Zhu, E.[En],
Fast Parameter-Free Multi-View Subspace Clustering With Consensus Anchor Guidance,
IP(31), 2022, pp. 556-568.
IEEE DOI 2112
Clustering algorithms, Time complexity, Optimization, Matrix decomposition, Symmetric matrices, Convergence, multiple view clustering BibRef

Ma, H.M.[Hui-Min], Wang, S.W.[Si-Wei], Zhang, J.[Junpu], Yu, S.J.[Sheng-Ju], Liu, S.Y.[Su-Yuan], Liu, X.W.[Xin-Wang], He, K.L.[Kun-Lun],
Symmetric Multi-View Subspace Clustering With Automatic Neighbor Discovery,
CirSysVideo(34), No. 9, September 2024, pp. 8766-8778.
IEEE DOI 2410
Symmetric matrices, Optimization, Task analysis, Laplace equations, Kernel, Circuits and systems, Vectors, automatic neighbor discovery BibRef

Chen, Y.Y.[Yong-Yong], Wang, S.Q.[Shu-Qin], Xiao, X.L.[Xiao-Lin], Liu, Y.F.[You-Fa], Hua, Z.Y.[Zhong-Yun], Zhou, Y.C.[Yi-Cong],
Self-Paced Enhanced Low-Rank Tensor Kernelized Multi-View Subspace Clustering,
MultMed(24), 2022, pp. 4054-4066.
IEEE DOI 2208
Tensors, Kernel, Streaming media, Feature extraction, Videos, Reliability, Clustering methods, Multi-view clustering, self-paced learning BibRef

Wang, S.Q.[Shu-Qin], Chen, Y.Y.[Yong-Yong], Cen, Y.G.[Yi-Gang], Zhang, L.[Linna], Voronin, V.[Viacheslav],
Low-Rank and Sparse Tensor Representation for Multi-View Subspace Clustering,
ICIP21(1534-1538)
IEEE DOI 2201
Tensors, Image processing, Clustering methods, Convex functions, Sparse matrices, Optimization, Multi-view clustering, sparse constraint. BibRef

Fu, L.[Lele], Chen, Z.L.[Zhao-Liang], Chen, Y.Y.[Yong-Yong], Wang, S.P.[Shi-Ping],
Unified Low-Rank Tensor Learning and Spectral Embedding for Multi-View Subspace Clustering,
MultMed(25), 2023, pp. 4972-4985.
IEEE DOI 2311
BibRef

Li, Z.L.[Zheng-Lai], Tang, C.[Chang], Zheng, X.[Xiao], Liu, X.W.[Xin-Wang], Zhang, W.[Wei], Zhu, E.[En],
High-Order Correlation Preserved Incomplete Multi-View Subspace Clustering,
IP(31), 2022, pp. 2067-2080.
IEEE DOI 2203
Correlation, Tensors, Task analysis, Optimization, Kernel, Image reconstruction, Sparse matrices, missing view imputation BibRef

Sun, M.J.[Meng-Jing], Wang, S.W.[Si-Wei], Zhang, P.[Pei], Liu, X.W.[Xin-Wang], Guo, X.F.[Xi-Feng], Zhou, S.H.[Si-Hang], Zhu, E.[En],
Projective Multiple Kernel Subspace Clustering,
MultMed(24), 2022, pp. 2567-2579.
IEEE DOI 2205
Kernel, Optimization, Clustering algorithms, Integrated circuits, Hilbert space, Redundancy, Clustering methods, Kernel clustering, multi-view information fusion BibRef

Lan, M.C.[Meng-Cheng], Meng, M.[Min], Yu, J.[Jun], Wu, J.G.[Ji-Gang],
Generalized Multi-View Collaborative Subspace Clustering,
CirSysVideo(32), No. 6, June 2022, pp. 3561-3574.
IEEE DOI 2206
Collaboration, Correlation, Tensors, Task analysis, Optimization, Linear programming, Deep learning, Multi-view clustering, low-rank representation BibRef

Tang, Y.Q.[Yong-Qiang], Xie, Y.[Yuan], Zhang, C.Y.[Chen-Yang], Zhang, W.[Wensheng],
Constrained Tensor Representation Learning for Multi-View Semi-Supervised Subspace Clustering,
MultMed(24), 2022, pp. 3920-3933.
IEEE DOI 2208
Representation learning, Tensors, Correlation, Clustering algorithms, Minimization, Task analysis, Optimization, tensor singular value decomposition (t-SVD) BibRef

Zheng, Q.H.[Qing-Hai],
Large-Scale Multi-View Clustering via Fast Essential Subspace Representation Learning,
SPLetters(29), 2022, pp. 1893-1897.
IEEE DOI 2209
Signal processing algorithms, Optimization, Costs, Representation learning, Time complexity, Clustering algorithms, linear computational complexity BibRef

Liu, Q.L.[Qi-Liang], Huan, W.H.[Wei-Hua], Deng, M.[Min],
A Method with Adaptive Graphs to Constrain Multi-View Subspace Clustering of Geospatial Big Data from Multiple Sources,
RS(14), No. 17, 2022, pp. xx-yy.
DOI Link 2209
BibRef

Tan, J.P.[Jun-Peng], Yang, Z.J.[Zhi-Jing], Ren, J.C.[Jin-Chang], Wang, B.[Bing], Cheng, Y.Q.[Yong-Qiang], Ling, W.K.[Wing-Kuen],
A Novel Robust Low-rank Multi-view Diversity Optimization Model with Adaptive-Weighting Based Manifold Learning,
PR(122), 2022, pp. 108298.
Elsevier DOI 2112
Low-rank Representation (LRR), Multi-view Subspace Clustering (MVSC), Adaptive-Weighting Manifold Learning (AWML) BibRef

Yu, Z.W.[Zhi-Wen], Wang, D.X.[Da-Xing], Meng, X.B.[Xian-Bing], Chen, C.L.P.[C. L. Philip],
Clustering Ensemble Based on Hybrid Multiview Clustering,
Cyber(52), No. 7, July 2022, pp. 6518-6530.
IEEE DOI 2207
Clustering algorithms, Kernel, Machine learning algorithms, Research and development, Machine learning, Fuses, random subspace transformation BibRef

Wang, S.[Shiye], Li, C.S.[Chang-Sheng], Li, Y.M.[Yan-Ming], Yuan, Y.[Ye], Wang, G.R.[Guo-Ren],
Self-Supervised Information Bottleneck for Deep Multi-View Subspace Clustering,
IP(32), 2023, pp. 1555-1567.
IEEE DOI 2303
Mutual information, Deep learning, Data models, Training, Task analysis, Representation learning, Feature extraction, subspace clustering BibRef

Zhao, J.B.[Jin-Biao], Lu, G.F.[Gui-Fu],
Clean affinity matrix learning with rank equality constraint for multi-view subspace clustering,
PR(134), 2023, pp. 109118.
Elsevier DOI 2212
Low-rank representation, Robust principal component analysis, Outliers value, Affinity matrix, Low-rank matrix decomposition BibRef

Cai, B.[Bing], Lu, G.F.[Gui-Fu], Yao, L.[Liang], Li, H.[Hua],
High-order manifold regularized multi-view subspace clustering with robust affinity matrices and weighted TNN,
PR(134), 2023, pp. 109067.
Elsevier DOI 2212
High-order manifold regularization, Robust affinity matrices, Multi-view subspace clustering, Weighted TNN BibRef

Guo, J.P.[Ji-Peng], Sun, Y.F.[Yan-Feng], Gao, J.B.[Jun-Bin], Hu, Y.L.[Yong-Li], Yin, B.C.[Bao-Cai],
Multi-Attribute Subspace Clustering via Auto-Weighted Tensor Nuclear Norm Minimization,
IP(31), 2022, pp. 7191-7205.
IEEE DOI 2212
Tensors, Optimization, Minimization, Correlation, Clustering methods, Task analysis, Sun, Subspace clustering, auto-weighted tensor nuclear norm BibRef

Guo, J.P.[Ji-Peng], Sun, Y.F.[Yan-Feng], Gao, J.B.[Jun-Bin], Hu, Y.L.[Yong-Li], Yin, B.C.[Bao-Cai],
Logarithmic Schatten-p Norm Minimization for Tensorial Multi-View Subspace Clustering,
PAMI(45), No. 3, March 2023, pp. 3396-3410.
IEEE DOI 2302
Tensors, Correlation, Clustering algorithms, Task analysis, Sun, Periodic structures, Minimization, Convergence guarantees BibRef

Wu, H.J.[Hong-Jie], Huang, S.D.[Shu-Dong], Tang, C.W.[Chen-Wei], Zhang, Y.C.[Yan-Cheng], Lv, J.C.[Jian-Cheng],
Pure graph-guided multi-view subspace clustering,
PR(136), 2023, pp. 109187.
Elsevier DOI 2301
Multi-view learning, Subspace clustering, Graph learning, Pure graph BibRef

Wang, S.Q.[Shu-Qin], Chen, Y.Y.[Yong-Yong], Lin, Z.P.[Zhi-Ping], Cen, Y.G.[Yi-Gang], Cao, Q.[Qi],
Robustness Meets Low-Rankness: Unified Entropy and Tensor Learning for Multi-View Subspace Clustering,
CirSysVideo(33), No. 11, November 2023, pp. 6302-6316.
IEEE DOI 2311
BibRef

Chen, Z.[Zhe], Wu, X.J.[Xiao-Jun], Xu, T.Y.[Tian-Yang], Kittler, J.V.[Josef V.],
Fast Self-Guided Multi-View Subspace Clustering,
IP(32), 2023, pp. 6514-6525.
IEEE DOI Code:
WWW Link. 2312
BibRef

Du, Y.F.[Yang-Fan], Lu, G.F.[Gui-Fu], Ji, G.[Guangyan],
Robust Least Squares Regression for Subspace Clustering: A Multi-View Clustering Perspective,
IP(33), 2024, pp. 216-227.
IEEE DOI 2312
BibRef

Long, Z.[Zhen], Zhu, C.[Ce], Chen, J.[Jie], Li, Z.H.[Zi-Han], Ren, Y.Z.[Ya-Zhou], Liu, Y.P.[Yi-Peng],
Multi-View MERA Subspace Clustering,
MultMed(26), 2024, pp. 3102-3112.
IEEE DOI 2402
Tensors, Correlation, Matrix decomposition, Clustering algorithms, Task analysis, Sparse matrices, Singular value decomposition, self-representation learning BibRef

Chen, Y.Y.[Yong-Yong], Wang, S.Q.[Shu-Qin], Zhao, Y.P.[Yin-Ping], Chen, C.L.P.[C. L. Philip],
Double Discrete Cosine Transform-Oriented Multi-View Subspace Clustering,
IP(33), 2024, pp. 2491-2501.
IEEE DOI 2404
Tensors, Discrete Fourier transforms, Discrete cosine transforms, Matrix decomposition, Correlation, Clustering methods, discrete cosine transform BibRef

Chang, W.[Wei], Chen, H.M.[Hui-Min], Nie, F.P.[Fei-Ping], Wang, R.[Rong], Li, X.L.[Xue-Long],
Tensorized and Compressed Multi-View Subspace Clustering via Structured Constraint,
PAMI(46), No. 12, December 2024, pp. 10434-10451.
IEEE DOI 2411
Dictionaries, Tensors, Costs, Bipartite graph, Optimization, Clustering methods, Clustering algorithms, optimal bipartite graph BibRef

Mi, Y.[Yong], Chen, H.M.[Hong-Mei], Yuan, Z.[Zhong], Luo, C.[Chuan], Horng, S.J.[Shi-Jinn], Li, T.R.[Tian-Rui],
Fast Multi-view Subspace Clustering with Balance Anchors Guidance,
PR(145), 2024, pp. 109895.
Elsevier DOI 2311
Multi-view subspace clustering, Anchor-based MVSC methods, Balance structure, Anchor graph BibRef

Wang, Y.N.[Yi-Nuo], Guo, Y.[Yu], Wang, Z.[Zheng], Wang, F.[Fei],
Joint learning of latent subspace and structured graph for multi-view clustering,
PR(154), 2024, pp. 110592.
Elsevier DOI 2406
Multi-view clustering, Latent space, Subspace clustering, Graph learning BibRef

Xie, D.[Deyan], Yang, M.[Ming], Gao, Q.X.[Quan-Xue], Song, W.[Wei],
Non-convex tensorial multi-view clustering by integrating L1-based sliced-Laplacian regularization and L2,p-sparsity,
PR(154), 2024, pp. 110605.
Elsevier DOI 2406
Multi-view subspace clustering, t-SVD BibRef

Cai, B.[Bing], Lu, G.F.[Gui-Fu], Li, H.[Hua], Song, W.H.[Wei-Hong],
Tensorized Scaled Simplex Representation for Multi-View Clustering,
MultMed(26), 2024, pp. 6621-6631.
IEEE DOI 2404
Tensors, Task analysis, Information technology, Fuses, Correlation, Adaptation models, Transforms, Scaled simplex representation, multi-view clustering BibRef

Cai, B.[Bing], Lu, G.F.[Gui-Fu], Guo, X.X.[Xiao-Xing], Wu, T.[Tong],
Tensorized latent representation with automatic dimensionality selection for multi-view clustering,
PR(160), 2025, pp. 111192.
Elsevier DOI 2501
Multi-view clustering, Latent representation, Singular value decomposition, Tensor subspace learning BibRef

Du, Y.F.[Yang-Fan], Lu, G.F.[Gui-Fu],
Joint local smoothness and low-rank tensor representation for robust multi-view clustering,
PR(157), 2025, pp. 110944.
Elsevier DOI 2409
Subspace clustering, Tensor, Tensor nuclear norm, Total variation BibRef

Shi, L.[Long], Cao, L.[Lei], Wang, J.[Jun], Chen, B.D.[Ba-Dong],
Enhanced Latent Multi-View Subspace Clustering,
CirSysVideo(34), No. 12, December 2024, pp. 12480-12495.
IEEE DOI 2501
Sparse matrices, Optimization, Clustering methods, Kernel, Principal component analysis, sparse regularization BibRef

Ji, J.T.[Jin-Tian], Feng, S.[Songhe],
Anchor Structure Regularization Induced Multi-view Subspace Clustering via Enhanced Tensor Rank Minimization,
ICCV23(19286-19295)
IEEE DOI 2401
BibRef

Song, J.[Jinjoo], Yoon, G.J.[Gang-Joon], Baek, S.[Sangwon], Yoon, S.M.[Sang Min],
Multi-View Feature Boosting Network for Deep Subspace Clustering,
ICIP22(496-500)
IEEE DOI 2211
Fuses, Clustering methods, Noise reduction, Neural networks, Benchmark testing, Boosting, Feature extraction, Data mining, Feature boosting BibRef

Wu, S., Lu, Z., Tang, H., Yan, Y., Zhu, S., Jing, X., Li, Z.,
Joint Learning of Self-Representation and Indicator for Multi-View Image Clustering,
ICIP19(4095-4099)
IEEE DOI 1910
Multi-view Clustering, Subspace Clustering, Self-representation Learning BibRef

Wang, X.B.[Xiao-Bo], Guo, X.J.[Xiao-Jie], Lei, Z.[Zhen], Zhang, C.Q.[Chang-Qing], Li, S.Z.[Stan Z.],
Exclusivity-Consistency Regularized Multi-view Subspace Clustering,
CVPR17(1-9)
IEEE DOI 1711
Benchmark testing, Clustering algorithms, Optimization, Standards BibRef

Zhang, Y., Wang, X., Gao, X.,
Adaptive Latent Representation for Multi-view Subspace Learning,
ICPR18(1229-1234)
IEEE DOI 1812
Clustering methods, Linear programming, Learning systems, Noise measurement, Optimization methods, Sparse matrices BibRef

Wang, L.[Lei], Li, D.P.[Dan-Ping], He, T.C.[Tian-Cheng], Xue, Z.[Zhong],
Manifold Regularized Multi-view Subspace Clustering for image representation,
ICPR16(283-288)
IEEE DOI 1705
Clustering algorithms, Data models, Laplace equations, Manifolds, Optimization, Sparse matrices, Standards BibRef

Gao, H., Nie, F., Li, X., Huang, H.,
Multi-view Subspace Clustering,
ICCV15(4238-4246)
IEEE DOI 1602
Benchmark testing BibRef

Kobayashi, T.[Takumi],
BFO Meets HOG: Feature Extraction Based on Histograms of Oriented p.d.f. Gradients for Image Classification,
CVPR13(747-754)
IEEE DOI 1309
BibRef
Earlier:
Generalized Mutual Subspace Based Methods for Image Set Classification,
ACCV12(I:578-592).
Springer DOI 1304
BibRef
And:
Higher-order Co-occurrence Features based on Discriminative Co-clusters for Image Classification,
BMVC12(64).
DOI Link 1301
bag of features
See also Motion Recognition Using Local Auto-Correlation of Space-Time Gradients. BibRef

Chapter on Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms continues in
Distance Measures, Criteria for Clustering .