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第5期 朱换荣，等：面向局部线性回归分类器的判别分析方法 ·965· [9]ZOU Quan,ZENG Jiancang,CAO Liujuan,et al.A novel ceedings of 2007 IEEE Conference on Computer Vision features ranking metric with application to scalable visual and Pattern Recognition.Minneapolis,USA,2007:1-8. and bioinformatics data classification[J].Neurocomputing, [21]NGO TT,BELLALIJ M,SAAD Y.The trace ratio op- 2016,173:346-354. timization problem[J].SIAM review,2012,54(3): [10]LI Tao,ZHU Shenghuo,OGIHARA M.Using discrimin- 545-569. ant analysis for multi-class classification:an experiment- [22]JIANG Wenhao,CHUNG Fulai.A trace ratio maximiza- al investigation[J].Knowledge and information systems, tion approach to multiple kernel-based dimensionality re 2006,10(4:453-472. duction[J].Neural networks,2014,49:96-106 [11]AMATRIAIN X,PUJOL J M.Data mining methods for [23]WEN Zaiwen,YIN Wotao.A feasible method for optim- recommender systems[MJ//RICCI F,ROKACH L,SHA- ization with orthogonality constraints[J].Mathematical PIRA B.Recommender Systems Handbook.Boston,MA: programming,2013,142(1/2):397-434. Springer,2015:227-262. [24]CHEN Yi,JIN Zhong.Reconstructive discriminant ana- [12]RAUDYS S J,JAIN A K.Small sample size effects in lysis:a feature extraction method induced from linear re- statistical pattern recognition:recommendations for prac- gression classification[J].Neurocomputing,2012,87: titioners[J.IEEE transactions on pattern analysis and ma- 41-50. chine intelligence,1991,13(3):252-264 [25]COVER T,HART P.Nearest neighbor pattern classifica- [13]TURK M,PENTLAND A.Eigenfaces for recognition[J]. tion[J].IEEE transactions on information theory,1967, Journal of cognitive neuroscience,1991,3(1):71-86 13(121-27. [14]BELHUMEUR P N,HESPANHA J P,KRIEGMAN D J. Eigenfaces vs.Fisherfaces:recognition using class specif- [26]ZHANG Daoqiang,CHEN Songcan,ZHOU Zhihua. Learning the kernel parameters in kernel minimum dis- ic linear projection[J].IEEE transactions on pattern ana- lysis and machine intelligence,1997,19(7):711-720. tance classifier[J].Pattern recognition,2006,39(1): 133-135. [15]HE Xiaofei,YAN Shuicheng,HU Yuxiao,et al.Face re- cognition using laplacianfaces[J].IEEE transactions on 作者简介： pattern analysis and machine intelligence,2005,27(3): 朱换荣，女，1994年生，硕士研究 328-340. 生，主要研究方向为机器学习、人脸 [16]ZHANG Lei,YANG Meng,FENG Xiangchu.Sparse rep- 识别。 resentation or collaborative representation:which helps face recognition?[C]//Proceedings of 2011 International Conference on Computer Vision.Barcelona,Spain,2011: 471-478. [17]NASEEM I,TOGNERI R,BENNAMOUN M.Linear re- 郑智超，男，1992年生，博士研究 gression for face recognition[J].IEEE transactions on pat- 生，主要研究方向为人脸识别、子空间 tern analysis and machine intelligence,2010,32(11): 学习。 2106-2112. [18]BROWN D,LI Hanxi,GAO Yongsheng.Locality-regu- larized linear regression for face recognition[Cl//Proceed- ings of the 21st International Conference on Pattern Re- 孙怀江，男.1968年生，教授，博 cognition.Tsukuba,Japan,2012:1586-1589 士生导师，主要研究方向为神经网络 [19]HUANG Pu,LI Tao,SHU Zhengiu,et al.Locality-regu- 与机器学习、人体运动分析与合成、多 larized linear regression discriminant analysis for feature 媒体与虚拟现实、图像处理与计算机 extraction[J].Information sciences,2018,429:164-176. 视觉。曾主持或参与完成国家级项目 [20]WANG Huan,YAN Shuisheng,XU Dong,et al.Trace ra- 3项，省部级项目3项，获省部级科技 tio vs.Ratio trace for dimensionality reduction[C]//Pro- 进步二等奖1项。发表学术论文80余篇。ZOU Quan, ZENG Jiancang, CAO Liujuan, et al. A novel features ranking metric with application to scalable visual and bioinformatics data classification[J]. Neurocomputing, 2016, 173: 346–354. [9] LI Tao, ZHU Shenghuo, OGIHARA M. Using discriminant analysis for multi-class classification: an experimental investigation[J]. Knowledge and information systems, 2006, 10(4): 453–472. [10] AMATRIAIN X, PUJOL J M. Data mining methods for recommender systems[M]//RICCI F, ROKACH L, SHAPIRA B. Recommender Systems Handbook. Boston, MA: Springer, 2015: 227–262. [11] RAUDYS S J, JAIN A K. Small sample size effects in statistical pattern recognition: recommendations for practitioners[J]. IEEE transactions on pattern analysis and machine intelligence, 1991, 13(3): 252–264. [12] TURK M, PENTLAND A. Eigenfaces for recognition[J]. Journal of cognitive neuroscience, 1991, 3(1): 71–86. [13] BELHUMEUR P N, HESPANHA J P, KRIEGMAN D J. Eigenfaces vs. Fisherfaces: recognition using class specific linear projection[J]. IEEE transactions on pattern analysis and machine intelligence, 1997, 19(7): 711–720. [14] HE Xiaofei, YAN Shuicheng, HU Yuxiao, et al. Face recognition using laplacianfaces[J]. IEEE transactions on pattern analysis and machine intelligence, 2005, 27(3): 328–340. [15] ZHANG Lei, YANG Meng, FENG Xiangchu. Sparse representation or collaborative representation: which helps face recognition?[C]//Proceedings of 2011 International Conference on Computer Vision. Barcelona, Spain, 2011: 471–478. [16] NASEEM I, TOGNERI R, BENNAMOUN M. Linear regression for face recognition[J]. IEEE transactions on pattern analysis and machine intelligence, 2010, 32(11): 2106–2112. [17] BROWN D, LI Hanxi, GAO Yongsheng. Locality-regularized linear regression for face recognition[C]//Proceedings of the 21st International Conference on Pattern Recognition. Tsukuba, Japan, 2012: 1586–1589. [18] HUANG Pu, LI Tao, SHU Zhenqiu, et al. Locality-regularized linear regression discriminant analysis for feature extraction[J]. Information sciences, 2018, 429: 164–176. [19] WANG Huan, YAN Shuisheng, XU Dong, et al. Trace ratio vs. Ratio trace for dimensionality reduction[C]//Pro- [20] ceedings of 2007 IEEE Conference on Computer Vision and Pattern Recognition. Minneapolis, USA, 2007: 1–8. NGO T T, BELLALIJ M, SAAD Y. The trace ratio optimization problem[J]. SIAM review, 2012, 54(3): 545–569. [21] JIANG Wenhao, CHUNG Fulai. A trace ratio maximization approach to multiple kernel-based dimensionality reduction[J]. Neural networks, 2014, 49: 96–106. [22] WEN Zaiwen, YIN Wotao. A feasible method for optimization with orthogonality constraints[J]. Mathematical programming, 2013, 142(1/2): 397–434. [23] CHEN Yi, JIN Zhong. Reconstructive discriminant analysis: a feature extraction method induced from linear regression classification[J]. Neurocomputing, 2012, 87: 41–50. [24] COVER T, HART P. Nearest neighbor pattern classification[J]. IEEE transactions on information theory, 1967, 13(1): 21–27. [25] ZHANG Daoqiang, CHEN Songcan, ZHOU Zhihua. Learning the kernel parameters in kernel minimum distance classifier[J]. Pattern recognition, 2006, 39(1): 133–135. [26] 作者简介： 朱换荣，女，1994 年生，硕士研究 生，主要研究方向为机器学习、人脸 识别。 郑智超，男，1992 年生，博士研究 生，主要研究方向为人脸识别、子空间 学习。 孙怀江，男，1968 年生，教授，博 士生导师，主要研究方向为神经网络 与机器学习、人体运动分析与合成、多 媒体与虚拟现实、图像处理与计算机 视觉。曾主持或参与完成国家级项目 3 项，省部级项目 3 项，获省部级科技 进步二等奖1项。发表学术论文80余篇。 第 5 期 朱换荣，等：面向局部线性回归分类器的判别分析方法 ·965·