Fetching the paper…
Reading the bibliography…
Subspace clustering is an important unsupervised clustering approach.
Springer, New York (1986)
Jolliffe, I.T.: Principal component analysis · 1986
Earlier work this paper cites.
International journal of computer vision
Tomasi, C., Kanade, T.: Shape and motion from image streams under orthography: a factorization method · 1992
Earlier work this paper cites.
In: Proceedings of 12th international conference on pattern recognition, vol. 1, pp. 582–585. IEEE (1994)
Ojala, T., Pietikainen, M., Harwood, D.: Performance evaluation of texture measures with classification based on Kullback discrimination of distributions · 1994
Earlier work this paper cites.
In: Proceedings of IEEE International Conference on Computer Vision, pp. 1071–1076. IEEE (1995)
Costeira, J., Kanade, T.: A multi-body factorization method for motion analysis · 1995
Earlier work this paper cites.
Nene, S.A., Nayar, S.K., Murase, H., et al.: Columbia object image library (coil-100) (1996)
1996
Earlier work this paper cites.
In: Conference on Statistical Science Honouring the Bicentennial of Stefano Franscini’s Birth, pp. 203–219. Springer (1997)
Hastie, T., Simard, P.: Metrics and models for handwritten character recognition · 1997
Earlier work this paper cites.
International Journal of Computer Vision
Costeira, J.P., Kanade, T.: A multibody factorization method for independently moving objects · 1998
Earlier work this paper cites.
IEEE Trans. Pattern Anal. Mach. Intelligence (23), 6 (1998)
Georghiades, A., Belhumeur, P.: Illumination cone models for faces recognition under variable lighting and pose · 1998
Earlier work this paper cites.
In: Proceedings of the seventh IEEE international conference on computer vision, vol. 2, pp. 1150–1157. Ieee (1999)
Lowe, D.G.: Object recognition from local scale-invariant features · 1999
Earlier work this paper cites.
Neural computation
Tipping, M.E., Bishop, C.M.: Mixtures of probabilistic principal component analyzers · 1999
Earlier work this paper cites.
Journal of Global Optimization
Bradley, P.S., Mangasarian, O.L.: K-plane clustering · 2000
Earlier work this paper cites.
IEEE Transactions on pattern analysis and machine intelligence
Shi, J., Malik, J.: Normalized cuts and image segmentation · 2000
Earlier work this paper cites.
Journal of Optimization Theory and Applications
Tseng, P.: Nearest q-flat to m points · 2000
Earlier work this paper cites.
Advances in neural information processing systems
Belkin, M., Niyogi, P.: Laplacian eigenmaps and spectral techniques for embedding and clustering · 2001
Earlier work this paper cites.
In: Advances in neural information processing systems, pp. 217–223 (2001)
Hahnloser, R.H., Seung, H.S.: Permitted and forbidden sets in symmetric threshold-linear networks · 2001
Earlier work this paper cites.
In: Proceedings Eighth IEEE International Conference on computer Vision. ICCV 2001, vol. 2, pp. 586–591. IEEE (2001)
Kanatani, K.i.: Motion segmentation by subspace separation and model selection · 2001
Earlier work this paper cites.
SIAM (2002)
Higham, N.J.: Accuracy and stability of numerical algorithms · 2002
Earlier work this paper cites.
Advances in neural information processing systems
Ng, A.Y., Jordan, M.I., Weiss, Y., et al.: On spectral clustering: Analysis and an algorithm · 2002
Earlier work this paper cites.
Journal of machine learning research
Strehl, A., Ghosh, J.: Cluster ensembles—a knowledge reuse framework for combining multiple partitions · 2002
Earlier work this paper cites.
IEEE Transactions on Pattern Analysis and Machine Intelligence
Basri, R., Jacobs, D.W.: Lambertian reflectance and linear subspaces · 2003
Earlier work this paper cites.
In: 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings., vol. 1, pp. I–I. IEEE (2003)
Ho, J., Yang, M.H., Lim, J., Lee, K.C., Kriegman, D.: Clustering appearances of objects under varying illumination conditions · 2003
Earlier work this paper cites.
Journal of machine learning research
Saul, L.K., Roweis, S.T.: Think globally, fit locally: unsupervised learning of low dimensional manifolds · 2003
Earlier work this paper cites.
In: Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004., vol. 1, pp. I–I. IEEE (2004)
Gruber, A., Weiss, Y.: Multibody factorization with uncertainty and missing data using the em algorithm · 2004
Earlier work this paper cites.
In: 2005 IEEE computer society conference on computer vision and pattern recognition (CVPR’05), vol. 1, pp. 886–893. Ieee (2005)
Dalal, N., Triggs, B.: Histograms of oriented gradients for human detection · 2005
Earlier work this paper cites.
IEEE Transactions on Pattern Analysis and Machine Intelligence
Lee, K.C., Ho, J., Kriegman, D.J.: Acquiring linear subspaces for face recognition under variable lighting · 2005
Earlier work this paper cites.
IEEE Transactions on Pattern Analysis and Machine Intelligence
Vidal, R., Ma, Y., Sastry, S.: Generalized principal component analysis (gpca) · 2005
Earlier work this paper cites.
Journal of machine learning research
Belkin, M., Niyogi, P., Sindhwani, V.: Manifold regularization: A geometric framework for learning from labeled and unlabeled examples · 2006
Earlier work this paper cites.
In: Advances in neural information processing systems, pp. 609–616 (2007)
Huang, K., Aviyente, S.: Sparse representation for signal classification · 2007
Earlier work this paper cites.
Statistics and computing
Von Luxburg, U.: A tutorial on spectral clustering · 2007
Earlier work this paper cites.
In: 2008 IEEE Conference on Computer Vision and Pattern Recognition, pp. 1–8. IEEE (2008)
Lu, Z., Carreira-Perpinan, M.A.: Constrained spectral clustering through affinity propagation · 2008
Earlier work this paper cites.
IEEE Transactions on Pattern Analysis and Machine Intelligence
Wright, J., Yang, A.Y., Ganesh, A., Sastry, S.S., Ma, Y.: Robust face recognition via sparse representation · 2008
Earlier work this paper cites.
Pattern recognition
Xiang, S., Nie, F., Zhang, C.: Learning a mahalanobis distance metric for data clustering and classification · 2008
Earlier work this paper cites.
IEEE transactions on image processing
Cheng, B., Yang, J., Yan, S., Fu, Y., Huang, T.S.: Learning with · 2009
Earlier work this paper cites.
American Mathematical Soc. (2009)
Daverman, R.J., Venema, G.: Embeddings in manifolds, vol. 106 · 2009
Earlier work this paper cites.
Tech. Rep. TiCC-TR 2009-005, Tilburg University (2009)
Van Der Maaten, L., Postma, E., Van den Herik, J.: Dimensionality reduction: A comparative review · 2009
Earlier work this paper cites.
In: Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining, pp. 907–916 (2009)
Yan, D., Huang, L., Jordan, M.I.: Fast approximate spectral clustering · 2009
Earlier work this paper cites.
In: 2010 IEEE computer society conference on computer vision and pattern recognition, pp. 3360–3367. IEEE (2010)
Wang, J., Yang, J., Yu, K., Lv, F., Huang, T., Gong, Y.: Locality-constrained linear coding for image classification · 2010
Earlier work this paper cites.
arXiv preprint arXiv:1108.0775 (2011)
Bach, F., Jenatton, R., Mairal, J., Obozinski, G.: Optimization with sparsity-inducing penalties · 2011
Earlier work this paper cites.
Journal of the ACM (JACM)
Candès, E.J., Li, X., Ma, Y., Wright, J.: Robust principal component analysis? · 2011
Earlier work this paper cites.
In: Advances in neural information processing systems, pp. 55–63 (2011)
Elhamifar, E., Vidal, R.: Sparse manifold clustering and embedding · 2011
Earlier work this paper cites.
In: Proceedings of the fourteenth international conference on artificial intelligence and statistics, pp. 315–323 (2011)
Glorot, X., Bordes, A., Bengio, Y.: Deep sparse rectifier neural networks · 2011
Earlier work this paper cites.
In: Joint European Conference on Machine Learning and Knowledge Discovery in Databases, pp. 405–420. Springer (2011)
Luo, D., Nie, F., Ding, C., Huang, H.: Multi-subspace representation and discovery · 2011
Earlier work this paper cites.
In: CVPR 2011, pp. 2137–2144. IEEE (2011)
Nasihatkon, B., Hartley, R.: Graph connectivity in sparse subspace clustering · 2011
Earlier work this paper cites.
IEEE Signal Processing Magazine
Vidal, R.: Subspace clustering · 2011
Earlier work this paper cites.
In: Twenty-Fifth AAAI Conference on Artificial Intelligence (2011)
Wang, S., Yuan, X., Yao, T., Yan, S., Shen, J.: Efficient subspace segmentation via quadratic programming · 2011
Earlier work this paper cites.
In: 2011 International conference on computer vision, pp. 471–478. IEEE (2011)
Zhang, L., Yang, M., Feng, X.: Sparse representation or collaborative representation: Which helps face recognition? · 2011
Earlier work this paper cites.
IEEE Transactions on Pattern Analysis and Machine Intelligence
Liu, G., Lin, Z., Yan, S., Sun, J., Yu, Y., Ma, Y.: Robust recovery of subspace structures by low-rank representation · 2012
Earlier work this paper cites.
In: European conference on computer vision, pp. 347–360. Springer (2012)
Lu, C.Y., Min, H., Zhao, Z.Q., Zhu, L., Huang, D.S., Yan, S.: Robust and efficient subspace segmentation via least squares regression · 2012
Earlier work this paper cites.
The Annals of Statistics
Soltanolkotabi, M., Candes, E.J., et al.: A geometric analysis of subspace clustering with outliers · 2012
Earlier work this paper cites.
IEEE Transactions on Pattern Analysis and Machine Intelligence
Elhamifar, E., Vidal, R.: Sparse subspace clustering: Algorithm, theory, and applications · 2013
Earlier work this paper cites.
In: Proceedings of the IEEE international conference on computer vision, pp. 1345–1352 (2013)
Lu, C., Feng, J., Lin, Z., Yan, S.: Correlation adaptive subspace segmentation by trace lasso · 2013
Earlier work this paper cites.
In: Proceedings of the IEEE international conference on computer vision, pp. 1801–1808 (2013)
Lu, C., Tang, J., Lin, M., Lin, L., Yan, S., Lin, Z.: Correntropy induced l2 graph for robust subspace clustering · 2013
Cited alongside, same era.
IEEE transactions on geoscience and remote sensing
Lu, X., Wang, Y., Yuan, Y.: Graph-regularized low-rank representation for destriping of hyperspectral images · 2013
Cited alongside, same era.
In: Advances in Neural Information Processing Systems, pp. 64–72 (2013)
Wang, Y.X., Xu, H., Leng, C.: Provable subspace clustering: When LRR meets SSC · 2013
Cited alongside, same era.
In: Twenty-Third International Joint Conference on Artificial Intelligence. Citeseer (2013)
Zhang, T., Ji, R., Liu, W., Tao, D., Hua, G.: Semi-supervised learning with manifold fitted graphs · 2013
Cited alongside, same era.
Neurocomputing
Zheng, Y., Zhang, X., Yang, S., Jiao, L.: Low-rank representation with local constraint for graph construction · 2013
Cited alongside, same era.
IEEE Transactions on Pattern Analysis and Machine Intelligence
Lu, C., Feng, J., Lin, Z., Mei, T., Yan, S.: Subspace clustering by block diagonal representation · 2018
Later among the works it cites.
IEEE Transactions on Image Processing
Peng, X., Feng, J., Xiao, S., Yau, W.Y., Zhou, J.T., Yang, S.: Structured autoencoders for subspace clustering · 2018
Later among the works it cites.
Neurocomputing
Qiao, L., Zhang, L., Chen, S., Shen, D.: Data-driven graph construction and graph learning: A review · 2018
Later among the works it cites.
In: Proceedings of the European Conference on Computer Vision (ECCV), pp. 67–83 (2018)
You, C., Li, C., Robinson, D.P., Vidal, R.: Scalable exemplar-based subspace clustering on class-imbalanced data · 2018
Later among the works it cites.
In: Asian Conference on Computer Vision, pp. 466–481. Springer (2018)
Zhang, T., Ji, P., Harandi, M., Hartley, R., Reid, I.: Scalable deep k-subspace clustering · 2018
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
In: Advances in neural information processing systems, pp. 2672–2680 (2014)
Goodfellow, I., Pouget-Abadie, J., Mirza, M., Xu, B., Warde-Farley, D., Ozair, S., Courville, A., Bengio, Y.: Generative adversarial nets · 2014
Cited alongside, same era.
In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp. 3834–3841 (2014)
Hu, H., Lin, Z., Feng, J., Zhou, J.: Smooth representation clustering · 2014
Cited alongside, same era.
In: IEEE Winter Conference on Applications of Computer Vision, pp. 461–468. IEEE (2014)
Ji, P., Salzmann, M., Li, H.: Efficient dense subspace clustering · 2014
Cited alongside, same era.
In: Advances in Neural Information Processing Systems, pp. 2078–2086 (2014)
Jiang, L., Meng, D., Yu, S.I., Lan, Z., Shan, S., Hauptmann, A.: Self-paced learning with diversity · 2014
Cited alongside, same era.
IEEE Transactions on Image Processing
Liu, J., Chen, Y., Zhang, J., Xu, Z.: Enhancing low-rank subspace clustering by manifold regularization · 2014
Cited alongside, same era.
In: 2014 IEEE international conference on image processing (ICIP), pp. 2849–2853. IEEE (2014)
Patel, V.M., Vidal, R.: Kernel sparse subspace clustering · 2014
Cited alongside, same era.
The Annals of Statistics
Soltanolkotabi, M., Elhamifar, E., Candes, E.J., et al.: Robust subspace clustering · 2014
Cited alongside, same era.
In: Joint IAPR International Workshops on Statistical Techniques in Pattern Recognition (SPR) and Structural and Syntactic Pattern Recognition (SSPR), pp. 42–51. Springer (2018)
Zhou, L., Wang, S., Bai, X., Zhou, J., Hancock, E.: Iterative deep subspace clustering · 2018
Later among the works it cites.
In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 1596–1604 (2018)
Zhou, P., Hou, Y., Feng, J.: Deep adversarial subspace clustering · 2018
Later among the works it cites.
Pattern Recognition Letters
Zhu, W., Lu, J., Zhou, J.: Nonlinear subspace clustering for image clustering · 2018
Later among the works it cites.
Signal Processing
Abdolali, M., Gillis, N., Rahmati, M.: Scalable and robust sparse subspace clustering using randomized clustering and multilayer graphs · 2019
Later among the works it cites.
In: Proceedings of the IEEE International Conference on Computer Vision, pp. 4502–4511 (2019)
Bau, D., Zhu, J.Y., Wulff, J., Peebles, W., Strobelt, H., Zhou, B., Torralba, A.: Seeing what a gan cannot generate · 2019
Later among the works it cites.
Knowledge-Based Systems
Chen, Y., Yi, Z.: Locality-constrained least squares regression for subspace clustering · 2019
Later among the works it cites.
Pattern Recognition Letters
Hechmi, S., Gallas, A., Zagrouba, E.: Multi-kernel sparse subspace clustering on the riemannian manifold of symmetric positive definite matrices · 2019
Later among the works it cites.
IEEE Transactions on Knowledge and Data Engineering
Huang, D., Wang, C.D., Wu, J.S., Lai, J.H., Kwoh, C.K.: Ultra-scalable spectral clustering and ensemble clustering · 2019
Later among the works it cites.
Knowledge-Based Systems
Kang, Z., Wen, L., Chen, W., Xu, Z.: Low-rank kernel learning for graph-based clustering · 2019
Later among the works it cites.
In: Proceedings of the IEEE International Conference on Computer Vision Workshops, pp. 0–0 (2019)
Lane, C., Boger, R., You, C., Tsakiris, M., Haeffele, B., Vidal, R.: Classifying and comparing approaches to subspace clustering with missing data · 2019
Later among the works it cites.
In: Advances in Neural Information Processing Systems, pp. 12,416–12,425 (2019)
Matsushima, S., Brbic, M.: Selective sampling-based scalable sparse subspace clustering · 2019
Later among the works it cites.
arXiv preprint arXiv:1911.00068 (2019)
Northcutt, C.G., Jiang, L., Chuang, I.L.: Confident learning: Estimating uncertainty in dataset labels · 2019
Later among the works it cites.
In: Proceedings of the IEEE International Conference on Computer Vision Workshops, pp. 0–0 (2019)
Seo, J., Koo, J., Jeon, T.: Deep closed-form subspace clustering · 2019
Later among the works it cites.
SIAM Journal on Mathematics of Data Science
Udell, M., Townsend, A.: Why are big data matrices approximately low rank? · 2019
Later among the works it cites.
Information Sciences
Yang, C., Ren, Z., Sun, Q., Wu, M., Yin, M., Sun, Y.: Joint correntropy metric weighting and block diagonal regularizer for robust multiple kernel subspace clustering · 2019
Later among the works it cites.
IEEE Transactions on Pattern Analysis and Machine Intelligence
Yang, J., Liang, J., Wang, K., Rosin, P.L., Yang, M.H.: Subspace clustering via good neighbors · 2019
Later among the works it cites.
In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp. 4066–4075 (2019)
Yang, X., Deng, C., Zheng, F., Yan, J., Liu, W.: Deep spectral clustering using dual autoencoder network · 2019
Later among the works it cites.
In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 5473–5482 (2019)
Zhang, J., Li, C.G., You, C., Qi, X., Zhang, H., Guo, J., Lin, Z.: Self-supervised convolutional subspace clustering network · 2019
Later among the works it cites.
arXiv preprint arXiv:1904.10596 (2019)
Zhang, T., Ji, P., Harandi, M., Huang, W., Li, H.: Neural collaborative subspace clustering · 2019
Later among the works it cites.
Information Sciences
Zhang, X., Sun, H., Liu, Z., Ren, Z., Cui, Q., Li, Y.: Robust low-rank kernel multi-view subspace clustering based on the schatten p-norm and correntropy · 2019
Later among the works it cites.
In: 28th International Joint Conference on Artificial Intelligence. York (2019)
Zhou, L., Xiao, B., Liu, X., Zhou, J., Hancock, E.R., et al.: Latent distribution preserving deep subspace clustering · 2019
Later among the works it cites.
In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp. 4155–4164 (2020)
Chen, Y., Li, C.G., You, C.: Stochastic sparse subspace clustering · 2020
Later among the works it cites.
Information Sciences
Deng, T., Ye, D., Ma, R., Fujita, H., Xiong, L.: Low-rank local tangent space embedding for subspace clustering · 2020
Later among the works it cites.
Pattern Recognition Letters
Fard, M.M., Thonet, T., Gaussier, E.: Deep k-means: Jointly clustering with k-means and learning representations · 2020
Later among the works it cites.
arXiv preprint arXiv:2010.03697 (2020)
Haeffele, B.D., You, C., Vidal, R.: A critique of self-expressive deep subspace clustering · 2020
Later among the works it cites.
In: International Conference on Machine Learning, pp. 4804–4815. PMLR (2020)
Jiang, L., Huang, D., Liu, M., Yang, W.: Beyond synthetic noise: Deep learning on controlled noisy labels · 2020
Later among the works it cites.
Neural Networks (2020)
Kang, Z., Lu, X., Lu, Y., Peng, C., Chen, W., Xu, Z.: Structure learning with similarity preserving · 2020
Later among the works it cites.
Neural Networks
Kang, Z., Zhao, X., Peng, C., Zhu, H., Zhou, J.T., Peng, X., Chen, W., Xu, Z.: Partition level multiview subspace clustering · 2020
Later among the works it cites.
In: The IEEE Winter Conference on Applications of Computer Vision, pp. 2039–2048 (2020)
Kheirandishfard, M., Zohrizadeh, F., Kamangar, F.: Multi-level representation learning for deep subspace clustering · 2020
Later among the works it cites.
arXiv preprint arXiv:2010.08515 (2020)
Li, Z., Zhang, Y., Arora, S.: Why are convolutional nets more sample-efficient than fully-connected nets? · 2020
Later among the works it cites.
In: International Conference on Machine Learning, pp. 6543–6553. PMLR (2020)
Ma, X., Huang, H., Wang, Y., Romano, S., Erfani, S., Bailey, J.: Normalized loss functions for deep learning with noisy labels · 2020
Later among the works it cites.
Signal Processing p. 107628 (2020)
Maggu, J., Majumdar, A., Chouzenoux, E., Chierchia, G.: Deeply transformed subspace clustering · 2020
Later among the works it cites.
IEEE Transactions on Neural Networks and Learning Systems (2020)
Peng, X., Feng, J., Zhou, J.T., Lei, Y., Yan, S.: Deep subspace clustering · 2020
Later among the works it cites.
Computer Science Review
Pourbahrami, S., Balafar, M.A., Khanli, L.M., Kakarash, Z.A.: A survey of neighborhood construction algorithms for clustering and classifying data points · 2020
Later among the works it cites.
Signal Processing
Pourkamali-Anaraki, F., Folberth, J., Becker, S.: Efficient solvers for sparse subspace clustering · 2020
Later among the works it cites.
Information Sciences (2020)
Ren, Z., Lei, H., Sun, Q., Yang, C.: Simultaneous learning coefficient matrix and affinity graph for multiple kernel clustering · 2020
Later among the works it cites.
Knowledge-Based Systems
Ren, Z., Li, H., Yang, C., Sun, Q.: Multiple kernel subspace clustering with local structural graph and low-rank consensus kernel learning · 2020
Later among the works it cites.
IEEE Transactions on Neural Networks and Learning Systems (2020)
Xie, Y., Liu, J., Qu, Y., Tao, D., Zhang, W., Dai, L., Ma, L.: Robust kernelized multiview self-representation for subspace clustering · 2020
Later among the works it cites.
Information Sciences
Xue, X., Zhang, X., Feng, X., Sun, H., Chen, W., Liu, Z.: Robust subspace clustering based on non-convex low-rank approximation and adaptive kernel · 2020
Later among the works it cites.
IEEE Transactions on Knowledge and Data Engineering (2020)
Yu, Z., Zhang, Z., Cao, W., Liu, C., Chen, J.P., San Wong, H.: Gan-based enhanced deep subspace clustering networks · 2020
Later among the works it cites.
Knowledge-Based Systems
Zhang, G.Y., Zhou, Y.R., He, X.Y., Wang, C.D., Huang, D.: One-step kernel multi-view subspace clustering · 2020
Later among the works it cites.
Expert Systems with Applications p. 113913 (2020)
Zhang, G.Y., Zhou, Y.R., Wang, C.D., Huang, D., He, X.Y.: Joint representation learning for multi-view subspace clustering · 2020
Later among the works it cites.
IEEE Access
Zheng, Y., Zhang, X., Xu, Y., Qin, M., Ren, Z., Xue, X.: Robust multi-view subspace clustering via weighted multi-kernel learning and co-regularization · 2020
Later among the works it cites.
Information Sciences
Zhong, G., Pun, C.M.: Nonnegative self-representation with a fixed rank constraint for subspace clustering · 2020
Later among the works it cites.
Knowledge-Based Systems
Zhu, W., Peng, B.: Sparse and low-rank regularized deep subspace clustering · 2020
Later among the works it cites.