·424· 智能系统学报 第16卷 [9]YI Shuangyan,LAI Zhihui,HE Zhenyu,et al.Joint sparse classification of single facial images[J].IEEE transac- principal component analysis[J].Pattern recognition,2017, tions on pattern analysis and machine intelligence,1999, 61:524536. 21(12):1357-1362. [10]BENGIO Y.LOURADOUR J,COLLOBERT R.et al. [18]WRIGHT J,YANG A Y,GANESH A,et al.Robust face Curriculum learning[C]//Proceedings of the 26th Annual recognition via sparse representation.[J].IEEE transac- International Conference on Machine Learning.Montreal, tions on pattern analysis and machine intelligence,2009. 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USA.2015:2694-2700 [21]KUSSUL E,BAIDYK T.Improved method of handwrit- [13]YU Hao,WEN Guoqiu,GAN Jiangzhang,et al.Self- ten digit recognition tested on MNIST database[J].Image paced learning for K-means clustering algorithm[J].Pat- tern recognition letters,2020,132:69-75. and vision computing,2004,22(12):971-981. [14]HU Sixiu,PENG Jiangtao,FU Yingxiong,et al.Kernel 作者简介： joint sparse representation based on self-paced learning 许子微，硕士研究生，主要研究方 for hyperspectral image classification[].Remote sensing, 向为模式识别、图像处理。 2019,11(9):11141132. [15]HAJINEZHAD D,SHI Qingjiang.Alternating direction method of multipliers for a class of nonconvex bilinear optimization:convergence analysis and applications[J]. Journal of global optimization,2018,70(1):261-288. [16]HOU Chenping,NIE Feiping,YI Dongyun,et al.Feature 陈秀宏，教授，主要研究方向为数 字图像处理和模式识别、目标检测与 selection via joint embedding learning and sparse regres- 跟踪、优化理论与方法。参与国家自 sion[Cl//Proceedings of the 22nd International Joint Con- 然基金项目2项，主持省部级研究项 ference on Artificial Intelligence.Barcelona,Spain,2011: 目3项，省博土后基金1项。获得省 1324-1329 部级奖1项、校级教学成果奖1项、市 [17]LYONS M J.BUDYNEK J.AKAMATSU S.Automatic 厅级奖6项。发表学术论文120余篇。YI Shuangyan, LAI Zhihui, HE Zhenyu, et al. Joint sparse principal component analysis[J]. Pattern recognition, 2017, 61: 524–536. [9] BENGIO Y, LOURADOUR J, COLLOBERT R, et al. Curriculum learning[C]//Proceedings of the 26th Annual International Conference on Machine Learning. Montreal, Quebec, Canada, 2009: 41−48. [10] KUMAR M P, PACKER B, KOLLER D. Self-paced learning for latent variable models[C]//Proceedings of the 23rd International Conference on Neural Information Pro￾cessing Systems. Vancouver, British Columbia, Canada, 2010: 1189−1197. [11] JIANG Lu, MENG Deyu, ZHAO Qian, et al. Self-paced curriculum learning[C]//Proceedings of the 29th AAAI Conference on Artificial Intelligence. Austin, Texas, USA, 2015: 2694−2700. [12] YU Hao, WEN Guoqiu, GAN Jiangzhang, et al. Self￾paced learning for K-means clustering algorithm[J]. Pat￾tern recognition letters, 2020, 132: 69–75. [13] HU Sixiu, PENG Jiangtao, FU Yingxiong, et al. Kernel joint sparse representation based on self-paced learning for hyperspectral image classification[J]. Remote sensing, 2019, 11(9): 1114–1132. [14] HAJINEZHAD D, SHI Qingjiang. Alternating direction method of multipliers for a class of nonconvex bilinear optimization: convergence analysis and applications[J]. Journal of global optimization, 2018, 70(1): 261–288. [15] HOU Chenping, NIE Feiping, YI Dongyun, et al. Feature selection via joint embedding learning and sparse regres￾sion[C]//Proceedings of the 22nd International Joint Con￾ference on Artificial Intelligence. Barcelona, Spain, 2011: 1324−1329. [16] [17] LYONS M J, BUDYNEK J, AKAMATSU S. Automatic classification of single facial images[J]. IEEE transac￾tions on pattern analysis and machine intelligence, 1999, 21(12): 1357–1362. WRIGHT J, YANG A Y, GANESH A, et al. Robust face recognition via sparse representation.[J]. IEEE transac￾tions on pattern analysis and machine intelligence, 2009, 31(2):210-227. [18] JESORSKY O, KIRCHBERG K J, FRISCHHOLZ R W. Robust face detection using the hausdorff distance[C]// Proceedings of the 3rd International Conference on Au￾dio- and Video-Based Biometric Person Authentication. Halmstad, Sweden, 2001: 90−95. [19] ZHENG Miao, BU Jiajun, CHEN C, et al. Graph regular￾ized sparse coding for image representation[J]. IEEE transactions on image processing, 2011, 20(5): 1327–1336. [20] KUSSUL E, BAIDYK T. Improved method of handwrit￾ten digit recognition tested on MNIST database[J]. Image and vision computing, 2004, 22(12): 971–981. [21] 作者简介： 许子微，硕士研究生，主要研究方 向为模式识别、图像处理。 陈秀宏，教授，主要研究方向为数 字图像处理和模式识别、目标检测与 跟踪、优化理论与方法。参与国家自 然基金项目 2 项，主持省部级研究项 目 3 项，省博士后基金 1 项。获得省 部级奖 1 项、校级教学成果奖 1 项、市 厅级奖 6 项。发表学术论文 120 余篇。 ·424· 智 能 系 统 学 报 第 16 卷