14.1.12 Multi-View Learning, Transfer from Other View

Zhang, Q.J.[Qing-Jiu], Sun, S.L.[Shi-Liang],
Multiple-view multiple-learner active learning,
PR(43), No. 9, September 2010, pp. 3113-3119.
Elsevier DOI 1006
Multiple-view learning; Multiple-learner learning; Active learning; Artificial neural network BibRef

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, Z.[Zhe], Chen, S.C.[Song-Can], Gao, D.[Daqi],
A novel multi-view learning developed from single-view patterns,
PR(44), No. 10-11, October-November 2011, pp. 2395-2413.
Elsevier DOI 1101
Multi-view learning; Classifier design; Rademacher complexity; Ensemble learning; Ho-Kashyap classifier; Regularization learning; Pattern recognition
See also Algorithm for Linear Inequalities and its Applications, An. BibRef

Wang, Z.[Zhe], Zhu, C.M.[Chang-Ming], Gao, D.[Daqi], Chen, S.C.[Song-Can],
Three-fold structured classifier design based on matrix pattern,
PR(46), No. 6, June 2013, pp. 1532-1555.
Elsevier DOI 1302
Vector pattern; Matrix pattern; Global structure; Local structure; Classifier design; Pattern recognition BibRef

Chen, X.H.[Xiao-Hong], Chen, S.C.[Song-Can], Xue, H.[Hui], Zhou, X.D.[Xu-Dong],
A unified dimensionality reduction framework for semi-paired and semi-supervised multi-view data,
PR(45), No. 5, May 2012, pp. 2005-2018.
Elsevier DOI 1201
Multi-view data; Correlation analysis; Semi-supervised learning; Semi-paired learning; Dimensionality reduction BibRef

Xu, C.[Chang], Tao, D.C.[Da-Cheng], Xu, C.[Chao],
Multi-View Learning With Incomplete Views,
IP(24), No. 12, December 2015, pp. 5812-5825.
IEEE DOI 1512
learning (artificial intelligence) BibRef

Zhu, X.F.[Xiao-Feng], Li, X.L.[Xue-Long], Zhang, S.C.[Shi-Chao],
Block-Row Sparse Multiview Multilabel Learning for Image Classification,
Cyber(46), No. 2, February 2016, pp. 450-461.
IEEE DOI 1601
Multiview, multilabel BibRef

Pang, Y.W.[Yan-Wei], Ma, Z.[Zhao], Yuan, Y.[Yuan], Li, X.L.[Xue-Long], Wang, K.Q.[Kong-Qiao],
Multimodal learning for multi-label image classification,
ICIP11(1797-1800).
IEEE DOI 1201
BibRef

Zhang, Z.Y.[Zhen-Yue], Zhai, Z.[Zheng], Li, L.M.[Li-Min],
Uniform Projection for Multi-View Learning,
PAMI(39), No. 8, August 2017, pp. 1675-1689.
IEEE DOI 1707
Convergence, Distortion measurement, Eigenvalues and eigenfunctions, Kernel, Nonlinear distortion, Optimization, Multi-view learning, clustering, low-dimensional projection, unsupervised learning BibRef

Tao, H.[Hong], Hou, C.P.[Chen-Ping], Nie, F.P.[Fei-Ping], Zhu, J.[Jubo], Yi, D.Y.[Dong-Yun],
Scalable Multi-View Semi-Supervised Classification via Adaptive Regression,
IP(26), No. 9, September 2017, pp. 4283-4296.
IEEE DOI 1708
image classification, learning (artificial intelligence), matrix algebra, minimisation, regression analysis, vectors, MVAR, adaptive optimized weight coefficient, adaptive regression, BibRef

Yang, M.[Muli], Deng, C.[Cheng], Nie, F.P.[Fei-Ping],
Adaptive-weighting discriminative regression for multi-view classification,
PR(88), 2019, pp. 236-245.
Elsevier DOI 1901
Multi-view learning, Supervised learning, Classification BibRef

Zhuge, W.Z.[Wen-Zhang], Luo, T.J.[Ting-Jin], Fan, R.D.[Rui-Dong], Tao, H.[Hong], Hou, C.P.[Chen-Ping], Yi, D.Y.[Dong-Yun],
Absent Multiview Semisupervised Classification,
Cyber(54), No. 3, March 2024, pp. 1708-1721.
IEEE DOI 2402
Task analysis, Representation learning, Optimization, Image retrieval, Fuses, Fans, Data collection, Anchor strategy, semisupervised classification BibRef

Nie, F., Cai, G., Li, J., Li, X.,
Auto-Weighted Multi-View Learning for Image Clustering and Semi-Supervised Classification,
IP(27), No. 3, March 2018, pp. 1501-1511.
IEEE DOI 1801
Clustering algorithms, Clustering methods, Correlation, Kernel, Laplace equations, Manifolds, Tensile stress, Auto-weight learning, semi-supervised classification BibRef

Nie, F., Li, J., Li, X.,
Convex Multiview Semi-Supervised Classification,
IP(26), No. 12, December 2017, pp. 5718-5729.
IEEE DOI 1710
hyperparameter elimination, local-minimum problem, multiview data context, optimization method, Data mining, Optimization methods, Semisupervised learning, BibRef

Zhu, P.F.[Peng-Fei], Hu, Q.[Qi], Hu, Q.H.[Qing-Hua], Zhang, C.Q.[Chang-Qing], Feng, Z.[Zhizhao],
Multi-view label embedding,
PR(84), 2018, pp. 126-135.
Elsevier DOI 1809
Multi-label classification, Multi-view label embedding, Label space dimension reduction BibRef

Huang, L.[Ling], Chao, H.Y.[Hong-Yang], Wang, C.D.[Chang-Dong],
Multi-view intact space clustering,
PR(86), 2019, pp. 344-353.
Elsevier DOI 1811
Multi-view clustering, Latent intact space, View-insufficiency, Representation learning BibRef

Pan, H.[Heng], He, J.R.[Jin-Rong], Ling, Y.[Yu], Ju, L.[Lie], He, G.L.[Guo-Liang],
Graph regularized multiview marginal discriminant projection,
JVCIR(57), 2018, pp. 12-22.
Elsevier DOI 1812
Marginal discriminant projection, Graph Laplacian, Manifold regularization, Multiview learning, Hyperspectral images classification BibRef

Cao, H.L.[Hong-Liu], Bernard, S.[Simon], Sabourin, R.[Robert], Heutte, L.[Laurent],
Random forest dissimilarity based multi-view learning for Radiomics application,
PR(88), 2019, pp. 185-197.
Elsevier DOI 1901
BibRef
Earlier: A1, A2, A4, A3:
Dynamic Voting in Multi-view Learning for Radiomics Applications,
SSSPR18(32-41).
Springer DOI 1810
Radiomics, Dissimilarity space, Random forest, Machine learning, Feature selection, Multi-view learning, High dimension, Low sample size BibRef

Liu, B.[Bo], Jing, L.P.[Li-Ping], Li, J.[Jia], Yu, J.[Jian], Gittens, A.[Alex], Mahoney, M.W.[Michael W.],
Group Collaborative Representation for Image Set Classification,
IJCV(127), No. 2, February 2019, pp. 181-206.
Springer DOI 1902
Recognition from multiple images. BibRef

Aeini, F.[Faraein], Moghadam, A.M.E.[Amir Masoud Eftekhari], Mahmoudi, F.[Fariborz],
A regularized approach for unsupervised multi-view multi-manifold learning,
SIViP(13), No. 2, March 2019, pp. 253-261.
Springer DOI 1904
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

Li, J.X.[Jin-Xing], Zhang, B.[Bob], Lu, G.M.[Guang-Ming], Ren, H.[Hu], Zhang, D.[David],
Visual Classification With Multikernel Shared Gaussian Process Latent Variable Model,
Cyber(49), No. 8, August 2019, pp. 2886-2899.
IEEE DOI 1905
Kernel, Feature extraction, Manifolds, Testing, Visualization, Gaussian processes, Biomedical imaging, Gaussian process (GP), multiview BibRef

Yin, Q.Y.[Qi-Yue], Zhang, J.G.[Jun-Ge], Wu, S.[Shu], Li, H.X.[He-Xi],
Multi-view clustering via joint feature selection and partially constrained cluster label learning,
PR(93), 2019, pp. 380-391.
Elsevier DOI 1906
Multi-view clustering, Feature selection, Prior information, Cluster indicator BibRef

Jia, K., Lin, J., Tan, M., Tao, D.,
Deep Multi-View Learning Using Neuron-Wise Correlation-Maximizing Regularizers,
IP(28), No. 10, October 2019, pp. 5121-5134.
IEEE DOI 1909
Training, Neurons, Task analysis, Correlation, Benchmark testing, Object recognition, Feature extraction, Multi-view learning, canonical correlation analysis BibRef

Liu, X.W.[Xin-Wang], Zhu, X.Z.[Xin-Zhong], Li, M.M.[Miao-Miao], Wang, L.[Lei], Tang, C.[Chang], Yin, J.P.[Jian-Ping], Shen, D.G.[Ding-Gang], Wang, H.M.[Huai-Min], Gao, W.[Wen],
Late Fusion Incomplete Multi-View Clustering,
PAMI(41), No. 10, October 2019, pp. 2410-2423.
IEEE DOI 1909
Kernel, Clustering algorithms, Optimization, Convergence, Partitioning algorithms, Pattern analysis, incomplete kernel learning BibRef

Zhang, C.J.[Chun-Jie], Cheng, J.[Jian], Tian, Q.[Qi],
Unsupervised and Semi-Supervised Image Classification With Weak Semantic Consistency,
MultMed(21), No. 10, October 2019, pp. 2482-2491.
IEEE DOI 1910
image classification, image representation, learning (artificial intelligence), pattern clustering, semantic consistency BibRef

Zhang, C.J.[Chun-Jie], Cheng, J.[Jian], Tian, Q.[Qi],
Multi-View Image Classification With Visual, Semantic and View Consistency,
IP(29), No. 1, 2020, pp. 617-627.
IEEE DOI 1910
image classification, optimisation, visual correlations, semantic correlations, view consistency BibRef

Zhang, C.J.[Chun-Jie], Wang, D.H.[Da-Han],
Exploring the Prediction Consistency of Multiple Views for Transductive Visual Recognition,
SPLetters(28), 2021, pp. 668-672.
IEEE DOI 2104
Visualization, Image recognition, Correlation, Convolutional neural networks, Optimization, Encoding, Semantics, visual recognition BibRef

Zhang, C., Li, Z., Cai, R., Chao, H., Rui, Y.,
Joint Multiview Segmentation and Localization of RGB-D Images Using Depth-Induced Silhouette Consistency,
CVPR16(4031-4039)
IEEE DOI 1612
BibRef

Zhang, X.P.[Xiao-Peng], Yang, Y.[Yang], Xiong, H., Feng, J.S.[Jia-Shi],
PML-LocNet: Improving Object Localization With Prior-Induced Multi-View Learning Network,
IP(29), 2020, pp. 2568-2582.
IEEE DOI 2001
BibRef
Earlier: A1, A2, A4, Only:
ML-LocNet: Improving Object Localization with Multi-view Learning Network,
ECCV18(III: 248-263).
Springer DOI 1810
Training, Optimization, Reliability, Detectors, Noise measurement, Object detection, Image representation, semi-supervised learning BibRef

Yang, L., Shen, C., Hu, Q., Jing, L., Li, Y.,
Adaptive Sample-Level Graph Combination for Partial Multiview Clustering,
IP(29), 2020, pp. 2780-2794.
IEEE DOI 2001
Partial multiview clustering, graph combination, adaptive weights BibRef

Jamshidpour, N.[Nasehe], Safari, A.[Abdolreza], Homayouni, S.[Saeid],
A GA-Based Multi-View, Multi-Learner Active Learning Framework for Hyperspectral Image Classification,
RS(12), No. 2, 2020, pp. xx-yy.
DOI Link 2001
BibRef

Zhang, J., Wang, Z., Li, Y., Wang, S.,
Node-Adaptive Multi-Graph Fusion Using Extreme Value Theory,
SPLetters(27), 2020, pp. 351-355.
IEEE DOI 2004
Multi-view graph fusion, extreme value theory, clustering BibRef

Yuan, J.[Jirui], Gao, K.[Ke], Zhu, P.F.[Peng-Fei], Egiazarian, K.[Karen],
Multi-view predictive latent space learning,
PRL(132), 2020, pp. 56-61.
Elsevier DOI 2005
Multi-view learning, Predictive latent space learning, Unsupervised clustering, Unsupervised dimension reduction BibRef

Li, Y., Lu, T., Li, S.,
Subpixel-Pixel-Superpixel-Based Multiview Active Learning for Hyperspectral Images Classification,
GeoRS(58), No. 7, July 2020, pp. 4976-4988.
IEEE DOI 2006
Training, Labeling, Data mining, Uncertainty, Hyperspectral imaging, Estimation, Feature extraction, Active learning (AL), multiview 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

Wan, J., Zhu, F.,
Cost-Sensitive Canonical Correlation Analysis for Semi-Supervised Multi-View Learning,
SPLetters(27), 2020, pp. 1330-1334.
IEEE DOI 2008
Correlation, Training data, Loss measurement, Optimization, Semantics, Hafnium, Propagation losses, Cost-sensitive learning, multi-view BibRef

Zhao, L.[Liang], Zhao, T.Y.[Tian-Yang], Sun, T.T.[Ting-Ting], Liu, Z.[Zhuo], Chen, Z.K.[Zhi-Kui],
Multi-View Robust Feature Learning for Data Clustering,
SPLetters(27), 2020, pp. 1750-1754.
IEEE DOI 2010
Optimization, Matrix decomposition, Learning systems, Clustering algorithms, Noise measurement, Aerospace electronics, robust feature learning BibRef

Yu, H.[Hong], Xiong, J.[Jing], Zhang, X.X.[Xiao-Xia],
Multi-view clustering by exploring complex mapping relationship between views,
PRL(138), 2020, pp. 230-236.
Elsevier DOI 2010
Multi-view clustering, Complex mapping relationship, Partial multi-view clustering, Non-negative matrix factorization (NMF) BibRef

Deng, S.Y.[Si-Yang], Xia, W.[Wei], Gao, Q.X.[Quan-Xue], Gao, X.B.[Xin-Bo],
Cross-view classification by joint adversarial learning and class-specificity distribution,
PR(110), 2021, pp. 107633.
Elsevier DOI 2011
Cross-view, View consistency, Class-specificity distribution, Adversarial learning 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

Yang, M.[Ming], Luo, Q.L.[Qi-Lun], Li, W.[Wen], Xiao, M.Q.[Ming-Qing],
Multiview Clustering of Images with Tensor Rank Minimization via Nonconvex Approach,
SIIMS(13), No. 4, 2020, pp. 2361-2392.
DOI Link 2012
BibRef

Wang, Q., Ding, Z., Tao, Z., Gao, Q., Fu, Y.,
Generative Partial Multi-View Clustering With Adaptive Fusion and Cycle Consistency,
IP(30), 2021, pp. 1771-1783.
IEEE DOI 2101
Generative adversarial networks, Adaptation models, Visualization, Task analysis, Kernel, Data models, generative adversarial networks BibRef

Luo, J.Q.[Jian-Qiao], Wang, Y.H.[Yi-Han], Ou, Y.[Yang], He, B.[Biao], Li, B.L.[Bai-Lin],
Neighbor-Based Label Distribution Learning to Model Label Ambiguity for Aerial Scene Classification,
RS(13), No. 4, 2021, pp. xx-yy.
DOI Link 2103
BibRef

Liu, J.L.[Jian-Lun], Teng, S.H.[Shao-Hua], Fei, L.K.[Lun-Ke], Zhang, W.[Wei], Fang, X.Z.[Xiao-Zhao], Zhang, Z.X.[Zhu-Xiu], Wu, N.Q.[Nai-Qi],
A novel consensus learning approach to incomplete multi-view clustering,
PR(115), 2021, pp. 107890.
Elsevier DOI 2104
Multi-view clustering, Incomplete multi-view clustering, Consensus representation, Consensus similarity graph BibRef

Li, Z.L.[Zheng-Lai], Tang, C.[Chang], Liu, X.W.[Xin-Wang], Zheng, X.[Xiao], Zhang, W.[Wei], Zhu, E.[En],
Consensus Graph Learning for Multi-View Clustering,
MultMed(24), 2022, pp. 2461-2472.
IEEE DOI 2205
Tensors, Clustering methods, Optimization, Streaming media, Feature extraction, Task analysis, Correlation, weighted tensor nuclear norm BibRef

Jia, X.D.[Xiao-Dong], Jing, X.Y.[Xiao-Yuan], Zhu, X.[Xiaoke], Chen, S.C.[Song-Can], Du, B.[Bo], Cai, Z.Y.[Zi-Yun], He, Z.Y.[Zhen-Yu], Yue, D.[Dong],
Semi-Supervised Multi-View Deep Discriminant Representation Learning,
PAMI(43), No. 7, July 2021, pp. 2496-2509.
IEEE DOI 2106
Redundancy, Feature extraction, Measurement, Machine learning, Taxonomy, Semisupervised learning, density clustering BibRef

Liu, X.W.[Xin-Wang], Li, M.M.[Miao-Miao], Tang, C.[Chang], Xia, J.Y.[Jing-Yuan], Xiong, J.[Jian], Liu, L.[Li], Kloft, M.[Marius], Zhu, E.[En],
Efficient and Effective Regularized Incomplete Multi-View Clustering,
PAMI(43), No. 8, August 2021, pp. 2634-2646.
IEEE DOI 2107
Kernel, Clustering algorithms, Optimization, Complexity theory, Task analysis, Convergence, Pattern analysis, incomplete kernel learning BibRef

Huang, A.[Aiping], Chen, W.L.[Wei-Ling], Zhao, T.S.[Tie-Song], Chen, C.W.[Chang Wen],
Joint Learning of Latent Similarity and Local Embedding for Multi-View Clustering,
IP(30), 2021, pp. 6772-6784.
IEEE DOI 2108
Symmetric matrices, Clustering methods, Robustness, Feature extraction, Manifolds, Laplace equations, Kernel, nuclear norm BibRef

Huang, A.P.[Ai-Ping], Wang, Z.[Zheng], Zheng, Y.N.[Yan-Nan], Zhao, T.S.[Tie-Song], Lin, C.W.[Chia-Wen],
Embedding Regularizer Learning for Multi-View Semi-Supervised Classification,
IP(30), 2021, pp. 6997-7011.
IEEE DOI 2108
Deep learning, Linear regression, Prediction algorithms, Robustness, Classification algorithms, Sparse matrices, embedding regularizer BibRef

Tan, J.P.[Jun-Peng], Shi, Y.[Yukai], Yang, Z.J.[Zhi-Jing], Wen, C.Z.[Cai-Zhen], Lin, L.[Liang],
Unsupervised Multi-View Clustering by Squeezing Hybrid Knowledge From Cross View and Each View,
MultMed(23), 2021, pp. 2943-2956.
IEEE DOI 2109
Sparse matrices, Clustering algorithms, Matrix decomposition, Feature extraction, Data mining, Adaptation models, adaptive graph regularization (AGR) 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

Wang, H.Y.[Hai-Yan], Han, G.Q.[Guo-Qiang], Zhang, B.[Bin], Tao, G.H.[Gui-Hua], Cai, H.M.[Hong-Min],
Multi-View Learning a Decomposable Affinity Matrix via Tensor Self-Representation on Grassmann Manifold,
IP(30), 2021, pp. 8396-8409.
IEEE DOI 2110
Tensors, Manifolds, Task analysis, Matrix decomposition, Sparse matrices, Merging, Clustering methods, Grassmann manifold BibRef

Wang, X.L.[Xiao-Li], Zhu, Z.F.[Zhi-Fan], Song, Y.[Yan], Fu, H.J.[Hai-Juan],
GRNet: Graph-based remodeling network for multi-view semi-supervised classification,
PRL(151), 2021, pp. 95-102.
Elsevier DOI 2110
Multi-view semi-supervised learning, Remodeling network, Consistency and complementation BibRef

Wang, X.L.[Xiao-Li], Fu, L.Y.[Li-Yong], Zhang, Y.D.[Yu-Dong], Wang, Y.L.[Yong-Li], Li, Z.C.[Ze-Chao],
MMatch: Semi-Supervised Discriminative Representation Learning for Multi-View Classification,
CirSysVideo(32), No. 9, September 2022, pp. 6425-6436.
IEEE DOI 2209
Representation learning, Training, Predictive models, Forestry, Feature extraction, Entropy, Task analysis, pseudo-labeling BibRef

Wang, X.L.[Xiao-Li], Wang, Y.L.[Yong-Li], Wang, Y.P.[Yu-Peng], Huang, A.[Anqi], Liu, J.[Jun],
Trusted Semi-Supervised Multi-View Classification with Contrastive Learning,
MultMed(26), 2024, pp. 8268-8278.
IEEE DOI 2408
Uncertainty, Semantics, Self-supervised learning, Deep learning, Ensemble learning, Ions, Estimation, Semi-supervised learning, uncertainty estimation BibRef

Jiang, Y.[Yu], Liu, J.[Jing], Li, Z.C.[Ze-Chao], Lu, H.Q.[Han-Qing],
Semi-Supervised Unified Latent Factor learning with Multi-View Data,
MVA(25), No. 7, October 2014, pp. 1635-1645.
Springer DOI 1410
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

Wang, L.C.[Li-Chen], Liu, Y.Y.[Yun-Yu], Di, H.[Hang], Qin, C.[Can], Sun, G.[Gan], Fu, Y.[Yun],
Semi-Supervised Dual Relation Learning for Multi-Label Classification,
IP(30), 2021, pp. 9125-9135.
IEEE DOI 2112
Semantics, Feature extraction, Correlation, Training, Tensors, Task analysis, Sun, Label relation learning, image annotation BibRef

Liu, Y.Y.[Yun-Yu], Wang, L.C.[Li-Chen], Bai, Y.[Yue], Qin, C.[Can], Ding, Z.M.[Zheng-Ming], Fu, Y.[Yun],
Generative View-Correlation Adaptation for Semi-Supervised Multi-View Learning,
ECCV20(XIV:318-334).
Springer DOI 2011
BibRef

Sun, S.L.[Shi-Liang], Dong, W.B.[Wen-Bo], Liu, Q.Y.[Qiu-Yang],
Multi-View Representation Learning With Deep Gaussian Processes,
PAMI(43), No. 12, December 2021, pp. 4453-4468.
IEEE DOI 2112
Global Positioning System, Gaussian processes, Uncertainty, Data models, Task analysis, Neural networks, Learning systems, representation learning BibRef

Dong, W.B.[Wen-Bo], Sun, S.L.[Shi-Liang],
Multi-View Deep Gaussian Processes for Supervised Learning,
PAMI(45), No. 12, December 2023, pp. 15137-15153.
IEEE DOI 2311
BibRef

Zhang, N.[Nan], Sun, S.L.[Shi-Liang],
Incomplete multiview nonnegative representation learning with multiple graphs,
PR(123), 2022, pp. 108412.
Elsevier DOI 2112
Multiview clustering, Graph learning, Incomplete multiview clustering, Nonnegative matrix factorization BibRef

Yin, J.[Jun], Sun, S.L.[Shi-Liang],
Incomplete multi-view clustering with cosine similarity,
PR(123), 2022, pp. 108371.
Elsevier DOI 2112
Multi-view learning, Missing view, Cosine similarity, Gradient descent, Matrix factorization BibRef

Hu, Y.L.[Yong-Li], Song, Z.[Zuolong], Wang, B.Y.[Bo-Yue], Gao, J.B.[Jun-Bin], Sun, Y.F.[Yan-Feng], Yin, B.C.[Bao-Cai],
AKM3C: Adaptive K-Multiple-Means for Multi-View Clustering,
CirSysVideo(31), No. 11, November 2021, pp. 4214-4226.
IEEE DOI 2112
Clustering methods, Bipartite graph, Kernel, Matrix decomposition, Tensors, Fuses, Adaptation models, Multi-view clustering, K-means, Laplacian rank constraint BibRef

Li, Z.H.[Zi-Heng], Wu, D.Y.[Dan-Yang], Nie, F.P.[Fei-Ping], Wang, R.[Rong], Sun, Z.S.[Zhen-Sheng], Li, X.L.[Xue-Long],
Multi-View Clustering Based on Invisible Weights,
SPLetters(28), 2021, pp. 1051-1055.
IEEE DOI 2106
Computational complexity, Signal processing algorithms, Kernel, Adaptation models, Cybernetics, Speech processing, invisible weights 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

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

Hu, S.Z.[Shi-Zhe], Lou, Z.Z.[Zheng-Zheng], Ye, Y.D.[Yang-Dong],
View-Wise Versus Cluster-Wise Weight: Which Is Better for Multi-View Clustering?,
IP(31), 2022, pp. 58-71.
IEEE DOI 2112
Mutual information, Optimization, Linear programming, Image color analysis, Clustering algorithms, Shape, weight learning BibRef

Li, X.L.[Xue-Long], Zhang, H.[Han], Wang, R.[Rong], Nie, F.P.[Fei-Ping],
Multiview Clustering: A Scalable and Parameter-Free Bipartite Graph Fusion Method,
PAMI(44), No. 1, January 2022, pp. 330-344.
IEEE DOI 2112
Laplace equations, Clustering algorithms, Bipartite graph, Optical imaging, Data models, Computer science, initialization-independent BibRef

Zhang, C.Q.[Chang-Qing], Cui, Y.J.[Ya-Jie], Han, Z.B.[Zong-Bo], Zhou, J.T.Y.[Joey Tian-Yi], Fu, H.Z.[Hua-Zhu], Hu, Q.H.[Qing-Hua],
Deep Partial Multi-View Learning,
PAMI(44), No. 5, May 2022, pp. 2402-2415.
IEEE DOI 2204
Correlation, Encoding, Training, Image reconstruction, Data models, Testing, Neural networks, Multi-view learning, latent representation BibRef

Prasad, S.[Shitala], Li, Y.Q.[Yi-Qun], Lin, D.Y.[Dong-Yun], Dong, S.[Sheng], Nwe, M.T.L.[Ma Tin Lay],
A Progressive Multi-View Learning Approach for Multi-Loss Optimization in 3D Object Recognition,
SPLetters(29), 2022, pp. 707-711.
IEEE DOI 2204
Object recognition, Training, Task analysis, Visualization, Prototypes, Solid modeling, 3D unseen learning, DCNN, self-supervised learning BibRef

Wu, D.Y.[Dan-Yang], Dong, X.[Xia], Nie, F.P.[Fei-Ping], Wang, R.[Rong], Li, X.L.[Xue-Long],
An attention-based framework for multi-view clustering on Grassmann manifold,
PR(128), 2022, pp. 108610.
Elsevier DOI 2205
Multi-view clustering, Grassmann manifold, Principle angles, Attentive weighted-learning scheme BibRef

Yu, X.[Xiao], Liu, H.[Hui], Lin, Y.X.[Yu-Xiu], Wu, Y.[Yan], Zhang, C.M.[Cai-Ming],
Auto-weighted sample-level fusion with anchors for incomplete multi-view clustering,
PR(130), 2022, pp. 108772.
Elsevier DOI 2206
Incomplete data, Multi-view clustering, Anchor, Auto-weighted, Large-scale BibRef

Yu, X.[Xiao], Liu, H.[Hui], Zhang, Y.[Yan], Sun, S.[Shanbao], Zhang, C.M.[Cai-Ming],
Multi-view clustering via efficient representation learning with anchors,
PR(144), 2023, pp. 109860.
Elsevier DOI 2310
Multi-view clustering, Large-scale, Anchor, Representation learning 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

Liu, X.[Xu], Jiao, L.C.[Li-Cheng], Li, L.L.[Ling-Ling], Cheng, L.[Lin], Liu, F.[Fang], Yang, S.Y.[Shu-Yuan], Hou, B.[Biao],
Deep Multiview Union Learning Network for Multisource Image Classification,
Cyber(52), No. 6, June 2022, pp. 4534-4546.
IEEE DOI 2207
Feature extraction, Laser radar, Data mining, Deep learning, Correlation, Imaging, Sensors, Classification, deep learning, multiview learning BibRef

Zheng, Q.H.[Qing-Hai], Zhu, J.[Jihua], Li, Z.Y.[Zhong-Yu],
Collaborative Unsupervised Multi-View Representation Learning,
CirSysVideo(32), No. 7, July 2022, pp. 4202-4210.
IEEE DOI 2207
Correlation, Tensors, Uniform resource locators, Task analysis, Feature extraction, Collaboration, Kernel, Multi-view learning, multi-view representation learning BibRef

Xia, W.[Wei], Wang, Q.Q.[Qian-Qian], Gao, Q.X.[Quan-Xue], Zhang, X.D.[Xiang-Dong], Gao, X.B.[Xin-Bo],
Self-Supervised Graph Convolutional Network for Multi-View Clustering,
MultMed(24), 2022, pp. 3182-3192.
IEEE DOI 2207
Feature extraction, Decoding, Transforms, Task analysis, Clustering methods, Social networking (online), Correlation, self-supervision BibRef

Shu, X.C.[Xiao-Chuang], Zhang, X.D.[Xiang-Dong], Gao, Q.X.[Quan-Xue], Yang, M.[Ming], Wang, R.[Rong], Gao, X.B.[Xin-Bo],
Self-Weighted Anchor Graph Learning for Multi-View Clustering,
MultMed(25), 2023, pp. 5485-5499.
IEEE DOI 2311
BibRef

Li, J.[Jing], Wang, Q.Q.[Qian-Qian], Yang, M.[Ming], Gao, Q.X.[Quan-Xue], Gao, X.B.[Xin-Bo],
Efficient Anchor Graph Factorization for Multi-View Clustering,
MultMed(26), 2024, pp. 5834-5845.
IEEE DOI 2404
Tensors, Matrix decomposition, Computational complexity, Data models, Clustering methods, Clustering algorithms, tensor Schatten p-norm BibRef

Zhao, W.H.[Wen-Hui], Li, Q.[Qin], Xu, H.[Huafu], Gao, Q.X.[Quan-Xue], Wang, Q.Q.[Qian-Qian], Gao, X.B.[Xin-Bo],
Anchor Graph-Based Feature Selection for One-Step Multi-View Clustering,
MultMed(26), 2024, pp. 7413-7425.
IEEE DOI 2405
Sparse matrices, Feature extraction, Tensors, Clustering methods, Clustering algorithms, Noise measurement, Sparse approximation, sparse representation BibRef

Wang, S.P.[Shi-Ping], Chen, Z.L.[Zhao-Liang], Du, S.[Shide], Lin, Z.C.[Zhou-Chen],
Learning Deep Sparse Regularizers With Applications to Multi-View Clustering and Semi-Supervised Classification,
PAMI(44), No. 9, September 2022, pp. 5042-5055.
IEEE DOI 2208
Neural networks, Optimization, Task analysis, Minimization, Deep learning, Compressed sensing, Backpropagation, Deep learning, multi-view learning BibRef

Luong, K.[Khanh], Nayak, R.[Richi], Balasubramaniam, T.[Thirunavukarasu], Bashar, M.A.[Md Abul],
Multi-layer manifold learning for deep non-negative matrix factorization-based multi-view clustering,
PR(131), 2022, pp. 108815.
Elsevier DOI 2208
Multi-view data/clustering, Manifold learning, Non-negative Matrix Factorization (NMF), Deep Non-negative Matrix Factorization (Deep-NMF) BibRef

Huang, S.D.[Shu-Dong], Shi, W.[Wei], Xu, Z.L.[Zeng-Lin], Tsang, I.W.[Ivor W.], Lv, J.C.[Jian-Cheng],
Efficient federated multi-view learning,
PR(131), 2022, pp. 108817.
Elsevier DOI 2208
Federated learning, Multi-view learning, Matrix factorization, Clustering BibRef

Lv, Z.Y.[Zi-Yu], Gao, Q.X.[Quan-Xue], Zhang, X.D.[Xiang-Dong], Li, Q.[Qin], Yang, M.[Ming],
View-Consistency Learning for Incomplete Multiview Clustering,
IP(31), 2022, pp. 4790-4802.
IEEE DOI 2208
Tensors, Clustering algorithms, Matrix decomposition, Cameras, Technological innovation, Representation learning, Optimization, graph learning BibRef

Jiang, G.Q.[Guang-Qi], Peng, J.J.[Jin-Jia], Wang, H.B.[Hui-Bing], Mi, Z.[Zetian], Fu, X.P.[Xian-Ping],
Tensorial Multi-View Clustering via Low-Rank Constrained High-Order Graph Learning,
CirSysVideo(32), No. 8, August 2022, pp. 5307-5318.
IEEE DOI 2208
Tensors, Correlation, Task analysis, Optimization, Clustering algorithms, Redundancy, Laplace equations, multi-view clustering BibRef

Wang, H.[Huibing], Jiang, G.Q.[Guang-Qi], Peng, J.J.[Jin-Jia], Deng, R.X.[Ruo-Xi], Fu, X.P.[Xian-Ping],
Towards Adaptive Consensus Graph: Multi-View Clustering via Graph Collaboration,
MultMed(25), 2023, pp. 6629-6641.
IEEE DOI 2311
BibRef

Li, X.[Xiang], Chen, S.C.[Song-Can],
A Concise Yet Effective Model for Non-Aligned Incomplete Multi-View and Missing Multi-Label Learning,
PAMI(44), No. 10, October 2022, pp. 5918-5932.
IEEE DOI 2209
Learning systems, Fish, Data privacy, Video surveillance, Transforms, Training, Time complexity, Non-aligned incomplete multi-view, model selection BibRef

Yang, B.[Ben], Zhang, X.T.[Xue-Tao], Lin, Z.P.[Zhi-Ping], Nie, F.P.[Fei-Ping], Chen, B.D.[Ba-Dong], Wang, F.[Fei],
Efficient and Robust MultiView Clustering With Anchor Graph Regularization,
CirSysVideo(32), No. 9, September 2022, pp. 6200-6213.
IEEE DOI 2209
Robustness, Clustering methods, Clustering algorithms, Matrix decomposition, Computational complexity, Standards, nonnegative matrix factorization BibRef

Zhong, G.[Guo], Pun, C.M.[Chi-Man],
Improved Normalized Cut for Multi-View Clustering,
PAMI(44), No. 12, December 2022, pp. 10244-10251.
IEEE DOI 2212
Laplace equations, Clustering algorithms, Optimization, Clustering methods, Matrix decomposition, Linear programming, normalized cut BibRef

Wang, Y.L.[Yu-Long], Kou, K.I.[Kit Ian], Chen, H.[Hong], Tang, Y.Y.[Yuan Yan], Li, L.Q.[Luo-Qing],
Simultaneous Robust Matching Pursuit for Multi-View Learning,
PR(134), 2023, pp. 109100.
Elsevier DOI 2212
Greedy algorithm, Multi-view learning, M-estimator, Sparse learning BibRef

Yan, W.Z.[Wen-Zhu], Li, Y.[Yanmeng], Yang, M.[Ming],
Towards deeper match for multi-view oriented multiple kernel learning,
PR(134), 2023, pp. 109119.
Elsevier DOI 2212
Multi-view representation, Deep kernel, Feature fusion, Classification BibRef

Hu, P.[Peng], Peng, X.[Xi], Zhu, H.Y.[Hong-Yuan], Zhen, L.L.[Liang-Li], Lin, J.[Jie], Yan, H.[Huaibai], Peng, D.Z.[De-Zhong],
Deep Semisupervised Multiview Learning With Increasing Views,
Cyber(52), No. 12, December 2022, pp. 12954-12965.
IEEE DOI 2212
Laplace equations, Data models, Training, Semisupervised learning, Correlation, Deep learning, Cross-view retrieval, semisupervised multiview learning BibRef

Hu, P.[Peng], Zhen, L.L.[Liang-Li], Peng, X.[Xi], Zhu, H.Y.[Hong-Yuan], Lin, J.[Jie], Wang, X.[Xu], Peng, D.Z.[De-Zhong],
Deep Supervised Multi-View Learning With Graph Priors,
IP(33), 2024, pp. 123-133.
IEEE DOI 2312
BibRef

Yang, M.X.[Mou-Xing], Li, Y.F.[Yun-Fan], Hu, P.[Peng], Bai, J.F.[Jin-Feng], Lv, J.C.[Jian-Cheng], Peng, X.[Xi],
Robust Multi-View Clustering With Incomplete Information,
PAMI(45), No. 1, January 2023, pp. 1055-1069.
IEEE DOI 2212
Noise measurement, Noise robustness, Robustness, Representation learning, Annotations, Task analysis, Optimization, false negatives BibRef

Zeng, P.X.[Peng-Xin], Yang, M.X.[Mou-Xing], Lu, Y.D.[Yi-Ding], Zhang, C.Q.[Chang-Qing], Hu, P.[Peng], Peng, X.[Xi],
Semantic Invariant Multi-View Clustering With Fully Incomplete Information,
PAMI(46), No. 4, April 2024, pp. 2139-2150.
IEEE DOI 2403
Semantics, Noise measurement, Kernel, Drones, Data collection, Complexity theory, Adversarial machine learning, semantic invariance BibRef

Zhu, Z.R.[Zhao-Rui], Gao, Q.X.[Quan-Xue],
Semi-Supervised Clustering via Cannot Link Relationship for Multiview Data,
CirSysVideo(32), No. 12, December 2022, pp. 8744-8755.
IEEE DOI 2212
Clustering algorithms, Tensors, Unsupervised learning, Semisupervised learning, Supervised learning, Clustering methods, cannot link constraint BibRef

Zheng, Q.H.[Qing-Hai], Zhu, J.[Jihua], Li, Z.Y.[Zhong-Yu], Tang, H.Y.[Hao-Yu],
Graph-Guided Unsupervised Multiview Representation Learning,
CirSysVideo(33), No. 1, January 2023, pp. 146-159.
IEEE DOI 2301
Representation learning, Correlation, Task analysis, Neural networks, Kernel, Fuses, Uncertainty, Multi-view learning, multi-view representation learning BibRef

Wang, Y.M.[Yi-Ming], Chang, D.X.[Dong-Xia], Fu, Z.Q.[Zhi-Qiang], Wen, J.[Jie], Zhao, Y.[Yao],
Incomplete Multiview Clustering via Cross-View Relation Transfer,
CirSysVideo(33), No. 1, January 2023, pp. 367-378.
IEEE DOI 2301
Graph neural networks, Kernel, Training, Clustering methods, Learning systems, Deep learning, Visualization, representation learning BibRef

Qin, Y.L.[Ya-Lan], Qin, C.[Chuan], Zhang, X.P.[Xin-Peng], Qi, D.L.[Dong-Lian], Feng, G.R.[Guo-Rui],
NIM-Nets: Noise-Aware Incomplete Multi-View Learning Networks,
IP(32), 2023, pp. 175-189.
IEEE DOI 2301
Data models, Task analysis, Representation learning, Optimization, Data integrity, Learning systems, Robustness, unified model BibRef

Han, Z.[Zongbo], Zhang, C.Q.[Chang-Qing], Fu, H.Z.[Hua-Zhu], Zhou, J.T.Y.[Joey Tian-Yi],
Trusted Multi-View Classification With Dynamic Evidential Fusion,
PAMI(45), No. 2, February 2023, pp. 2551-2566.
IEEE DOI 2301
Uncertainty, Reliability, Bayes methods, Computational modeling, Estimation, Robustness, Heuristic algorithms, varitional Dirichlet BibRef

Houfar, K.[Khamis], Samai, D.[Djamel], Dornaika, F.[Fadi], Benlamoudi, A.[Azeddine], Bensid, K.[Khaled], Taleb-Ahmed, A.[Abdelmalik],
Automatically weighted binary multi-view clustering via deep initialization (AW-BMVC),
PR(137), 2023, pp. 109281.
Elsevier DOI 2302
Multi-view clustering, Large scale, Anchors, Discrete representation and BD-FFT BibRef

Lin, Y.J.[Yi-Jie], Gou, Y.B.[Yuan-Biao], Liu, X.T.[Xiao-Tian], Bai, J.F.[Jin-Feng], Lv, J.C.[Jian-Cheng], Peng, X.[Xi],
Dual Contrastive Prediction for Incomplete Multi-View Representation Learning,
PAMI(45), No. 4, April 2023, pp. 4447-4461.
IEEE DOI 2303
Task analysis, Representation learning, Mutual information, Entropy, Linear programming, Optimization, Kernel, multi-view representation learning BibRef

Lin, Y.J.[Yi-Jie], Gou, Y.B.[Yuan-Biao], Liu, Z.T.[Zi-Tao], Li, B.Y.[Bo-Yun], Lv, J.C.[Jian-Cheng], Peng, X.[Xi],
COMPLETER: Incomplete Multi-view Clustering via Contrastive Prediction,
CVPR21(11169-11178)
IEEE DOI 2111
Codes, Clustering methods, Entropy, Task analysis, Mutual information BibRef

Xu, J.[Jie], Li, C.[Chao], Peng, L.[Liang], Ren, Y.Z.[Ya-Zhou], Shi, X.S.[Xiao-Shuang], Shen, H.T.[Heng Tao], Zhu, X.F.[Xiao-Feng],
Adaptive Feature Projection With Distribution Alignment for Deep Incomplete Multi-View Clustering,
IP(32), 2023, pp. 1354-1366.
IEEE DOI 2303
Kernel, Representation learning, Tensors, Adaptation models, Optimization, Mutual information, Image reconstruction, deep feature learning BibRef

Xu, J.[Jie], Tang, H.Y.[Hua-Yi], Ren, Y.Z.[Ya-Zhou], Peng, L.[Liang], Zhu, X.F.[Xiao-Feng], He, L.F.[Li-Fang],
Multi-level Feature Learning for Contrastive Multi-view Clustering,
CVPR22(16030-16039)
IEEE DOI 2210
Representation learning, Computational modeling, Semantics, Predictive models, Feature extraction, Data models, Self- semi- meta- unsupervised learning BibRef

Xu, J.[Jie], Ren, Y.Z.[Ya-Zhou], Tang, H.Y.[Hua-Yi], Pu, X.R.[Xiao-Rong], Zhu, X.F.[Xiao-Feng], Zeng, M.[Ming], He, L.F.[Li-Fang],
Multi-VAE: Learning Disentangled View-common and View-peculiar Visual Representations for Multi-view Clustering,
ICCV21(9214-9223)
IEEE DOI 2203
Visualization, Fuses, Gaussian distribution, Complexity theory, Mutual information, Representation learning 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

Wang, Y.M.[Yi-Ming], Chang, D.X.[Dong-Xia], Fu, Z.Q.[Zhi-Qiang], Zhao, Y.[Yao],
Consistent Multiple Graph Embedding for Multi-View Clustering,
MultMed(25), 2023, pp. 1008-1018.
IEEE DOI 2303
Mutual information, Clustering methods, Clustering algorithms, Data models, Task analysis, Laplace equations, Fuses, representation learning BibRef

Guo, W.[Wei], Wang, Z.[Zhe], Du, W.L.[Wen-Li],
Robust semi-supervised multi-view graph learning with sharable and individual structure,
PR(140), 2023, pp. 109565.
Elsevier DOI 2305
Semi-supervised learning, Multi-view learning, Clean data, Manifold structure BibRef

Zhang, J.[Jing], Wei, G.Y.[Gui-Yan], Sun, F.[Fang],
Synthetic multi-view clustering with missing relationships and instances,
IVC(134), 2023, pp. 104669.
Elsevier DOI 2305
Synthetic multi-view data, Multi-view clustering, Auto-encoder, Knowledge distillation BibRef

Luo, D.[Dixin], Xu, H.T.[Hong-Teng], Carin, L.[Lawrence],
Differentiable Hierarchical Optimal Transport for Robust Multi-View Learning,
PAMI(45), No. 6, June 2023, pp. 7293-7307.
IEEE DOI 2305
Learning systems, Task analysis, Hospitals, Data models, Optimization, Diseases, Predictive models, Bi-level optimization, unaligned multi-view data BibRef

Jia, X.D.[Xiao-Dong], Jing, X.Y.[Xiao-Yuan], Sun, Q.X.[Qi-Xing], Chen, S.C.[Song-Can], Du, B.[Bo], Zhang, D.[David],
Human Collective Intelligence Inspired Multi-View Representation Learning: Enabling View Communication by Simulating Human Communication Mechanism,
PAMI(45), No. 6, June 2023, pp. 7412-7429.
IEEE DOI 2305
Decision making, Representation learning, Computational modeling, Information sharing, Collective intelligence, Bioinformatics, view communication BibRef

Pintelas, E.[Emmanuel], Livieris, I.E.[Ioannis E.], Kotsiantis, S.[Sotiris], Pintelas, P.[Panagiotis],
A multi-view-CNN framework for deep representation learning in image classification,
CVIU(232), 2023, pp. 103687.
Elsevier DOI 2305
Transfer learning, Convolutional neural networks, Deep learning, Feature augmentation, Dimensionality reduction, Image classification BibRef

Sun, S.[Shiding], Yu, X.T.[Xiao-Tong], Tian, Y.J.[Ying-Jie],
Multi-view prototype-based disambiguation for partial label learning,
PR(141), 2023, pp. 109625.
Elsevier DOI 2306
Multi-view learning, Partial label learning, Weakly supervised learning BibRef

Fan, R.D.[Rui-Dong], Ouyang, X.[Xiao], Luo, T.J.[Ting-Jin], Hu, D.[Dewen], Hou, C.P.[Chen-Ping],
Incomplete Multi-View Learning Under Label Shift,
IP(32), 2023, pp. 3702-3716.
IEEE DOI 2307
Training, Pulmonary diseases, Kernel, Estimation error, Biomedical imaging, Multilayer perceptrons, Learning systems, reweighting strategy BibRef

Zhang, C.Y.[Chao-Yang], Lou, Z.Z.[Zheng-Zheng], Zhou, Q.L.[Qing-Lei], Hu, S.Z.[Shi-Zhe],
Multi-View Clustering via Triplex Information Maximization,
IP(32), 2023, pp. 4299-4313.
IEEE DOI 2308
Mutual information, Visualization, Data models, Feature extraction, Dictionaries, Correlation, Indexes, Multi-view clustering, visual clustering BibRef

Zhu, P.F.[Peng-Fei], Yao, X.J.[Xin-Jie], Wang, Y.[Yu], Cao, M.[Meng], Hui, B.Y.[Bin-Yuan], Zhao, S.[Shuai], Hu, Q.H.[Qing-Hua],
Latent Heterogeneous Graph Network for Incomplete Multi-View Learning,
MultMed(25), 2023, pp. 3033-3045.
IEEE DOI 2309
BibRef

Wang, Y.[Yu], Yao, X.J.[Xin-Jie], Zhu, P.F.[Peng-Fei], Li, W.H.[Wei-Hao], Cao, M.[Meng], Hu, Q.H.[Qing-Hua],
Integrated Heterogeneous Graph Attention Network for Incomplete Multi-modal Clustering,
IJCV(132), No. 1, January 2024, pp. 3847-3866.
Springer DOI 2409
BibRef

Zhou, Y.[Yuan], Guo, Y.R.[Yan-Rong], Hao, S.J.[Shi-Jie], Hong, R.C.[Ri-Chang], Luo, J.B.[Jie-Bo],
Few-Shot Partial Multi-View Learning,
PAMI(45), No. 10, October 2023, pp. 11824-11841.
IEEE DOI 2310
BibRef

Gao, C.[Chiwei], Xu, Z.W.[Zi-Wei], Chen, X.H.[Xiu-Hong],
Multi-view clustering with Laplacian rank constraint based on symmetric and nonnegative low-rank representation,
CVIU(236), 2023, pp. 103829.
Elsevier DOI 2310
Multi-view clustering, Low-rank representation, Symmetry, Nonnegativeness, Similarity matrix BibRef

Diallo, B.[Bassoma], Hu, J.[Jie], Li, T.R.[Tian-Rui], Khan, G.A.[Ghufran Ahmad], Liang, X.Y.[Xin-Yan], Wang, H.J.[Hong-Jun],
Auto-attention mechanism for multi-view deep embedding clustering,
PR(143), 2023, pp. 109764.
Elsevier DOI 2310
Deep embedding clustering, Deep multi-view clustering, Multi-view autoencoder, Auto-attention BibRef

Deng, J.X.[Jiao-Xue], Lin, Y.F.[You-Fang], Jin, X.[Xiyuan], Ning, X.J.[Xiao-Jun], Wang, J.[Jing],
Multi-View Consistency Contrastive Learning With Hard Positives for Sleep Signals,
SPLetters(30), 2023, pp. 1102-1106.
IEEE DOI 2310
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

Ping, K.[Ke], Li, S.[Shuxiao], Wu, C.H.[Chu-Han], Ren, Z.W.[Zhen-Wen],
Architecture Alternative Deep Multi-View Clustering,
SPLetters(30), 2023, pp. 1547-1551.
IEEE DOI 2311
BibRef

Wang, Y.M.[Yi-Ming], Chang, D.X.[Dong-Xia], Fu, Z.Q.[Zhi-Qiang], Wen, J.[Jie], Zhao, Y.[Yao],
Graph Contrastive Partial Multi-View Clustering,
MultMed(25), 2023, pp. 6551-6562.
IEEE DOI 2311
BibRef

Hao, W.Y.[Wen-Yu], Pang, S.M.[Shan-Min], Bai, X.X.[Xiu-Xiu], Xue, J.R.[Jian-Ru],
Tensor-Based Incomplete Multi-View Clustering With Low-Rank Data Reconstruction and Consistency Guidance,
CirSysVideo(33), No. 12, December 2023, pp. 7156-7169.
IEEE DOI 2312
BibRef

Chen, J.[Jin], Huang, A.[Aiping], Gao, W.[Wei], Niu, Y.Z.[Yu-Zhen], Zhao, T.S.[Tie-Song],
Joint Shared-and-Specific Information for Deep Multi-View Clustering,
CirSysVideo(33), No. 12, December 2023, pp. 7224-7235.
IEEE DOI 2312
BibRef

Dong, Z.B.[Zhi-Bin], Wang, S.W.[Si-Wei], Jin, J.Q.[Jia-Qi], Liu, X.W.[Xin-Wang], Zhu, E.[En],
Cross-view Topology Based Consistent and Complementary Information for Deep Multi-view Clustering,
ICCV23(19383-19394)
IEEE DOI 2401
BibRef

Bi, X.A.[Xia-An], Huang, Y.J.[Yang-Jun], Yang, Z.C.[Zi-Cheng], Chen, K.[Ke], Xing, Z.X.[Zhao-Xu], Xu, L.Y.[Lu-Yun], Li, X.[Xiang], Liu, Z.L.[Zheng-Liang], Liu, T.M.[Tian-Ming],
Structure Mapping Generative Adversarial Network for Multi-View Information Mapping Pattern Mining,
PAMI(46), No. 4, April 2024, pp. 2252-2266.
IEEE DOI 2403
Generative adversarial networks, Deep learning, Data models, Data mining, Training, Task analysis, Predictive models BibRef

Zhou, W.X.[Wei-Xun], Shi, Y.X.[Yong-Xin], Huang, X.[Xiao],
Multi-View Scene Classification Based on Feature Integration and Evidence Decision Fusion,
RS(16), No. 5, 2024, pp. 738.
DOI Link 2403
BibRef

Zeng, X.H.[Xian-Hua], Guo, J.[Jueqiu], Wei, Y.F.[Yi-Fan], Zhuo, Y.[Yang],
Deep hybrid manifold for image set classification,
IVC(143), 2024, pp. 104935.
Elsevier DOI 2403
The image set data is modeled through SPD manifold and Grassmann manifold. The modeled data is input into the backbone network composed of SPDNet and GrNet for initial feature extraction, and the output manifold data are input into HMAEs. SPD manifold, Grassmann manifold, Visual classification, Hybrid manifold, Neural network BibRef

Cai, H.M.[Hong-Min], Huang, W.T.[Wei-Tian], Yang, S.[Sirui], Ding, S.Q.[Si-Qi], Zhang, Y.[Yue], Hu, B.[Bin], Zhang, F.[Fa], Cheung, Y.M.[Yiu-Ming],
Realize Generative Yet Complete Latent Representation for Incomplete Multi-View Learning,
PAMI(46), No. 5, May 2024, pp. 3637-3652.
IEEE DOI 2404
Representation learning, Correlation, Task analysis, Data models, Computational modeling, Gaussian distribution, Computer science, representation learning BibRef

Zhao, X.J.[Xiao-Jia], Shen, Q.Q.[Qiang-Qiang], Chen, Y.Y.[Yong-Yong], Liang, Y.S.[Yong-Sheng], Chen, J.X.[Jun-Xin], Zhou, Y.C.[Yi-Cong],
Self-Completed Bipartite Graph Learning for Fast Incomplete Multi-View Clustering,
CirSysVideo(34), No. 4, April 2024, pp. 2166-2178.
IEEE DOI 2404
Bipartite graph, Kernel, Correlation, Task analysis, Optimization, Excavation, Time complexity, Incomplete multi-view clustering, graph self-completion BibRef

Hu, Y.[Yutao], Wang, Y.L.[Yu-Long], Li, H.[Han], Chen, H.[Hong],
Robust multi-view learning via M-estimator joint sparse representation,
PR(151), 2024, pp. 110355.
Elsevier DOI Code:
WWW Link. 2404
Robust multi-view learning, Joint sparse representation, M-estimator BibRef

Cai, R.G.[Rong-Gang], Chen, H.M.[Hong-Mei], Mi, Y.[Yong], Luo, C.[Chuan], Horng, S.J.[Shi-Jinn], Li, T.R.[Tian-Rui],
Multi-view clustering via pseudo-label guide learning and latent graph structure recovery,
PR(151), 2024, pp. 110420.
Elsevier DOI 2404
Multi-view clustering, Latent space, Pseudo-label, Latent graph structure recovery, Enhanced label fusion BibRef

Ke, G.Z.[Guan-Zhou], Chao, G.Q.[Guo-Qing], Wang, X.L.[Xiao-Li], Xu, C.Y.[Chen-Yang], Zhu, Y.Q.[Yong-Qi], Yu, Y.[Yang],
A Clustering-Guided Contrastive Fusion for Multi-View Representation Learning,
CirSysVideo(34), No. 4, April 2024, pp. 2056-2069.
IEEE DOI Code:
WWW Link. 2404
Task analysis, Semantics, Robustness, Representation learning, Image reconstruction, Data models, Learning systems, incomplete view BibRef

Xiao, Y.S.[Yan-Shan], Zhang, J.W.[Jian-Wei], Liu, B.[Bo], Zhao, L.[Liang], Kong, X.J.[Xiang-Jun], Hao, Z.F.[Zhi-Feng],
Multi-View Maximum Margin Clustering With Privileged Information Learning,
CirSysVideo(34), No. 4, April 2024, pp. 2719-2733.
IEEE DOI 2404
Clustering methods, Training, Feature extraction, Kernel, Deep learning, Task analysis, Integrated circuit modeling, cutting plane BibRef

Liu, B.[Bo], Sun, P.[Peng], Xiao, Y.[Yanshan], Zhao, S.L.[Shi-Lei], Li, X.K.[Xiao-Kai], Peng, T.T.[Tian-Tian], Zheng, Z.[Zhiyu], Huang, Y.S.[Yong-Sheng],
Dictionary-Based Multi-View Learning With Privileged Information,
CirSysVideo(34), No. 5, May 2024, pp. 3523-3537.
IEEE DOI 2405
Dictionaries, Machine learning, Sparse matrices, Redundancy, Clustering methods, Feature extraction, Multi-view learning, sparse representation 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

Yu, S.J.[Sheng-Ju], Wang, S.W.[Si-Wei], Wen, Y.[Yi], Wang, Z.M.[Zi-Ming], Luo, Z.G.[Zhi-Gang], Zhu, E.[En], Liu, X.W.[Xin-Wang],
How to Construct Corresponding Anchors for Incomplete Multiview Clustering,
CirSysVideo(34), No. 4, April 2024, pp. 2845-2860.
IEEE DOI 2404
Bipartite graph, Clustering algorithms, Transforms, Task analysis, Kernel, Complexity theory, Neural networks, multiview learning BibRef

Wan, X.H.[Xin-Hang], Xiao, B.[Bin], Liu, X.W.[Xin-Wang], Liu, J.Y.[Ji-Yuan], Liang, W.X.[Wei-Xuan], Zhu, E.[En],
Fast Continual Multi-View Clustering With Incomplete Views,
IP(33), 2024, pp. 2995-3008.
IEEE DOI Code:
WWW Link. 2405
Complexity theory, Kernel, Task analysis, Clustering algorithms, Real-time systems, Privacy, Fuses, Multi-view learning, clustering, continual learning BibRef

Jin, J.Q.[Jia-Qi], Wang, S.W.[Si-Wei], Dong, Z.B.[Zhi-Bin], Liu, X.W.[Xin-Wang], Zhu, E.[En],
Deep Incomplete Multi-View Clustering with Cross-View Partial Sample and Prototype Alignment,
CVPR23(11600-11609)
IEEE DOI 2309
BibRef

Wen, J.[Jie], Xu, G.[Gehui], Tang, Z.[Zhanyan], Wang, W.[Wei], Fei, L.[Lunke], Xu, Y.[Yong],
Graph Regularized and Feature Aware Matrix Factorization for Robust Incomplete Multi-View Clustering,
CirSysVideo(34), No. 5, May 2024, pp. 3728-3741.
IEEE DOI 2405
Task analysis, Data models, Representation learning, Adaptation models, Kernel, Optimization, Noise measurement, multi-view learning BibRef

Du, S.[Shide], Cai, Z.L.[Zhi-Ling], Wu, Z.H.[Zhi-Hao], Pi, Y.Y.[Yue-Yang], Wang, S.P.[Shi-Ping],
UMCGL: Universal Multi-View Consensus Graph Learning With Consistency and Diversity,
IP(33), 2024, pp. 3399-3412.
IEEE DOI 2406
Semantics, Noise, Representation learning, Generators, Training, Task analysis, Noise measurement, Multi-view learning, consistency and diversity BibRef

Fang, Z.[Zihan], Du, S.[Shide], Cai, Z.L.[Zhi-Ling], Lan, S.Y.[Shi-Yang], Wu, C.M.[Chun-Ming], Tan, Y.C.[Yan-Chao], Wang, S.P.[Shi-Ping],
Representation Learning Meets Optimization-Derived Networks: From Single-View to Multi-View,
MultMed(26), 2024, pp. 8889-8901.
IEEE DOI 2408
To learn extensible models. Representation learning, Optimization, Task analysis, Training, Feature extraction, Linear programming, Guidelines, representation learning BibRef

Cui, J.R.[Jin-Rong], Li, Y.T.[Yu-Ting], Huang, H.[Han], Wen, J.[Jie],
Dual Contrast-Driven Deep Multi-View Clustering,
IP(33), 2024, pp. 4753-4764.
IEEE DOI Code:
WWW Link. 2409
Feature extraction, Contrastive learning, Reliability, Clustering methods, Task analysis, Data mining, contrastive 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

Zhan, S.[Senwen], Jiang, H.[Hao], Shen, D.[Dong],
Co-regularized optimal high-order graph embedding for multi-view clustering,
PR(157), 2025, pp. 110892.
Elsevier DOI 2409
Multi-view, Graph embedding, Second-order Laplacian matrix, Co-regularization BibRef

Lin, F.F.[Fang-Fei], Bai, B.[Bing], Guo, Y.W.[Yi-Wen], Chen, H.[Hao], Ren, Y.Z.[Ya-Zhou], Xu, Z.L.[Zeng-Lin],
MHCN: A Hyperbolic Neural Network Model for Multi-view Hierarchical Clustering,
ICCV23(16479-16489)
IEEE DOI 2401
BibRef

Tan, Y.Z.[Yu-Ze], Liu, Y.X.[Yi-Xi], Huang, S.D.[Shu-Dong], Feng, W.T.[Wen-Tao], Lv, J.C.[Jian-Cheng],
Sample-level Multi-view Graph Clustering,
CVPR23(23966-23975)
IEEE DOI 2309
BibRef

Yan, W.Q.[Wei-Qing], Zhang, Y.Y.[Yuan-Yang], Lv, C.[Chenlei], Tang, C.[Chang], Yue, G.H.[Guang-Hui], Liao, L.[Liang], Lin, W.S.[Wei-Si],
GCFAgg: Global and Cross-View Feature Aggregation for Multi-View Clustering,
CVPR23(19863-19872)
IEEE DOI 2309
BibRef

Xie, M.Y.[Meng-Yao], Han, Z.[Zongbo], Zhang, C.Q.[Chang-Qing], Bai, Y.C.[Yi-Chen], Hu, Q.H.[Qing-Hua],
Exploring and Exploiting Uncertainty for Incomplete Multi-View Classification,
CVPR23(19873-19882)
IEEE DOI 2309
BibRef

Trosten, D.J.[Daniel J.], Løkse, S.[Sigurd], Jenssen, R.[Robert], Kampffmeyer, M.C.[Michael C.],
On the Effects of Self-supervision and Contrastive Alignment in Deep Multi-view Clustering,
CVPR23(23976-23985)
IEEE DOI 2309
BibRef

Xu, H.Q.[Hao-Qi], Hou, J.[Jian], Yuan, H.Q.[Hua-Qiang],
Weighted Multi-view Clustering Based on Internal Evaluation,
MMMod23(II: 215-227).
Springer DOI 2304
BibRef

Liu, X.B.[Xiao-Bo], Long, Y.[Yin], Nomikos, Y.F.[Yi-Fannis],
Spectral Embedding and Novel Low-rank Approximation Based Multi-view Clustering,
ICPR22(840-846)
IEEE DOI 2212
Periodic structures BibRef

Ebrahimi, A.[Abdolghani], Stec, A.[Alexander], Klabjan, D.[Diego], Utke, J.[Jean],
Nested Multi-view Image Classification,
ICPR22(5125-5131)
IEEE DOI 2212
Training, Training data, Distance measurement, Convolutional neural networks, Task analysis, Standards, neural network BibRef

Yuan, Y.H.[Yun-Hao], Lil, J.[Jin], Lil, Y.[Yun], Qiang, J.P.[Ji-Peng], Zhu, Y.[Yi], Shen, X.B.[Xiao-Bo], Gou, J.P.[Jian-Ping],
Learning Canonical F-Correlation Projection for Compact Multiview Representation,
CVPR22(19238-19247)
IEEE DOI 2210
Representation learning, Correlation, Linearity, Benchmark testing, Pattern recognition, Iterative methods, Representation learning, Self- semi- meta- Statistical methods BibRef

Liu, J.J.[Jun-Jie], Liu, J.L.[Jun-Long], Yan, S.T.[Shao-Tian], Jiang, R.X.[Rong-Xin], Tian, X.[Xiang], Gu, B.X.[Bo-Xuan], Chen, Y.W.[Yao-Wu], Shen, C.[Chen], Huang, J.Q.[Jian-Qiang],
MPC: Multi-view Probabilistic Clustering,
CVPR22(9499-9508)
IEEE DOI 2210
Transforms, Benchmark testing, Probabilistic logic, Robustness, Pattern recognition, Recognition: detection, categorization, retrieval BibRef

Tang, H.Y.[Hua-Yi], Liu, Y.[Yong],
Deep Safe Multi-view Clustering: Reducing the Risk of Clustering Performance Degradation Caused by View Increase,
CVPR22(202-211)
IEEE DOI 2210
Degradation, Deep learning, Computational modeling, Feature extraction, Robustness, Data models, Machine learning, Self- semi- meta- unsupervised learning BibRef

Do, K.[Kien], Tran, T.[Truyen], Venkatesh, S.[Svetha],
Clustering by Maximizing Mutual Information Across Views,
ICCV21(9908-9918)
IEEE DOI 2203
Representation learning, Head, Clustering methods, Object detection, Semisupervised learning, Data mining, Machine learning architectures and formulations BibRef

Xiong, B.[Bo], Fan, H.Q.[Hao-Qi], Grauman, K.[Kristen], Feichtenhofer, C.[Christoph],
Multiview Pseudo-Labeling for Semi-supervised Learning from Video,
ICCV21(7189-7199)
IEEE DOI 2203
Representation learning, Computational modeling, Semisupervised learning, Benchmark testing, Reliability, Standards, Transfer/Low-shot/Semi/Unsupervised Learning BibRef

Wang, S.W.[Si-Wei], Liu, X.W.[Xin-Wang], Liu, L.[Li], Tu, W.X.[Wen-Xuan], Zhu, X.Z.[Xin-Zhong], Liu, J.Y.[Ji-Yuan], Zhou, S.[Sihang], Zhu, E.[En],
Highly-efficient Incomplete Largescale Multiview Clustering with Consensus Bipartite Graph,
CVPR22(9766-9775)
IEEE DOI 2210
Codes, Clustering algorithms, Manuals, Machine learning, Benchmark testing, Bipartite graph, Self- semi- meta- Machine learning BibRef

Liu, J.Y.[Ji-Yuan], Liu, X.W.[Xin-Wang], Yang, Y.X.[Yue-Xiang], Liu, L.[Li], Wang, S.Q.[Si-Qi], Liang, W.X.[Wei-Xuan], Shi, J.Y.[Jiang-Yong],
One-pass Multi-view Clustering for Large-scale Data,
ICCV21(12324-12333)
IEEE DOI 2203
Clustering algorithms, Benchmark testing, Partitioning algorithms, Complexity theory, Matrix decomposition, Vision + other modalities BibRef

Jarraya, M.[Mahmoud], Marwani, M.[Maher], Aversano, G.[Gianmarco], Lahouli, I.[Ichraf], Skhiri, S.[Sabri],
AMI-Class: Towards a Fully Automated Multi-View Image Classifier,
CAIP21(II:36-45).
Springer DOI 2112
BibRef

Trosten, D.J.[Daniel J.], Løkse, S.[Sigurd], Jenssen, R.[Robert], Kampffmeyer, M.[Michael],
Reconsidering Representation Alignment for Multi-view Clustering,
CVPR21(1255-1265)
IEEE DOI 2111
Computational modeling, Adversarial machine learning, Pattern recognition BibRef

Wang, Z.[Zhan], Wang, L.Z.[Li-Zhi], Zhang, L.[Lei], Huang, H.[Hua],
Embedding shared low-rank and feature correlation for multi-view data analysis,
ICPR21(1686-1693)
IEEE DOI 2105
Learning systems, Analytical models, Correlation, Data analysis, Redundancy, Data models BibRef

Cao, H.[Hongliu], Bernard, S.[Simon], Sabourin, R.[Robert], Heutte, L.[Laurent],
A Novel Random Forest Dissimilarity Measure for Multi-View Learning,
ICPR21(1344-1351)
IEEE DOI 2105
Radio frequency, Training, Learning systems, Vegetation, Size measurement, Proposals, High Dimension Low Sample Size BibRef

Jenni, S.[Simon], Favaro, P.[Paolo],
Self-supervised Multi-view Synchronization Learning for 3d Pose Estimation,
ACCV20(V:170-187).
Springer DOI 2103
BibRef

Ho, C.H.[Chih-Hui], Liu, B.[Bo], Wu, T.Y.[Tz-Ying], Vasconcelos, N.M.[Nuno M.],
Exploit Clues From Views: Self-Supervised and Regularized Learning for Multiview Object Recognition,
CVPR20(9087-9097)
IEEE DOI 2008
Task analysis, Training, Prototypes, Object recognition, Robots, Image color analysis 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

Hu, H.T.[Heng-Tong], Hong, R.C.[Ri-Chang], Fu, W.J.[Wei-Jie], Wang, M.[Meng],
Efficient Graph Based Multi-view Learning,
MMMod19(I:691-703).
Springer DOI 1901
BibRef

Zou, P., Li, F., Zhang, L.,
Nonnegative and Adaptive Multi-view Clustering,
ICPR18(1247-1252)
IEEE DOI 1812
Optimization, Linear programming, Adaptation models, Clustering algorithms, Laplace equations, Clustering methods, adaptive neighborhood BibRef

Fang, Z.[Zheng], Zhou, S.[Sen], Li, J.[Jing],
Multi-View Autoencoder for Image Feature Learning with Structured Nonnegative Low Rank,
ICIP18(4033-4037)
IEEE DOI 1809
Linear programming, Optimization, Measurement, Learning systems, Task analysis, Decoding, Robustness, multi-view, feature learning, consensus representation BibRef

Liu, Y., Li, Y., Yuan, Y.,
A Complete Canonical Correlation Analysis for Multiview Learning,
ICIP18(3254-3258)
IEEE DOI 1809
Correlation, Machine learning, Kernel, Optimization, Eigenvalues and eigenfunctions, Learning systems, feature representations BibRef

Lemsara, A., Ouadfel, S., Batouche, M.,
Multi-view clustering with local refinement for cancer patient stratification,
ISCV17(1-5)
IEEE DOI 1710
Cancer, DNA, Genomics, Kernel, BibRef

Ye, T.Q.[Teng-Qi], Wang, T.C.[Tian-Chun], McGuinness, K.[Kevin], Guo, Y.[Yu], Gurrin, C.[Cathal],
Learning Multiple Views with Orthogonal Denoising Autoencoders,
MMMod16(I: 313-324).
Springer DOI 1601
BibRef

Feng, Y.[Yinfu], Xiao, J.[Jun], Zhuang, Y.T.[Yue-Ting], Liu, X.M.[Xiao-Ming],
Adaptive Unsupervised Multi-view Feature Selection for Visual Concept Recognition,
ACCV12(I:343-357).
Springer DOI 1304
BibRef

Danielsson, O.[Oscar], Carlsson, S.[Stefan],
Projectable classifiers for multi-view object class recognition,
3DRR11(577-584).
IEEE DOI 1201
BibRef

Danielsson, O.[Oscar], Rasolzadeh, B.[Babak], Carlsson, S.[Stefan],
Gated classifiers: Boosting under high intra-class variation,
CVPR11(2673-2680).
IEEE DOI 1106
BibRef

Mirzaei, H.[Hamidreza],
A Novel Multi-view Agglomerative Clustering Algorithm Based on Ensemble of Partitions on Different Views,
ICPR10(1007-1010).
IEEE DOI 1008
BibRef

Fan, Z.G.[Zhi-Gang], Lu, B.L.[Bao-Liang],
Fast Recognition of Multi-View Faces with Feature Selection,
ICCV05(I: 76-81).
IEEE DOI 0510
SVM based face recognition. BibRef

Thirion, E., Quan, L.,
Geometrical Learning from Multiple Stereo Views Through Monocular Based Feature Grouping,
ICCV90(481-484).
IEEE DOI BibRef 9000

Chapter on Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms continues in
Multi-View Learning, Co-Clustering .