Robust low-rank representation with adaptive graph regularization from clean data

[1]  Shuilong He,et al.  A classification method to detect faults in a rotating machinery based on kernelled support tensor machine and multilinear principal component analysis , 2020, Appl. Intell..

[2]  Wenjie Zhu,et al.  Sparse and low-rank regularized deep subspace clustering , 2020, Knowl. Based Syst..

[3]  Yanxue Wang,et al.  Cross-domain intelligent fault classification of bearings based on tensor-aligned invariant subspace learning and two-dimensional convolutional neural networks , 2020, Knowl. Based Syst..

[4]  Hamido Fujita,et al.  Inverse projection group sparse representation for tumor classification: A low rank variation dictionary approach , 2020, Knowl. Based Syst..

[5]  Zhihui Lai,et al.  Structured optimal graph based sparse feature extraction for semi-supervised learning , 2020, Signal Process..

[6]  Hong Liu,et al.  Incomplete Multiview Spectral Clustering With Adaptive Graph Learning , 2020, IEEE Transactions on Cybernetics.

[7]  Lin Zhang,et al.  Discriminative low-rank preserving projection for dimensionality reduction , 2019, Appl. Soft Comput..

[8]  Feiping Nie,et al.  Graph Structure Fusion for Multiview Clustering , 2019, IEEE Transactions on Knowledge and Data Engineering.

[9]  Zenglin Xu,et al.  Robust Graph Learning From Noisy Data , 2018, IEEE Transactions on Cybernetics.

[10]  I. Kopriva,et al.  $\ell_0$ -Motivated Low-Rank Sparse Subspace Clustering , 2018, IEEE Transactions on Cybernetics.

[11]  Chunwei Tian,et al.  Low-rank representation with adaptive graph regularization , 2018, Neural Networks.

[12]  Jian Yang,et al.  Adaptive weighted nonnegative low-rank representation , 2018, Pattern Recognit..

[13]  Ling Shao,et al.  Scaled Simplex Representation for Subspace Clustering , 2018, IEEE Transactions on Cybernetics.

[14]  Junbin Gao,et al.  Subspace Clustering via Learning an Adaptive Low-Rank Graph , 2018, IEEE Transactions on Image Processing.

[15]  Dong Xu,et al.  Robust Kernel Low-Rank Representation , 2016, IEEE Transactions on Neural Networks and Learning Systems.

[16]  Feiping Nie,et al.  Subspace Clustering via New Low-Rank Model with Discrete Group Structure Constraint , 2016, IJCAI.

[17]  René Vidal,et al.  Generalized Principal Component Analysis , 2016, Interdisciplinary applied mathematics.

[18]  Junbin Gao,et al.  Laplacian Regularized Low-Rank Representation and Its Applications , 2016, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[19]  Feiping Nie,et al.  The Constrained Laplacian Rank Algorithm for Graph-Based Clustering , 2016, AAAI.

[20]  René Vidal,et al.  Algebraic Clustering of Affine Subspaces , 2015, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[21]  Feiping Nie,et al.  A New Simplex Sparse Learning Model to Measure Data Similarity for Clustering , 2015, IJCAI.

[22]  Feiping Nie,et al.  Clustering and projected clustering with adaptive neighbors , 2014, KDD.

[23]  Zongben Xu,et al.  Enhancing Low-Rank Subspace Clustering by Manifold Regularization , 2014, IEEE Transactions on Image Processing.

[24]  G. Sapiro,et al.  A collaborative framework for 3D alignment and classification of heterogeneous subvolumes in cryo-electron tomography. , 2013, Journal of structural biology.

[25]  Nenghai Yu,et al.  Non-negative low rank and sparse graph for semi-supervised learning , 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.

[26]  René Vidal,et al.  Sparse Subspace Clustering: Algorithm, Theory, and Applications , 2012, IEEE transactions on pattern analysis and machine intelligence.

[27]  Shuicheng Yan,et al.  Latent Low-Rank Representation for subspace segmentation and feature extraction , 2011, 2011 International Conference on Computer Vision.

[28]  Zhixun Su,et al.  Linearized Alternating Direction Method with Adaptive Penalty for Low-Rank Representation , 2011, NIPS.

[29]  René Vidal,et al.  Subspace Clustering , 2011, IEEE Signal Processing Magazine.

[30]  Yong Yu,et al.  Robust Recovery of Subspace Structures by Low-Rank Representation , 2010, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[31]  René Vidal,et al.  Motion Segmentation in the Presence of Outlying, Incomplete, or Corrupted Trajectories , 2010, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[32]  Zhouchen Lin,et al.  Analysis and Improvement of Low Rank Representation for Subspace segmentation , 2010, ArXiv.

[33]  Shuicheng Yan,et al.  Learning With $\ell ^{1}$-Graph for Image Analysis , 2010, IEEE Transactions on Image Processing.

[34]  Yi Ma,et al.  Robust principal component analysis? , 2009, JACM.

[35]  Junfeng Yang,et al.  A Fast Algorithm for Edge-Preserving Variational Multichannel Image Restoration , 2009, SIAM J. Imaging Sci..

[36]  Allen Y. Yang,et al.  Robust Face Recognition via Sparse Representation , 2009, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[37]  Emmanuel J. Candès,et al.  A Singular Value Thresholding Algorithm for Matrix Completion , 2008, SIAM J. Optim..

[38]  René Vidal,et al.  Motion segmentation via robust subspace separation in the presence of outlying, incomplete, or corrupted trajectories , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.

[39]  S. Shankar Sastry,et al.  Generalized principal component analysis (GPCA) , 2005, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[40]  Michael I. Jordan,et al.  On Spectral Clustering: Analysis and an algorithm , 2001, NIPS.

[41]  S T Roweis,et al.  Nonlinear dimensionality reduction by locally linear embedding. , 2000, Science.

[42]  Jitendra Malik,et al.  Normalized cuts and image segmentation , 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[43]  Hamido Fujita,et al.  Low-rank local tangent space embedding for subspace clustering , 2020, Inf. Sci..

[44]  Sheng Wang,et al.  Low-rank graph preserving discriminative dictionary learning for image recognition , 2020, Knowl. Based Syst..

[45]  Guangcan Liu,et al.  Implicit Block Diagonal Low-Rank Representation , 2018, IEEE Transactions on Image Processing.

[46]  Songcan Chen,et al.  Sparsity preserving projections with applications to face recognition , 2010, Pattern Recognit..