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Introduction to the Issue on Robust Subspace Learning and Tracking: Theory, Algorithms, and Applications

T. Bouwmans, N. Vaswani, P. Rodriguez, R. Vidal, Z. Lin
<span title="">2018</span> <i title="Institute of Electrical and Electronics Engineers (IEEE)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/aznf273kcvcbfjcdeghr3xjd6i" style="color: black;">IEEE Journal on Selected Topics in Signal Processing</a> </i> &nbsp;
Gitlin et al. improve K-Subspaces clustering algorithm with a robust subspace recovery (RSR) method known as Coherence Pursuit (CoP) to handle low-rank outliers with low computational complexity.  ...  First, Chen et al. propose a Tensor Nuclear Norm (TNN)-based low-rank approximation with total variation regularization (TLR-TV) for color and multispectral image denoising.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/jstsp.2018.2879245">doi:10.1109/jstsp.2018.2879245</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/z3ohqdl37nat3pjo65fzsf2ady">fatcat:z3ohqdl37nat3pjo65fzsf2ady</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20210717053240/https://ieeexplore.ieee.org/ielx7/4200690/8566078/08566028.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/11/c1/11c1c4babd9c4e15b67828856069cf71a911be8a.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/jstsp.2018.2879245"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> ieee.com </button> </a>

A Unified Framework for Representation-Based Subspace Clustering of Out-of-Sample and Large-Scale Data

Xi Peng, Huajin Tang, Lei Zhang, Zhang Yi, Shijie Xiao
<span title="">2016</span> <i title="Institute of Electrical and Electronics Engineers (IEEE)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/j6amxna35bbs5p42wy5crllu2i" style="color: black;">IEEE Transactions on Neural Networks and Learning Systems</a> </i> &nbsp;
Some recent works build the graph using sparse, low-rank, and ℓ_2-norm-based representation, and have achieved state-of-the-art performance.  ...  Furthermore, we give an estimation for the error bounds by treating each subspace as a point in a hyperspace.  ...  Algorithm 3 Scalable Sparse Subspace Clustering (SSSC) and Scalable Low Rank Representation (SLRR).  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/tnnls.2015.2490080">doi:10.1109/tnnls.2015.2490080</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/26540718">pmid:26540718</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/enhlccmjsrcknd4xtsglvh2szu">fatcat:enhlccmjsrcknd4xtsglvh2szu</a> </span>
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Distributed Low-Rank Subspace Segmentation

Ameet Talwalkar, Lester Mackey, Yadong Mu, Shih-Fu Chang, Michael I. Jordan
<span title="">2013</span> <i title="IEEE"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/753trptklbb4nj6jquqadzwwdu" style="color: black;">2013 IEEE International Conference on Computer Vision</a> </i> &nbsp;
This has immediate implications for the scalability of subspace segmentation, which we demonstrate on a benchmark face recognition dataset and in simulations.  ...  We then introduce novel applications of LRR-based subspace segmentation to large-scale semisupervised learning for multimedia event detection, concept detection, and image tagging.  ...  Runtime: As noted in [21] , many state-of-the-art solvers for nuclear-norm regularized problems like Eq.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/iccv.2013.440">doi:10.1109/iccv.2013.440</a> <a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/iccv/TalwalkarMMCJ13.html">dblp:conf/iccv/TalwalkarMMCJ13</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/qgjtuqnlsjhdhfh7mxpqpzq764">fatcat:qgjtuqnlsjhdhfh7mxpqpzq764</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20160129083213/http://www.cv-foundation.org/openaccess/content_iccv_2013/papers/Talwalkar_Distributed_Low-Rank_Subspace_2013_ICCV_paper.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/d4/f7/d4f71e5623995b5102f64bb9f0946b6530996314.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/iccv.2013.440"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> ieee.com </button> </a>

Projective Low-rank Subspace Clustering via Learning Deep Encoder

Jun Li, Liu Hongfu, Handong Zhao, Yun Fu
<span title="">2017</span> <i title="International Joint Conferences on Artificial Intelligence Organization"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/vfwwmrihanevtjbbkti2kc3nke" style="color: black;">Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence</a> </i> &nbsp;
To address this challenge, we create a projective low-rank subspace clustering (PLrSC) scheme for large scale clustering problem. First, a small dataset is randomly sampled from big dataset.  ...  Low-rank subspace clustering (LRSC) has been considered as the state-of-the-art method on small datasets.  ...  Acknowledgments This work is supported in part by the NSF IIS award 1651902, ONR Young Investigator Award N00014-14-1-0484, and U.S. Army Research Office Young Investigator Award W911NF-14-1-0218.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.24963/ijcai.2017/298">doi:10.24963/ijcai.2017/298</a> <a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/ijcai/LiLZF17.html">dblp:conf/ijcai/LiLZF17</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/nppl7gprhnatjnrqgga7wjhfoi">fatcat:nppl7gprhnatjnrqgga7wjhfoi</a> </span>
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Beyond Linear Subspace Clustering: A Comparative Study of Nonlinear Manifold Clustering Algorithms [article]

Maryam Abdolali, Nicolas Gillis
<span title="2021-03-19">2021</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
It is based on the assumption that the high-dimensional data points are approximately distributed around several low-dimensional linear subspaces.  ...  Subspace clustering is an important unsupervised clustering approach.  ...  [51] , proposed Low-rank Kernel learning for Graph matrix (LKG) that learns a low-rank consensus kernel from a weighted linear combination of the given kernels by solving the following optimization problem  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2103.10656v1">arXiv:2103.10656v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/vtlb3d337fgixkumu5faidisrm">fatcat:vtlb3d337fgixkumu5faidisrm</a> </span>
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Robust PCA as Bilinear Decomposition With Outlier-Sparsity Regularization

Gonzalo Mateos, Georgios B. Giannakis
<span title="">2012</span> <i title="Institute of Electrical and Electronics Engineers (IEEE)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/gkn2pu46ozb4tmkxczacnmtvkq" style="color: black;">IEEE Transactions on Signal Processing</a> </i> &nbsp;
Beyond its neat ties to robust statistics, the developed outlier-aware PCA framework is versatile to accommodate novel and scalable algorithms to: i) track the low-rank signal subspace robustly, as new  ...  A least-trimmed squares estimator of a low-rank bilinear factor analysis model is shown closely related to that obtained from an ℓ_0-(pseudo)norm-regularized criterion encouraging sparsity in a matrix  ...  Lewis Goldberg (Oregon Research Institute) for facilitating access to the BFI data studied in Section VII-B.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/tsp.2012.2204986">doi:10.1109/tsp.2012.2204986</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/up4cvmexj5f6bclc64bvsrwtxa">fatcat:up4cvmexj5f6bclc64bvsrwtxa</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20130226042216/http://iie.fing.edu.uy:80/~gmateos/pubs/rpca/RPCA_TSP.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/04/98/04980d1408caa8d417adf68bdadf23d7a90bb0c5.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/tsp.2012.2204986"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> ieee.com </button> </a>

Interpretable Hyperspectral AI: When Non-Convex Modeling meets Hyperspectral Remote Sensing [article]

Danfeng Hong and Wei He and Naoto Yokoya and Jing Yao and Lianru Gao and Liangpei Zhang and Jocelyn Chanussot and Xiao Xiang Zhu
<span title="2021-03-02">2021</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
However, their ability in handling complex practical problems remains limited, particularly for HS data, due to the effects of various spectral variabilities in the process of HS imaging and the complexity  ...  For this reason, it is, therefore, urgent to develop more intelligent and automatic approaches for various HS RS applications.  ...  [108] modeled the low-rank properties in the HS tensor to address the SV for robust SU.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2103.01449v1">arXiv:2103.01449v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/jvo4pr5atvfb5kohpslvkhhmky">fatcat:jvo4pr5atvfb5kohpslvkhhmky</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20210304000855/https://arxiv.org/pdf/2103.01449v1.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/31/82/31829a43a78bfaf1126ff149e6f0dc9befeb4184.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2103.01449v1" title="arxiv.org access"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> arxiv.org </button> </a>

Decomposition into low-rank plus additive matrices for background/foreground separation: A review for a comparative evaluation with a large-scale dataset

Thierry Bouwmans, Andrews Sobral, Sajid Javed, Soon Ki Jung, El-Hadi Zahzah
<span title="">2017</span> <i title="Elsevier BV"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/x3ibtg2oifh47c73tgo66gjrw4" style="color: black;">Computer Science Review</a> </i> &nbsp;
Recovery (RSR), Robust Subspace Tracking (RST) and Robust Low-Rank Minimization (RLRM).  ...  In this context, this work aims to initiate a rigorous and comprehensive review of the similar problem formulations in robust subspace learning and tracking based on decomposition into low-rank plus additive  ...  thank the following researchers: Zhouchen Lin (Visual Computing Group, Microsoft Research Asia) who has kindly provided the solver LADMAP [192] and the l 1 -filtering [196] , Shiqian Ma (Institute for  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/j.cosrev.2016.11.001">doi:10.1016/j.cosrev.2016.11.001</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/vdh7ic4n6zfkjlccnyiq74z5wu">fatcat:vdh7ic4n6zfkjlccnyiq74z5wu</a> </span>
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Distributed Low-rank Subspace Segmentation [article]

Ameet Talwalkar, Lester Mackey, Yadong Mu, Shih-Fu Chang, Michael I. Jordan
<span title="2013-10-16">2013</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
This has immediate implications for the scalability of subspace segmentation, which we demonstrate on a benchmark face recognition dataset and in simulations.  ...  We then introduce novel applications of LRR-based subspace segmentation to large-scale semi-supervised learning for multimedia event detection, concept detection, and image tagging.  ...  norm · represents the spectral norm of a matrix.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1304.5583v2">arXiv:1304.5583v2</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/q522vxwe3ng2zlq3he2fsewgzi">fatcat:q522vxwe3ng2zlq3he2fsewgzi</a> </span>
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Fast Robust PCA on Graphs

Nauman Shahid, Nathanael Perraudin, Vassilis Kalofolias, Gilles Puy, Pierre Vandergheynst
<span title="">2016</span> <i title="Institute of Electrical and Electronics Engineers (IEEE)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/aznf273kcvcbfjcdeghr3xjd6i" style="color: black;">IEEE Journal on Selected Topics in Signal Processing</a> </i> &nbsp;
Our theoretical analysis proves that the proposed model is able to recover approximate low-rank representations with a bounded error for clusterable data.  ...  In this paper we propose a principal component analysis (PCA) based solution that overcomes these three issues and approximates a low-rank recovery method for high dimensional datasets.  ...  ACKNOWLEDGEMENT The work of Nauman Shahid and Nathanael Perraudin is supported by the SNF grant no. 200021 154350/1 for the project "Towards signal processing on graphs". The work of G.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/jstsp.2016.2555239">doi:10.1109/jstsp.2016.2555239</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/ri3vmhsmjreqrkzgp2ruvtpvme">fatcat:ri3vmhsmjreqrkzgp2ruvtpvme</a> </span>
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Restricted Connection Orthogonal Matching Pursuit For Sparse Subspace Clustering [article]

Wenqi Zhu, Yuesheng Zhu, Li Zhong, Shuai Yang
<span title="2019-05-01">2019</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
In this paper, we propose a noise-robust algorithm, Restricted Connection Orthogonal Matching Pursuit for Sparse Subspace Clustering (RCOMP-SSC), to improve the clustering accuracy and maintain the low  ...  And the framework is scalable for other data point selection strategies.  ...  For instance, Low Rank Representation (LRR) [7, 8] based on nuclear norm represents the data points with the lowest-rank representation among all the candidates; Least Square Regression (LSR) [9] with  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1905.00420v1">arXiv:1905.00420v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/r4dmsbtelrh6xneyy6jvf7fbf4">fatcat:r4dmsbtelrh6xneyy6jvf7fbf4</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200912164202/https://arxiv.org/pdf/1905.00420v1.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/27/50/2750edb1f6f5463abb17f5409d24717ce199f6b9.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1905.00420v1" title="arxiv.org access"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> arxiv.org </button> </a>

Essential Tensor Learning for Multi-view Spectral Clustering [article]

Jianlong Wu, Zhouchen Lin, Hongbin Zha
<span title="2019-05-06">2019</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
By incorporating the idea from robust principle component analysis, tensor singular value decomposition (t-SVD) based tensor nuclear norm is imposed to preserve the low-rank property of the essential tensor  ...  In this paper, we focus on the Markov chain based spectral clustering method and propose a novel essential tensor learning method to explore the high order correlations for multi-view representation.  ...  Yuan Xie for his selfless support in sharing codes and datasets as well as the valuable suggestions.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1807.03602v2">arXiv:1807.03602v2</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/nute6fz6t5fuvojg5trnlwhpxe">fatcat:nute6fz6t5fuvojg5trnlwhpxe</a> </span>
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Robust and Scalable Column/Row Sampling from Corrupted Big Data [article]

Mostafa Rahmani, George Atia
<span title="2016-11-18">2016</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
Conventional sampling techniques fall short of drawing descriptive sketches of the data when the data is grossly corrupted as such corruptions break the low rank structure required for them to perform  ...  In addition, we develop new scalable randomized designs of the proposed algorithms.  ...  The low rankness of the data is a crucial requirement for these algorithms.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1611.05977v1">arXiv:1611.05977v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/vfdxvcm3f5g6ddozrpkafwmfai">fatcat:vfdxvcm3f5g6ddozrpkafwmfai</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200930145954/https://arxiv.org/pdf/1611.05977v1.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/8c/1a/8c1a6265c148c454018749b0dd614bfd8eb18d14.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1611.05977v1" title="arxiv.org access"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> arxiv.org </button> </a>

Online Stochastic Tensor Decomposition for Background Subtraction in Multispectral Video Sequences

Andrews Sobral, Sajid Javed, Soon Ki Jung, Thierry Bouwmans, El-hadi Zahzah
<span title="">2015</span> <i title="IEEE"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/6s36fqp6q5hgpdq2scjq3sfu6a" style="color: black;">2015 IEEE International Conference on Computer Vision Workshop (ICCVW)</a> </i> &nbsp;
subtraction is an important task for visual surveillance systems.  ...  First, the experimental evaluations on synthetic generated data show the robustness of the OSTD with other state of the art approaches then, we apply the same idea on seven multispectral video bands to  ...  The authors gratefully acknowledge the financial support of CAPES (Brazil) for granting a PhD scholarship to the first author.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/iccvw.2015.125">doi:10.1109/iccvw.2015.125</a> <a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/iccvw/SobralJJBZ15.html">dblp:conf/iccvw/SobralJJBZ15</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/htzy5ep4lrdjhp2kixrsspnr6e">fatcat:htzy5ep4lrdjhp2kixrsspnr6e</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170812050806/http://www.cv-foundation.org/openaccess/content_iccv_2015_workshops/w24/papers/Sobral_Online_Stochastic_Tensor_ICCV_2015_paper.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/3e/13/3e13f24b4a8088d83f16e63cba5e3463701148ec.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/iccvw.2015.125"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> ieee.com </button> </a>

2020 Index IEEE Transactions on Knowledge and Data Engineering Vol. 32

<span title="">2021</span> <i title="Institute of Electrical and Electronics Engineers (IEEE)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/ht3yl6qfebhwrg7vrxkz4gxv3q" style="color: black;">IEEE Transactions on Knowledge and Data Engineering</a> </i> &nbsp;
Zheng, K., +, TKDE Nov. 2020 2227-2240 Robust Low-Rank Kernel Subspace Clustering based on the Schatten p-norm and Correntropy.  ...  Xu, L., +, TKDE Dec. 2020 2414-2425 Robust Low-Rank Kernel Subspace Clustering based on the Schatten p-norm and Correntropy.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/tkde.2020.3038549">doi:10.1109/tkde.2020.3038549</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/75f5fmdrpjcwrasjylewyivtmu">fatcat:75f5fmdrpjcwrasjylewyivtmu</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20201209083459/https://ieeexplore.ieee.org/ielx7/69/9285350/09285351.pdf?tp=&amp;arnumber=9285351&amp;isnumber=9285350&amp;ref=" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/39/61/396190325b193dfc727bd35c0fb53cc6316da11f.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/tkde.2020.3038549"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> ieee.com </button> </a>
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