{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,29]],"date-time":"2026-04-29T17:21:22Z","timestamp":1777483282718,"version":"3.51.4"},"reference-count":47,"publisher":"Springer Science and Business Media LLC","issue":"2","license":[{"start":{"date-parts":[[2019,7,17]],"date-time":"2019-07-17T00:00:00Z","timestamp":1563321600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2019,7,17]],"date-time":"2019-07-17T00:00:00Z","timestamp":1563321600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61732006"],"award-info":[{"award-number":["61732006"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61501230"],"award-info":[{"award-number":["61501230"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61876082"],"award-info":[{"award-number":["61876082"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61861130366"],"award-info":[{"award-number":["61861130366"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"National Science and Technology Major Project","award":["2018ZX10201002"],"award-info":[{"award-number":["2018ZX10201002"]}]},{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"crossref","award":["NP2018104"],"award-info":[{"award-number":["NP2018104"]}],"id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Int. J. Mach. Learn. & Cyber."],"published-print":{"date-parts":[[2020,2]]},"DOI":"10.1007\/s13042-019-00986-7","type":"journal-article","created":{"date-parts":[[2019,7,17]],"date-time":"2019-07-17T17:02:21Z","timestamp":1563382941000},"page":"463-474","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Adaptive feature weighting for robust Lp-norm sparse representation with application to biometric image classification"],"prefix":"10.1007","volume":"11","author":[{"given":"Qi","family":"Zhu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nuoya","family":"Xu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sheng-Jun","family":"Huang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jianjun","family":"Qian","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Daoqiang","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2019,7,17]]},"reference":[{"key":"986_CR1","doi-asserted-by":"publisher","first-page":"164","DOI":"10.1016\/j.neucom.2012.08.038","volume":"103","author":"Y Xu","year":"2013","unstructured":"Xu Y, Fan Z, Qiu M, Zhang D, Yang J-Y (2013) A sparse representation method of bimodal biometrics and palmprint recognition experiments. Neurocomputing 103:164\u2013171","journal-title":"Neurocomputing"},{"issue":"9","key":"986_CR2","doi-asserted-by":"publisher","first-page":"1864","DOI":"10.1109\/TPAMI.2012.30","volume":"34","author":"W Deng","year":"2012","unstructured":"Deng W, Hu J, Guo J (2012) Extended SRC: undersampled face recognition via intraclass variant dictionary. IEEE Trans Pattern Anal Mach Intell 34(9):1864\u20131870","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"issue":"2","key":"986_CR3","doi-asserted-by":"publisher","first-page":"210","DOI":"10.1109\/TPAMI.2008.79","volume":"31","author":"J Wright","year":"2009","unstructured":"Wright J, Yang AY, Ganesh A, Sastry SS, Ma Y (2009) Robust face recognition via sparse representation. IEEE Trans Pattern Anal Mach Intell 31(2):210\u2013227","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"986_CR4","doi-asserted-by":"publisher","first-page":"218","DOI":"10.1016\/j.neucom.2016.05.083","volume":"214","author":"S-J Wang","year":"2016","unstructured":"Wang S-J, Yan W-J, Sun T, Zhao G, Fu X (2016) Sparse tensor canonical correlation analysis for micro-expression recognition. Neurocomputing 214:218\u2013232","journal-title":"Neurocomputing"},{"key":"986_CR5","doi-asserted-by":"publisher","first-page":"260","DOI":"10.1016\/j.jvcir.2017.04.007","volume":"46","author":"F Cao","year":"2017","unstructured":"Cao F, Feng X, Zhao J (2017) Sparse representation for robust face recognition by dictionary decomposition. J Vis Commun Image Represent 46:260\u2013268","journal-title":"J Vis Commun Image Represent"},{"issue":"7","key":"986_CR6","doi-asserted-by":"publisher","first-page":"3111","DOI":"10.1109\/TNNLS.2017.2712801","volume":"29","author":"Z Zhang","year":"2018","unstructured":"Zhang Z, Xu Y, Shao L, Yang J (2018) Discriminative block-diagonal representation learning for image recognition. IEEE Trans Neural Netw Learn Syst 29(7):3111\u20133125","journal-title":"IEEE Trans Neural Netw Learn Syst"},{"issue":"4","key":"986_CR7","first-page":"1","volume":"6314","author":"S Gao","year":"2010","unstructured":"Gao S, Tsang IWH, Chia LT (2010) Kernel sparse representation for image classification and face recognition. LNCS 6314(4):1\u201314","journal-title":"LNCS"},{"issue":"11","key":"986_CR8","doi-asserted-by":"publisher","first-page":"2106","DOI":"10.1109\/TPAMI.2010.128","volume":"32","author":"I Naseem","year":"2010","unstructured":"Naseem I, Togneri R, Bennamoun M (2010) Linear regression for face recognition. IEEE Trans Pattern Anal Mach Intell 32(11):2106\u20132112","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"986_CR9","first-page":"2224","volume":"1","author":"M Yang","year":"2012","unstructured":"Yang M, Zhang L, Zhang D, Wang S (2012) Relaxed collaborative representation for pattern classification. Proc IEEE Comput Soc Conf Comput Vis Pattern Recognit 1:2224\u20132231","journal-title":"Proc IEEE Comput Soc Conf Comput Vis Pattern Recognit"},{"issue":"8","key":"986_CR10","first-page":"1432","volume":"44","author":"G Liu","year":"2010","unstructured":"Liu G, Lin Z, Liu G (2010) Robust subspace segmentation by low rank represention. Icml 44(8):1432\u20131445","journal-title":"Icml"},{"key":"986_CR11","doi-asserted-by":"publisher","first-page":"195","DOI":"10.1016\/j.bspc.2017.02.005","volume":"34","author":"J Jing Zong","year":"2017","unstructured":"Jing Zong J, Shuang Qiu T (2017) Medical image fusion based on sparse representation of classified image patches. Biomed Signal Process Control 34:195\u2013205","journal-title":"Biomed Signal Process Control"},{"key":"986_CR12","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.artmed.2017.03.006","volume":"79","author":"K Yan","year":"2017","unstructured":"Yan K, Xu Y, Fang X, Zheng C, Liu B (2017) Protein fold recognition based on sparse representation based classification. Artif Intell Med 79:1\u20138","journal-title":"Artif Intell Med"},{"key":"986_CR13","unstructured":"Zhang L, Yang M, Feng X (2011) Sparse representation or collaborative representation: which helps face recognition? In: 2011 International conference on computer vision, pp 471\u2013478"},{"issue":"10","key":"986_CR14","doi-asserted-by":"publisher","first-page":"185","DOI":"10.1007\/978-1-4419-9569-8_10","volume":"49","author":"PL Combettes","year":"2011","unstructured":"Combettes PL, Pesquet JC (2011) Proximal splitting methods in signal processing BT\u2014fixed-point algorithms for inverse problems. Fixed-Point Algorithms Inverse Probl 49(10):185\u2013212","journal-title":"Fixed-Point Algorithms Inverse Probl"},{"issue":"10","key":"986_CR15","doi-asserted-by":"publisher","first-page":"4735","DOI":"10.1109\/TSP.2011.2160058","volume":"59","author":"C Ekanadham","year":"2011","unstructured":"Ekanadham C, Tranchina D, Simoncelli EP (2011) Recovery of sparse translation-invariant signals with continuous basis pursuit. IEEE Trans Signal Process 59(10):4735\u20134744","journal-title":"IEEE Trans Signal Process"},{"key":"986_CR16","doi-asserted-by":"publisher","first-page":"8502","DOI":"10.1109\/ACCESS.2017.2695239","volume":"5","author":"Y Xu","year":"2017","unstructured":"Xu Y, Li Z, Yang J, Zhang D (2017) A survey of dictionary learning algorithms for face recognition. IEEE Access 5:8502\u20138514","journal-title":"IEEE Access"},{"key":"986_CR17","doi-asserted-by":"publisher","first-page":"490","DOI":"10.1109\/ACCESS.2015.2430359","volume":"3","author":"Z Zhang","year":"2015","unstructured":"Zhang Z, Xu Y, Yang J, Li X, Zhang D (2015) A survey of sparse representation: algorithms and applications. IEEE Access 3:490\u2013530","journal-title":"IEEE Access"},{"key":"986_CR18","doi-asserted-by":"crossref","unstructured":"Zheng L, Wang S, Liu Z, Tian Q (2013) Lp-norm IDF for large scale image search. In: 2013 IEEE conference on computer vision and pattern recognition, pp 1626\u20131633","DOI":"10.1109\/CVPR.2013.213"},{"issue":"5","key":"986_CR19","doi-asserted-by":"publisher","first-page":"1859","DOI":"10.1109\/TCYB.2018.2815559","volume":"49","author":"Y Lu","year":"2019","unstructured":"Lu Y, Lai Z, Li X, Wong WK, Yuan C, Zhang D (2019) Low-rank 2-D neighborhood preserving projection for enhanced robust image representation. IEEE Trans Cybern 49(5):1859\u20131872","journal-title":"IEEE Trans Cybern"},{"key":"986_CR20","unstructured":"Bengio Y, Louradour J, Collobert R, Weston J (2019) Curriculum learning. In: Proceedings of the 26th Annual International Conference on Machine Learning - ICML\u201909, pp 1\u20138"},{"key":"986_CR21","first-page":"1189","volume":"23","author":"MP Kumar","year":"2010","unstructured":"Kumar MP, Packer B, Koller D (2010) Self-paced learning for latent variable models. Adv Neural Inf Process Syst 23:1189\u20131197","journal-title":"Adv Neural Inf Process Syst"},{"key":"986_CR22","doi-asserted-by":"crossref","unstructured":"Zhao Q, Meng D, Jiang L, Xie Q, Xu Z, Hauptmann AG (2015) Self-paced learning for matrix factorization. AAAI pp. 3196\u20133202","DOI":"10.1609\/aaai.v29i1.9584"},{"key":"986_CR23","unstructured":"Jiang L, Meng D, Yu SI, Lan Z, Shan S, Hauptmann A (2014) Self-paced learning with diversity. Adv Neural Inf Process Syst, pp. 2078\u20132086"},{"key":"986_CR24","doi-asserted-by":"crossref","unstructured":"Jiang L, Meng D, Zhao Q, Shan S, Hauptmann AG (2015) Self-paced curriculum learning. AAAI, pp 1\u201330","DOI":"10.1609\/aaai.v29i1.9608"},{"issue":"1","key":"986_CR25","doi-asserted-by":"publisher","first-page":"7","DOI":"10.1109\/TPAMI.2017.2652459","volume":"40","author":"L Lin","year":"2018","unstructured":"Lin L, Wang K, Meng D, Zuo W, Zhang L (2018) Active self-paced learning for cost-effective and progressive face identification. IEEE Trans Pattern Anal Mach Intell 40(1):7\u201319","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"986_CR26","doi-asserted-by":"crossref","unstructured":"Kumar MP, Turki H, Preston D, Koller D (2011) Learning specific-class segmentation from diverse data. In: Proceedings of the IEEE international conference on computer vision, pp. 1800\u20131807","DOI":"10.1109\/ICCV.2011.6126446"},{"key":"986_CR27","unstructured":"Lee YJ, Grauman K (2011) Learning the easy things first: self-paced visual category discovery. In: Proceedings of the IEEE computer society conference on computer vision and pattern recognition, pp. 1721\u20131728"},{"issue":"1\u20132","key":"986_CR28","doi-asserted-by":"publisher","first-page":"237","DOI":"10.1016\/S0304-3975(97)00115-1","volume":"209","author":"E Amaldi","year":"1998","unstructured":"Amaldi E, Kann V (1998) On the approximability of minimizing nonzero variables or unsatisfied relations in linear systems. Theor Comput Sci 209(1\u20132):237\u2013260","journal-title":"Theor Comput Sci"},{"issue":"3","key":"986_CR29","doi-asserted-by":"publisher","first-page":"1466","DOI":"10.1109\/TIP.2017.2651396","volume":"26","author":"Z Zhang","year":"2017","unstructured":"Zhang Z, Lai Z, Xu Y, Shao L, Wu J, Xie G-S (2017) Discriminative elastic-net regularized linear regression. IEEE Trans Image Process 26(3):1466\u20131481","journal-title":"IEEE Trans Image Process"},{"issue":"6","key":"986_CR30","doi-asserted-by":"publisher","first-page":"797","DOI":"10.1002\/cpa.20132","volume":"59","author":"DL Donoho","year":"2006","unstructured":"Donoho DL (2006) For most large underdetermined systems of linear equations the minimal l1-norm solution is also the sparsest solution. Commun Pure Appl Math 59(6):797\u2013829","journal-title":"Commun Pure Appl Math"},{"issue":"4","key":"986_CR31","doi-asserted-by":"publisher","first-page":"941","DOI":"10.1109\/TCSVT.2018.2822761","volume":"29","author":"Y Lu","year":"2019","unstructured":"Lu Y, Yuan C, Lai Z, Li X, Zhang D, Wong WK (2019) Horizontal and vertical nuclear norm-based 2DLDA for image representation. IEEE Trans Circuits Syst Video Technol 29(4):941\u2013955","journal-title":"IEEE Trans Circuits Syst Video Technol"},{"issue":"2","key":"986_CR32","doi-asserted-by":"publisher","first-page":"187","DOI":"10.1007\/BF00939667","volume":"78","author":"CA Floudas","year":"1993","unstructured":"Floudas CA, Visweswaran V (1993) Primal-relaxed dual global optimization approach. J Optim Theory Appl 78(2):187\u2013225","journal-title":"J Optim Theory Appl"},{"issue":"8","key":"986_CR33","doi-asserted-by":"publisher","first-page":"1900","DOI":"10.1109\/TCYB.2015.2457611","volume":"46","author":"Y Lu","year":"2016","unstructured":"Lu Y, Lai Z, Xu Y, Li X, Zhang D, Yuan C (2016) Low-rank preserving projections. IEEE Trans Cybern 46(8):1900\u20131913","journal-title":"IEEE Trans Cybern"},{"key":"986_CR34","doi-asserted-by":"crossref","unstructured":"Jiang L, Meng D, Mitamura T, Hauptmann AG (2014) Easy samples first. In: Proceedings of the ACM international conference on multimedia\u2014MM\u201914, pp. 547\u2013556","DOI":"10.1145\/2647868.2654918"},{"key":"986_CR35","doi-asserted-by":"publisher","first-page":"104","DOI":"10.1016\/j.neucom.2015.08.111","volume":"195","author":"M Zhang","year":"2016","unstructured":"Zhang M, Yang Y, Zhang H, Shen F, Zhang D (2016) L2, p-norm and sample constraint based feature selection and classification for AD diagnosis. Neurocomputing 195:104\u2013111","journal-title":"Neurocomputing"},{"key":"986_CR36","doi-asserted-by":"crossref","unstructured":"Saab R, Chartrand R, Yilmaz O (2008) Stable sparse approximations via nonconvex optimization. In: 2008 IEEE international conference on acoustics, speech and signal processing, pp. 3885\u20133888","DOI":"10.1109\/ICASSP.2008.4518502"},{"issue":"10","key":"986_CR37","doi-asserted-by":"publisher","first-page":"707","DOI":"10.1109\/LSP.2007.898300","volume":"14","author":"R Chartrand","year":"2007","unstructured":"Chartrand R (2007) Exact reconstruction of sparse signals via nonconvex minimization. IEEE Signal Process Lett 14(10):707\u2013710","journal-title":"IEEE Signal Process Lett"},{"key":"986_CR38","doi-asserted-by":"crossref","unstructured":"Chartrand R, Yin W (2008) Iteratively reweighted algorithms for compressive sensing. In: 2008 IEEE international conference on acoustics, speech and signal processing, pp. 3869\u20133872","DOI":"10.1109\/ICASSP.2008.4518498"},{"issue":"3","key":"986_CR39","first-page":"889","volume":"3","author":"R Chartrand","year":"2007","unstructured":"Chartrand R (2007) Nonconvex compressed sensing and error correction. ICASSP IEEE Int Conf Acoust Speech Signal Process Proc 3(3):889\u2013892","journal-title":"ICASSP IEEE Int Conf Acoust Speech Signal Process Proc"},{"issue":"10","key":"986_CR40","doi-asserted-by":"publisher","first-page":"4645","DOI":"10.1109\/TNNLS.2017.2772264","volume":"29","author":"Z Zhang","year":"2018","unstructured":"Zhang Z, Shao L, Xu Y, Liu L, Yang J (2018) Marginal representation learning with graph structure self-adaptation. IEEE Trans Neural Netw Learn Syst 29(10):4645\u20134659","journal-title":"IEEE Trans Neural Netw Learn Syst"},{"key":"986_CR41","unstructured":"\u201cPolyU multispectral palmprint Database.\u201d [Online]. Available: http:\/\/www.comp.polyu.edu.hk\/~biometrics\/MultispectralPalmprint\/MSP.htm"},{"key":"986_CR42","unstructured":"\u201cPolyU FKP Database.\u201d [Online]. Available: http:\/\/www.comp.polyu.edu.hk\/~biometrics\/FKP\/polyudb.htm"},{"key":"986_CR43","unstructured":"Martinez AM, Benavente R (1998) The AR face database"},{"issue":"2","key":"986_CR44","doi-asserted-by":"publisher","first-page":"210","DOI":"10.1109\/TPAMI.2008.79","volume":"31","author":"J Wright","year":"2009","unstructured":"Wright J, Yang AY, Ganesh A, Sastry SS, Ma Y (2009) Sparsity and robustness in face recognition. IEEE Trans Pattern Anal Mach Intell 31(2):210\u2013227","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"issue":"3","key":"986_CR45","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/1970392.1970395","volume":"58","author":"EJ Cand\u00e8s","year":"2011","unstructured":"Cand\u00e8s EJ et al (2011) Robust principal component analysis? J ACM 58(3):1\u201337","journal-title":"J ACM"},{"key":"986_CR46","doi-asserted-by":"crossref","unstructured":"Liu G, Yan S (2011) Latent low-rank representation for subspace segmentation and feature extraction. In: 2011 international conference on computer vision, pp. 1615\u20131622","DOI":"10.1109\/ICCV.2011.6126422"},{"issue":"9","key":"986_CR47","doi-asserted-by":"publisher","first-page":"1255","DOI":"10.1109\/TCSVT.2011.2138790","volume":"21","author":"Y Xu","year":"2011","unstructured":"Xu Y, Zhang D, Yang J, Yang JY (2011) A two-phase test sample sparse representation method for use with face recognition. IEEE Trans Circuits Syst Video Technol 21(9):1255\u20131262","journal-title":"IEEE Trans Circuits Syst Video Technol"}],"container-title":["International Journal of Machine Learning and Cybernetics"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s13042-019-00986-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s13042-019-00986-7\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s13042-019-00986-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,9,24]],"date-time":"2022-09-24T03:00:20Z","timestamp":1663988420000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s13042-019-00986-7"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,7,17]]},"references-count":47,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2020,2]]}},"alternative-id":["986"],"URL":"https:\/\/doi.org\/10.1007\/s13042-019-00986-7","relation":{},"ISSN":["1868-8071","1868-808X"],"issn-type":[{"value":"1868-8071","type":"print"},{"value":"1868-808X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,7,17]]},"assertion":[{"value":"4 August 2018","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"11 July 2019","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"17 July 2019","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}