14.1.4.8 Multi-View Learning, Transfer from Other View

Chapter Contents (Back)
Multi-View Learning.

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., Li, X., Zhang, S.,
Block-Row Sparse Multiview Multilabel Learning for Image Classification,
Cyber(46), No. 2, February 2016, pp. 450-461.
IEEE DOI 1601
Multiview, multilabel 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., Hou, C., Nie, F., Zhu, J., Yi, D.,
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

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

Cheng, M., Jing, L., Ng, M.K.,
Tensor-Based Low-Dimensional Representation Learning for Multi-View Clustering,
IP(28), No. 5, May 2019, pp. 2399-2414.
IEEE DOI 1903
learning (artificial intelligence), matrix decomposition, pattern clustering, tensors, tensor decomposition 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.[Qiyue], Zhang, J.[Junge], Wu, S.[Shu], Li, H.[Hexi],
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


Hu, H.T.[Heng-Tong], Hong, R.[Richang], Fu, W.[Weijie], 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

Zhang, X.P.[Xiao-Peng], Yang, Y.[Yang], Feng, J.[Jiashi],
ML-LocNet: Improving Object Localization with Multi-view Learning Network,
ECCV18(III: 248-263).
Springer DOI 1810
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

Davis, R.I.A., Lovell, B.C., Caelli, T.M.,
Improved estimation of hidden Markov model parameters from multiple observation sequences,
ICPR02(II: 168-171).
IEEE DOI 0211
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-Label Classification, Multilabel Classification .


Last update:Jun 13, 2019 at 09:53:00