{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,22]],"date-time":"2026-01-22T23:56:06Z","timestamp":1769126166255,"version":"3.49.0"},"reference-count":34,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2023,12,19]],"date-time":"2023-12-19T00:00:00Z","timestamp":1702944000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,12,19]],"date-time":"2023-12-19T00:00:00Z","timestamp":1702944000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"name":"the Natural Science Research Project of Anhui Province University","award":["No. 2022AH050970"],"award-info":[{"award-number":["No. 2022AH050970"]}]},{"name":"the Open Research Fund of Anhui Province Key Laboratory of Machine Vision Inspection","award":["No. KLMVI-2023-HIT-07"],"award-info":[{"award-number":["No. KLMVI-2023-HIT-07"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["No. 61976005"],"award-info":[{"award-number":["No. 61976005"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Machine Vision and Applications"],"published-print":{"date-parts":[[2024,1]]},"DOI":"10.1007\/s00138-023-01487-y","type":"journal-article","created":{"date-parts":[[2023,12,19]],"date-time":"2023-12-19T11:02:10Z","timestamp":1702983730000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["A fast anchor-based graph-regularized low-rank representation approach for large-scale subspace clustering"],"prefix":"10.1007","volume":"35","author":[{"given":"Lili","family":"Fan","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Guifu","family":"Lu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ganyi","family":"Tang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yong","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2023,12,19]]},"reference":[{"key":"1487_CR1","doi-asserted-by":"crossref","unstructured":"Feng, J. S., Lin, Z. C., Xu, H., et al.: Robust subspace segmentation with block-diagonal prior. In: Proceedings of the IEEE International Conference on Computer Vision and Pattern Recognition, Columbus, USA, 2014, pp. 3818\u20133825","DOI":"10.1109\/CVPR.2014.482"},{"key":"1487_CR2","doi-asserted-by":"publisher","first-page":"46","DOI":"10.1016\/j.knosys.2017.02.031","volume":"127","author":"J Chen","year":"2017","unstructured":"Chen, J., Mao, H., Sang, Y.S., et al.: Subspace clustering using a symmetric low-rank representation. Knowl. Based Syst. 127, 46\u201357 (2017)","journal-title":"Knowl. Based Syst."},{"issue":"4","key":"1487_CR3","doi-asserted-by":"publisher","first-page":"691","DOI":"10.1109\/JSTSP.2015.2402643","volume":"9","author":"VM Patel","year":"2015","unstructured":"Patel, V.M., Nguyen, H.V., Vidal, R.: Latent space sparse and low-rank subspace clustering. IEEE J. Selected Top. Signal Process. 9(4), 691\u2013701 (2015)","journal-title":"IEEE J. Selected Top. Signal Process."},{"issue":"8","key":"1487_CR4","doi-asserted-by":"publisher","first-page":"1532","DOI":"10.1109\/TKDE.2018.2858782","volume":"31","author":"XF Zhu","year":"2019","unstructured":"Zhu, X.F., Zhang, S.C., Li, Y.G., et al.: Low-rank sparse subspace for spectral clustering. IEEE Trans. Knowl. Data Eng. 31(8), 1532\u20131543 (2019)","journal-title":"IEEE Trans. Knowl. Data Eng."},{"issue":"9","key":"1487_CR5","doi-asserted-by":"publisher","first-page":"4022","DOI":"10.1109\/TIP.2014.2343458","volume":"23","author":"JM Liu","year":"2014","unstructured":"Liu, J.M., Chen, Y.J., Zhang, J.S., et al.: Enhancing low-rank subspace clustering by manifold regularization. IEEE Trans. Image Process. 23(9), 4022\u20134030 (2014)","journal-title":"IEEE Trans. Image Process."},{"issue":"3","key":"1487_CR6","doi-asserted-by":"publisher","first-page":"504","DOI":"10.1109\/TPAMI.2015.2462360","volume":"38","author":"M Yin","year":"2016","unstructured":"Yin, M., Gao, J.B., Lin, Z.C.: Laplacian regularized low-rank representation and its applications. IEEE Trans. Pattern Anal. Mach. Intell. 38(3), 504\u2013517 (2016)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"issue":"6","key":"1487_CR7","doi-asserted-by":"publisher","first-page":"1569","DOI":"10.1007\/s00500-015-1869-0","volume":"21","author":"W He","year":"2017","unstructured":"He, W., Chen, J., Zhang, W.H.: Low-rank representation with graph regularization for subspace clustering. Soft. Comput. 21(6), 1569\u20131581 (2017)","journal-title":"Soft. Comput."},{"key":"1487_CR8","doi-asserted-by":"crossref","unstructured":"Belabbas, M.A., Wolfe, P.J.: Fast low-rank approximation for covariance matrices. In: 2007 2nd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMPSAP), 2007, pp. 293-296","DOI":"10.1109\/CAMSAP.2007.4498023"},{"issue":"13","key":"1487_CR9","doi-asserted-by":"publisher","first-page":"936","DOI":"10.1049\/el.2014.1396","volume":"50","author":"H Zhang","year":"2014","unstructured":"Zhang, H., Yi, Z., Peng, X.: fLRR: fast low-rank representation using Frobenius-norm. Electron. Lett. 50(13), 936\u2013938 (2014)","journal-title":"Electron. Lett."},{"key":"1487_CR10","doi-asserted-by":"crossref","unstructured":"Chen, J., Cao, H., Chen, S., et al.: A fast low rank approximation and sparsity representation approach to hyperspectral anomaly detection. In: IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2020","DOI":"10.1109\/IGARSS39084.2020.9324251"},{"key":"1487_CR11","unstructured":"Lin, Z., Liu, R., Su, Z.: Linearized alternating direction method with adaptive penalty for low-rank representation. In: Advances in Neural Information Processing Systems 24 (NIPS 2011), Granada, Spain, 2011, pp. 612\u2013620"},{"issue":"5","key":"1487_CR12","doi-asserted-by":"publisher","first-page":"1293","DOI":"10.1109\/TKDE.2013.114","volume":"26","author":"X Zhang","year":"2014","unstructured":"Zhang, X., Sun, F., et al.: Fast low-rank subspace segmentation. IEEE Trans. Knowl. Data Eng. 26(5), 1293\u20131297 (2014)","journal-title":"IEEE Trans. Knowl. Data Eng."},{"key":"1487_CR13","doi-asserted-by":"crossref","unstructured":"Xiao, S., Wen, L., Dong, X., et al.: FaLRR: A fast low rank representation solver. In: Conf. on Computer Vision and Pattern Recognition (CVPR), Boston, Massachusetts, June 2015, pp. 4612\u20134620","DOI":"10.1109\/CVPR.2015.7299092"},{"issue":"1","key":"1487_CR14","doi-asserted-by":"publisher","first-page":"171","DOI":"10.1109\/TPAMI.2012.88","volume":"35","author":"G Liu","year":"2013","unstructured":"Liu, G., Lin, Z., Yan, S., Sun, J., Yu, Y., Ma, Y.: Robust recovery of subspace structures by low-rank representation. IEEE Trans. Pattern Anal. Mach. Intell. 35(1), 171\u2013184 (2013)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"issue":"8","key":"1487_CR15","doi-asserted-by":"publisher","first-page":"1475","DOI":"10.1049\/iet-ipr.2018.6596","volume":"14","author":"D Xie","year":"2020","unstructured":"Xie, D., Nie, F., Gao, Q., Xiao, S.: Fast algorithm for large-scale subspace clustering by LRR. IET Image Process. 14(8), 1475\u20131480 (2020)","journal-title":"IET Image Process."},{"key":"1487_CR16","doi-asserted-by":"crossref","unstructured":"Shen, Q., Liang, Y., Yi, S. and Zhao, J.: Fast universal low rank representation. IEEE Trans. Circuits Syst. Video Technol., May. 2021","DOI":"10.1109\/TCSVT.2021.3078327"},{"key":"1487_CR17","unstructured":"Shen, Q., Yi, S., Liang, Y., Chen, Y. and Liu, W.: Bilateral fast low-rank representation with equivalent transformation for subspace clustering. In: IEEE Transactions on Multimedia, September, 2022, pp. 1\u201313"},{"key":"1487_CR18","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2022.3142806","author":"B Yang","year":"2022","unstructured":"Yang, B., Zhang, X., Nie, F., Chen, B., Wang, F., Nan, Z., Zheng, N.: ECCA: Efficient correntropy-based clustering algorithm with orthogonal concept factorization. IEEE Trans. Neural Netw. Learn. Syst. (2022). https:\/\/doi.org\/10.1109\/TNNLS.2022.3142806","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"key":"1487_CR19","doi-asserted-by":"publisher","first-page":"72","DOI":"10.1016\/j.neucom.2022.05.011","volume":"496","author":"B Yang","year":"2022","unstructured":"Yang, B., Wu, J., Sun, A., Gao, N., Zhang, X.: Robust landmark graph-based clustering for high-dimensional data. Neurocomputing 496, 72\u201384 (2022)","journal-title":"Neurocomputing"},{"key":"1487_CR20","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2022.3219131","author":"F Nie","year":"2022","unstructured":"Nie, F., Xue, J., Wang, R., Zhang, L., Li, X.: Fast clustering by directly solving bipartite graph clustering problem. IEEE Trans. Neural Netw. Learn. Syst. (2022). https:\/\/doi.org\/10.1109\/TNNLS.2022.3219131","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"issue":"9","key":"1487_CR21","doi-asserted-by":"publisher","first-page":"4199","DOI":"10.1109\/TNNLS.2021.3056080","volume":"33","author":"J Wang","year":"2022","unstructured":"Wang, J., Ma, Z., Nie, F., Li, X.: Fast self-supervised clustering with anchor graph. IEEE Trans. Neural Netw. Learn. Syst. 33(9), 4199\u20134212 (2022)","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"key":"1487_CR22","doi-asserted-by":"crossref","unstructured":"Xu, S., Shen, W. W.: Hyper-Laplacian regularized low-rank collaborative representation classification. In: 2020 12th International Conference on Advanced Computational Intelligence (ICACI), August 14\u201316, 2020, Dali, China. New York: IEEE Press, 2020, pp. 512\u2013516","DOI":"10.1109\/ICACI49185.2020.9177524"},{"issue":"8","key":"1487_CR23","doi-asserted-by":"publisher","first-page":"1548","DOI":"10.1109\/TPAMI.2010.231","volume":"33","author":"D Cai","year":"2011","unstructured":"Cai, D., He, X., Han, J., et al.: Graph regularized nonnegative matrix factorization for data representation. IEEE Trans. Pattern Anal. Mach. Intell. 33(8), 1548\u20131560 (2011)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"1487_CR24","doi-asserted-by":"crossref","unstructured":"Belkin, M., and Niyogi, P.: Laplacian eigenmaps and spectral techniques for embedding and clustering. In: Advances in Neural Information Processing Systems. Cambridge, MA: MIT Press, 2001, pp. 585\u2013591","DOI":"10.7551\/mitpress\/1120.003.0080"},{"issue":"7","key":"1487_CR25","doi-asserted-by":"publisher","first-page":"4009","DOI":"10.1109\/TGRS.2012.2226730","volume":"51","author":"X Lu","year":"2013","unstructured":"Lu, X., Wang, Y., Yuan, Y.: Graph-regularized low-rank representation for destriping of hyperspectral images. IEEE Trans. Geosci. Remote Sens. 51(7), 4009\u20134018 (2013)","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"issue":"8","key":"1487_CR26","doi-asserted-by":"publisher","first-page":"1669","DOI":"10.1109\/TCYB.2014.2358564","volume":"45","author":"D Cai","year":"2015","unstructured":"Cai, D., Chen, X.: Large scale spectral clustering via landmark based sparse representation. IEEE Trans. Cybern. 45(8), 1669\u20131680 (2015)","journal-title":"IEEE Trans. Cybern."},{"issue":"10","key":"1487_CR27","doi-asserted-by":"publisher","first-page":"7352","DOI":"10.1109\/TGRS.2019.2913004","volume":"57","author":"R Wang","year":"2019","unstructured":"Wang, R.: Scalable graph-based clustering with nonnegative relaxation for large hyperspectral image. IEEE Trans. Geosci. Remote Sens. 57(10), 7352\u20137364 (2019)","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"1487_CR28","doi-asserted-by":"publisher","first-page":"319","DOI":"10.1016\/j.patrec.2018.08.008","volume":"130","author":"F He","year":"2020","unstructured":"He, F., Wang, R., Jia, W.M.: Fast semi-supervised learning with anchor graph for large hyperspectral images. Pattern Recogn. Lett. 130, 319\u2013326 (2020)","journal-title":"Pattern Recogn. Lett."},{"issue":"4","key":"1487_CR29","doi-asserted-by":"publisher","first-page":"1956","DOI":"10.1137\/080738970","volume":"20","author":"JF Cai","year":"2008","unstructured":"Cai, J.F., Candes, E.J., Shen, Z.: A singular value thresholding algorithm for matrix completion. SIAM J. Optimization 20(4), 1956\u20131982 (2008)","journal-title":"SIAM J. Optimization"},{"key":"1487_CR30","unstructured":"Liu, W., He, J. and Chang, S. F.: Large graph construction for scalable semi-supervised learning. In: Proc. ICML, 2010, pp. 679\u2013686"},{"key":"1487_CR31","doi-asserted-by":"publisher","first-page":"2765","DOI":"10.1109\/TPAMI.2013.57","volume":"35","author":"E Elhamifar","year":"2013","unstructured":"Elhamifar, E., Vidal, R.: Sparse subspace clustering: algorithm, theory, and applications. IEEE Trans. Pattern Anal. Mach. Intell. 35, 2765\u20132781 (2013)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"1487_CR32","doi-asserted-by":"crossref","unstructured":"Lu, C., Min, H., Zhao, Z., Zhu, L., Huang, D. and Yan, S.: Robust and efficient subspace segmentation via least squares regression. In: Proceedings of the 12th European Conference on Computer Vision. Cham: Springer, 2012, pp. 347\u2013360","DOI":"10.1007\/978-3-642-33786-4_26"},{"key":"1487_CR33","doi-asserted-by":"publisher","first-page":"171","DOI":"10.1109\/TPAMI.2012.88","volume":"35","author":"G Liu","year":"2013","unstructured":"Liu, G., Lin, Z., Yan, S., Sun, J., Yu, Y., Ma, Y.: Robust recovery of subspace structures by low-rank representation. IEEE Trans. Pattern Anal. Mach. Intell. 35, 171\u2013184 (2013)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"1487_CR34","doi-asserted-by":"crossref","unstructured":"M. M. R. Khan, R. B. Arif, M. A. B. Siddique, and M. R. Oishe.: Study and observation of the variation of accuracies of KNN, SVM, LMNN, ENN algorithms on eleven different datasets from UCI machine learning repository. CoRR, vol. abs\/1809.06186, pp. 124\u2013129, Sep. 2018","DOI":"10.1109\/CEEICT.2018.8628041"}],"container-title":["Machine Vision and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00138-023-01487-y.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00138-023-01487-y\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00138-023-01487-y.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,1,23]],"date-time":"2024-01-23T09:07:52Z","timestamp":1706000872000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00138-023-01487-y"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,12,19]]},"references-count":34,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2024,1]]}},"alternative-id":["1487"],"URL":"https:\/\/doi.org\/10.1007\/s00138-023-01487-y","relation":{},"ISSN":["0932-8092","1432-1769"],"issn-type":[{"value":"0932-8092","type":"print"},{"value":"1432-1769","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,12,19]]},"assertion":[{"value":"2 July 2023","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"22 September 2023","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"28 October 2023","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"19 December 2023","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare no competing interests.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"15"}}