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Dimensionality reduction
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Dimensionality reduction
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convex programming
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data visualisation, feature extraction, image representation,
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Machine learning, Semi-supervised learning, Active learning,
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Dimensionality reduction,
Semi-supervised discriminant analysis, Incremental learning,
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Chen, H.[Hong],
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Wang, R.[Rong],
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2112
Principal component analysis, Manifolds, Manifold learning,
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Guo, W.[Weili],
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Tang, Y.Y.[Yuan-Yan],
Tao, D.C.[Da-Cheng],
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2203
Dimensionality reduction, Correlation, Memory management,
Prediction algorithms, Optimization, Training, Data models,
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2205
Fuzzy rough set theory, Unsupervised attribute reduction,
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Long, J.[Jiang],
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2208
Dimensionality reduction, Feature extraction, Graph embedding,
Unsupervised learning
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Wang, J.[Jikui],
Wu, Y.[Yiwen],
Li, B.[Bing],
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WWW Link.
2311
Dimensionality reduction, Principal component analysis,
Anchor graph, Unsupervised learning
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Wang, Q.[Quan],
Wang, F.[Fei],
Li, Z.H.[Zhong-Heng],
Wang, Z.[Zheng],
Nie, F.P.[Fei-Ping],
Coordinate Descent Optimized Trace Difference Model for Joint
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Elsevier DOI
2311
Clustering, Coordinate descent method, Feature extraction,
Trace difference criterion, Unsupervised learning
BibRef
Yang, Q.W.[Qian-Wen],
Sun, F.C.[Fu-Chun],
Unsupervised Local Linear Preserving Manifold Reduction with
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1711
Manifold learning.
BibRef
Wang, Y.M.[Ya-Ming],
Morariu, V.I.[Vlad I.],
Davis, L.S.[Larry S.],
Unsupervised Feature Extraction Inspired by Latent Low-Rank
Representation,
WACV15(542-549)
IEEE DOI
1503
Algorithm design and analysis
BibRef
Morariu, V.I.[Vlad I.],
Ahmed, E.[Ejaz],
Santhanam, V.[Venkataraman],
Harwood, D.[David],
Davis, L.S.[Larry S.],
Composite Discriminant Factor analysis,
WACV14(564-571)
IEEE DOI
1406
Accuracy
BibRef
Carreira-Perpinan, M.A.[Miguel A.],
Lu, Z.D.[Zheng-Dong],
Parametric dimensionality reduction by unsupervised regression,
CVPR10(1895-1902).
IEEE DOI
1006
BibRef
Earlier:
Dimensionality reduction by unsupervised regression,
CVPR08(1-8).
IEEE DOI
0806
BibRef
Yang, W.[Wuyi],
Zhang, S.W.[Shu-Wu],
Liang, W.[Wei],
A Graph Based Subspace Semi-supervised Learning Framework for
Dimensionality Reduction,
ECCV08(II: 664-677).
Springer DOI
0810
BibRef
Gong, H.F.[Hai-Feng],
Pan, C.H.[Chun-Hong],
Yang, Q.[Qing],
Lu, H.Q.[Han-Qing],
Ma, S.D.[Song-De],
Neural Network Modeling of Spectral Embedding,
BMVC06(I:227).
PDF File.
0609
BibRef
Earlier:
A Semi-Supervised Framework for Mapping Data to the Intrinsic Manifold,
ICCV05(I: 98-105).
IEEE DOI
0510
Reduce dimensionality, but to the intrinsic form.
BibRef
Chapter on Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms continues in
Riemannian Manifold Learning, Clustering .