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PR(38), No. 10, October 2005, pp. 1764-1767.
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0508
BibRef
Earlier:
Incremental Locally Linear Embedding Algorithm,
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Springer DOI
0506
BibRef
Hadid, A.,
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Unsupervised Learning Using Locally Linear Embedding:
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Elsevier DOI Nonlinear dimensionality reduction; Manifold learning;
Locally linear embedding; Principal component analysis; Outlier;
Robust statistics; M-estimation;
Handwritten digit; Wood texture
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Nonlinear dimensionality reduction, Manifold learning, Feature
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To overcome outlier problems in linear embedded classification.
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MVA(21), No. 3, April 2010, pp. xx-yy.
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Learning to discover neighborhood relationships.
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Dimensionality reduction, Manifold learning, Locally linear embedding;
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Automatic configuration of spectral dimensionality reduction methods,
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Elsevier DOI
1008
Dimensionality reduction, Locally Linear Embedding, Isomap, Laplacian
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Manifold learning, Dimensionality reduction, Weight vector, Stability
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Elsevier DOI
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Locally linear embedding, Localization, Nyström method,
Received signal strength indicator, Manifold learning
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Alipanahi, B.[Babak],
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Guided Locally Linear Embedding,
PRL(32), No. 7, 1 May 2011, pp. 1029-1035.
Elsevier DOI
1101
Supervised dimensionality reduction; Locally Linear Embedding;
Classification; Pattern recognition
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Wang, R.P.[Rui-Ping],
Shan, S.G.[Shi-Guang],
Chen, X.L.[Xi-Lin],
Chen, J.[Jie],
Gao, W.[Wen],
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1109
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IEEE DOI
1712
BibRef
Earlier:
Nonlinear Embedding Transform for Unsupervised Domain Adaptation,
TASKCV16(III: 451-457).
Springer DOI
1611
Adaptation models, Data models, Knowledge transfer,
Machine learning, Training data
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Sun, W.W.[Wei-Wei],
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A Sparse and Low-Rank Near-Isometric Linear Embedding Method for
Feature Extraction in Hyperspectral Imagery Classification,
GeoRS(55), No. 7, July 2017, pp. 4032-4046.
IEEE DOI
1706
Feature extraction, Hyperspectral imaging, Learning systems,
Manifolds, Principal component analysis, Sparse matrices,
Classification, dimensionality reduction, feature extraction,
linear, embedding, (SLRNILE)
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Jorge, J.[Javier],
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Passive-Aggressive online learning with nonlinear embeddings,
PR(79), 2018, pp. 162-171.
Elsevier DOI
1804
Online learning, Nonlinear functions, Passive-Aggressive,
Binary classification, Nonlinear embedding
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Zhang, Y.[Yan],
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PR(76), No. 1, 2018, pp. 662-678.
Elsevier DOI
1801
Semi-supervised manifold feature extraction
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Zhu, R.F.[Rui-Feng],
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PR(93), 2019, pp. 458-469.
Elsevier DOI
1906
BibRef
Earlier:
Flexible and Discriminative Non-linear Embedding with Feature
Selection for Image Classification,
ICPR18(3192-3197)
IEEE DOI
1812
Graph-based embedding, Discriminative embedding,
Feature weighting, Supervised learning.
Symmetric matrices, Feature extraction, Sparse matrices, Manifolds,
Transforms, Laplace equations, Estimation,
feature selection
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Örnek, C.[Cem],
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PR(87), 2019, pp. 55-66.
Elsevier DOI
1812
Manifold learning, Dimensionality reduction,
Supervised learning, Out-of-sample, Nonlinear embeddings
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PRL(123), 2019, pp. 47-52.
Elsevier DOI
1906
Cross validation, Dimension reduction, Regularization
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Niu, G.[Guo],
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Tensor local linear embedding with global subspace projection
optimisation,
IET-CV(16), No. 3, 2022, pp. 241-254.
DOI Link
2204
Tensor dimensionality reduction.
local linear embedding, subspace projection,
tensor dimensionality reduction, tensors
BibRef
Miao, J.Y.[Jian-Yu],
Yang, T.J.[Tie-Jun],
Sun, L.J.[Li-Jun],
Fei, X.[Xuan],
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Shi, Y.[Yong],
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selection,
PR(122), 2022, pp. 108299.
Elsevier DOI
2112
Unsupervised feature selection, Local linear embedding,
Graph Laplacian, Manifold regularization
BibRef
Xue, J.Q.[Jia-Qi],
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Local Linear Embedding with Adaptive Neighbors,
PR(136), 2023, pp. 109205.
Elsevier DOI
2301
dimensionality reduction, Locally Linear Embedding,
manifold learning, adaptive neighbor strategy
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CVPR12(3053-3060).
IEEE DOI
1208
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Semi-supervised learning by locally linear embedding in kernel space,
ICPR08(1-4).
IEEE DOI
0812
BibRef
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Nonlinear Embedded Map Projection for Dimensionality Reduction,
CIAP09(219-228).
Springer DOI
0909
BibRef
Earlier:
Embedded Map Projection for Dimensionality Reduction-Based Similarity
Search,
SSPR08(582-591).
Springer DOI
0812
BibRef
Hui, K.H.[Kang-Hua],
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ICPR08(1-4).
IEEE DOI
0812
LLE for dimensionality reduction
BibRef
Chapter on Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms continues in
Discriminant Analysis .