Roweis S T,Saul L K. Nonlinear Dimensionality Reduction by Locally Linear Embedding. Science,2000,290(5500): 2323-2326
[2]
Belkin M,Niyogi P. Laplacian Eigenmaps for Dimensionality Reduction and Data Representation. Neural Computation,2003,15(6): 1373-1396
[3]
Zhang Z Y,Zha H Y. Principal Manifolds and Nonlinear Dimensionality Reduction via Tangent Space Alignment. SIAM Journal on Scientific Computing,2005,26(1): 313-338
[4]
He Xiaofei,Niyogi P. Locality Preserving Projections // Proc of the Conference on Advances in Neural Information Processing System. Vancouver,Canada,2003: 135-160
[5]
He Xiaofei,Cai Deng,Yan Shuicheng,et al. Neighborhood Preserving Embedding // Proc of the 10th IEEE International Conference on Computer Vision. Beijing,China,2005,Ⅱ: 1208-1213
[6]
Zhang Tianhao,Yang Jie,Zhao Deli,et al. Linear Local Tangent Space Alignment and Application to Face Recognition.Neurocomputing,2007,70(7/8/9): 1547-1553
[7]
Han P Y,Jin A T B,Abas F S. Neighborhood Preserving Discriminant Embedding in Face Recognition. Journal of Visual Communication and Image Representation,2009,20(8): 532-542
[8]
Lai Z J,Jin Z,Wong W K.Tangent Space Discriminant Analysis for Feature Extraction // Proc of the 17th IEEE International Conference on Image Processing. Hong Kong,China,2010: 3793-3796
[9]
Huang Hong,Li Jianwei,Liu Jiamin. Enhanced Semi-Supervised Local Fisher Discriminant Analysis for Face Recognition. Future Generation Computer Systems,2012,28(1): 244-253
[10]
Wang Wenjun,Zhang Junying. Kernel Based Class-Wise Non-Locality Preserving Projection. Pattern Recognition and Artificial Intelligence,2009,22(5): 769-773 (in Chinese)(王文俊,张军英.基于核的类别非局保留投影.模式识别与人工智能,2009,22(5): 769-773)
[11]
Yang W K,Sun C Y,Yang J Y,et al. Face Recognition Using Kernel UDP. Neural Processing Letters,2011,34(2): 177-192
Baudat G,Anouar F. Generalized Discriminant Analysis Using a Kernel Approach. Neural Computation,2000,12(10): 2385-2404
[14]
Wang Qingjun,Zhang Rubo,Pan Haiwei. Kernel Orthogonal Unsupervised Discriminant Projection with Applications to Face Recognition.Journal of Computer-Aided Design Computer Graphics,2010,22(10): 1783-1787 (in Chinese)(王庆军,张汝波,潘海为.核正交UDP及其在人脸识别中的应用.计算机辅助设计与图形学学报,2010,22(10): 1783-1787)
[15]
Lin Yu′e,Gu Guochang,Liu Haibo,et al. A Kernel Orthogonal Discriminant Locality Preserving Projections Method. Acta Electronica Sinica,2010,38(4): 979-982 (in Chinese)(林玉娥,顾国昌,刘海波,等.一种核正交鉴别保局投影算法.电子学报,2010,38(4): 979-982)
[16]
Wang Yong,Wu Yi. Complete Neighborhood Preserving Embedding for Face Recognition. Pattern Recognition,2010,43(3): 1008-1015
[17]
Cheng Mianshu,Chen Hexin,Liu Wei. A New Method for Resolving the Uncorrelated Set of Discriminant Vectors. Chinese Journal of Computers,2004,27(7): 913-917 (in Chinese)(陈绵书,陈贺新,刘 伟.一种新的求解无相关鉴别矢量集方法.计算机学报,2004,27(7): 913-917)
[18]
Yang Jian,Zhang David,Yang Jingyu,et al. Globally Maximizing,Locally Minimizing: Unsupervised Discriminant Projection with Applications to Face and Palm Biometrics.IEEE Trans on Pattern Analysis and Machine Intelligence,2007,29(4): 650-664
[19]
Kim K I,Jung K,Kim H J. Face Recognition Using Kernel Principal Component Analysis. IEEE Signal Processing Letters,2002,9(2): 40-42
