14.1.4.7 Locally Linear Embedding, Nonlinear Embedding

Chapter Contents (Back)
Locally Linear Embedding. Linear Embedding.

Roweis, S.T., Saul, L.K.,
Nonlinear Dimensionality Reduction by Locally Linear Embedding,
Science(290), No. 5500, December 2000, pp. 2323-2326.
WWW Link. BibRef 0012

Kouropteva, O.[Olga], Okun, O.[Oleg], Pietikäinen, M.[Matti],
Incremental locally linear embedding,
PR(38), No. 10, October 2005, pp. 1764-1767.
Elsevier DOI 0508
BibRef
Earlier:
Incremental Locally Linear Embedding Algorithm,
SCIA05(521-530).
Springer DOI 0506
BibRef

Hadid, A., Kouropteva, O., Pietikanen, M.,
Unsupervised Learning Using Locally Linear Embedding: Experiments with Face Pose Analysis,
ICPR02(I: 111-114).
IEEE DOI 0211
BibRef

Chang, H.[Hong], Yeung, D.Y.[Dit-Yan],
Robust locally linear embedding,
PR(39), No. 6, June 2006, pp. 1053-1065.
Elsevier DOI Nonlinear dimensionality reduction; Manifold learning; Locally linear embedding; Principal component analysis; Outlier; Robust statistics; M-estimation; Handwritten digit; Wood texture 0604
BibRef

Pan, Y.Z.[Yao-Zhang], Ge, S.Z.S.[Shu-Zhi Sam], Al Mamun, A.[Abdullah],
Weighted locally linear embedding for dimension reduction,
PR(42), No. 5, May 2009, pp. 798-811.
Elsevier DOI 0902
Nonlinear dimensionality reduction, Manifold learning, Feature extraction, Locally linear embedding BibRef

Zhang, T., Huang, K., Li, X., Yang, J., Tao, D.,
Discriminative Orthogonal Neighborhood-Preserving Projections for Classification,
SMC-B(40), No. 1, February 2010, pp. 253-263.
IEEE DOI 0911
To overcome outlier problems in linear embedded classification. BibRef

Ge, S.Z.S.[Shu-Zhi Sam], Guan, F.[Feng], Pan, Y.Z.[Yao-Zhang], Loh, A.P.[Ai Poh],
Neighborhood linear embedding for intrinsic structure discovery,
MVA(21), No. 3, April 2010, pp. xx-yy.
Springer DOI 1003
Learning to discover neighborhood relationships. BibRef

Hou, C.P.[Chen-Ping], Zhang, C.S.[Chang-Shui], Wu, Y.[Yi], Jiao, Y.Y.[Yuan-Yuan],
Stable local dimensionality reduction approaches,
PR(42), No. 9, September 2009, pp. 2054-2066.
Elsevier DOI 0905
Dimensionality reduction, Manifold learning, Locally linear embedding; Laplacian eigenmaps, Local tangent space alignment BibRef

Lewandowski, M.[Michal], Makris, D.[Dimitrios], Nebel, J.C.[Jean-Christophe],
Automatic configuration of spectral dimensionality reduction methods,
PRL(31), No. 12, 1 September 2010, pp. 1720-1727.
Elsevier DOI 1008
Dimensionality reduction, Locally Linear Embedding, Isomap, Laplacian Eigenmaps, Mutual information, Radial Basis Function network BibRef

Wang, J.[Jing], Zhang, Z.Y.[Zhen-Yue],
Nonlinear embedding preserving multiple local-linearities,
PR(43), No. 4, April 2010, pp. 1257-1268.
Elsevier DOI 1002
Manifold learning, Dimensionality reduction, Weight vector, Stability of algorithm BibRef

Jain, N.[Neeraj], Verma, S.[Shekhar], Kumar, M.[Manish],
Low cost localization using Nyström extended locally linear embedding,
PRL(110), 2018, pp. 30-35.
Elsevier DOI 1806
Locally linear embedding, Localization, Nyström method, Received signal strength indicator, Manifold learning BibRef

Alipanahi, B.[Babak], Ghodsi, A.[Ali],
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 BibRef

Wang, R.P.[Rui-Ping], Shan, S.G.[Shi-Guang], Chen, X.L.[Xi-Lin], Chen, J.[Jie], Gao, W.[Wen],
Maximal Linear Embedding for Dimensionality Reduction,
PAMI(33), No. 9, September 2011, pp. 1776-1792.
IEEE DOI 1109
BibRef

Venkateswara, H.[Hemanth], Chakraborty, S.[Shayok], Panchanathan, S.[Sethuraman],
Deep-Learning Systems for Domain Adaptation in Computer Vision: Learning Transferable Feature Representations,
SPMag(34), No. 6, November 2017, pp. 117-129.
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 BibRef

Sun, W.W.[Wei-Wei], Yang, G.[Gang], Du, B.[Bo], Zhang, L.F.[Le-Fei], Zhang, L.P.[Liang-Pei],
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) BibRef

Jorge, J.[Javier], Paredes, R.[Roberto],
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 BibRef

Zhang, Y.[Yan], Zhang, Z.[Zhao], Qin, J.[Jie], Zhang, L.[Li], Li, B.[Bing], Li, F.Z.[Fan-Zhang],
Semi-supervised local multi-manifold Isomap by linear embedding for feature extraction,
PR(76), No. 1, 2018, pp. 662-678.
Elsevier DOI 1801
Semi-supervised manifold feature extraction BibRef

Zhu, R.F.[Rui-Feng], Dornaika, F.[Fadi], Ruichek, Y.[Yassine],
Joint graph based embedding and feature weighting for image classification,
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, Pattern recognition. Symmetric matrices, Feature extraction, Sparse matrices, Manifolds, Transforms, Laplace equations, Estimation, feature selection BibRef

Örnek, C.[Cem], Vural, E.[Elif],
Nonlinear supervised dimensionality reduction via smooth regular embeddings,
PR(87), 2019, pp. 55-66.
Elsevier DOI 1812
Manifold learning, Dimensionality reduction, Supervised learning, Out-of-sample, Nonlinear embeddings BibRef

Wang, J.[Justin], Wong, R.K.W.[Raymond K.W.], Lee, T.C.M.[Thomas C.M.],
Locally linear embedding with additive noise,
PRL(123), 2019, pp. 47-52.
Elsevier DOI 1906
Cross validation, Dimension reduction, Regularization BibRef

Kaya, S.[Semih], Vural, E.[Elif],
Learning Multi-Modal Nonlinear Embeddings: Performance Bounds and an Algorithm,
IP(30), 2021, pp. 4384-4394.
IEEE DOI 2104
BibRef
Earlier:
Multi-Modal Learning With Generalizable Nonlinear Dimensionality Reduction,
ICIP19(2139-2143)
IEEE DOI 1910
Training, Kernel, Interpolation, Data models, Geometry, Learning systems, Deep learning, Multi-modal learning, RBF interpolators. Cross-modal learning, multi-view learning, cross-modal retrieval, nonlinear embeddings. BibRef

Niu, G.[Guo], Ma, Z.M.[Zheng-Ming],
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], Niu, L.F.[Ling-Feng], Shi, Y.[Yong],
Graph regularized locally linear embedding for unsupervised feature 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], Zhang, B.[Bin], Qiang, Q.Y.[Qian-Yao],
Local Linear Embedding with Adaptive Neighbors,
PR(136), 2023, pp. 109205.
Elsevier DOI 2301
dimensionality reduction, Locally Linear Embedding, manifold learning, adaptive neighbor strategy BibRef


Huang, Y.[Yan], Wang, W.[Wei], Wang, L.[Liang], Tan, T.N.[Tie-Niu],
A General Nonlinear Embedding Framework Based on Deep Neural Network,
ICPR14(732-737)
IEEE DOI 1412
Face BibRef

Hwang, Y.[Yoonho], Han, B.H.[Bo-Hyung], Ahn, H.K.[Hee-Kap],
A fast nearest neighbor search algorithm by nonlinear embedding,
CVPR12(3053-3060).
IEEE DOI 1208
BibRef

Liu, R.J.[Ru-Jie], Wang, Y.H.[Yue-Hong], Baba, T.[Takayuki], Masumoto, D.[Daiki],
Semi-supervised learning by locally linear embedding in kernel space,
ICPR08(1-4).
IEEE DOI 0812
BibRef

Marinai, S.[Simone], Marino, E.[Emanuele], Soda, G.[Giovanni],
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], Wang, C.H.[Chun-Heng],
Clustering-based locally linear embedding,
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 .


Last update:Jun 5, 2024 at 10:22:22