Jolliffe I T. Principal Component Analysis[M]. Wiley Online Library:Springer, 2002.[DOI:10.1002/9781118445112. stat06472]
[2]
Wold S, Esbensen K, Geladi P. Principal component analysis[J]. Chemometrics and Intelligent Laboratory Systems, 1987, 2(1):37-52.[DOI:10.1016/0169-7439(87)80084-9]
[3]
Ding C H Q, Zhou D, He X F, et al. R 1-PCA:rotational invariant L1-norm principal component analysis for robust subspace factorization[C]//Proceedings of the 23rd International Conference on Machine Learning. Carnegie Mellon University, Pittsburgh, USA:ACM, 2006:281-288.[DOI:10.1145/1143844.1143880]
[4]
Baccini A, Besse P, De Falguerolles A D. A L1-norm PCA and a heuristic approach[J]. Ordinal and Symbolic Data Analysis, Springer, 1996:359-368.
[5]
Kwak N. Principal component analysis based on L1-norm maximization[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2008, 30(9):1672-1680.[DOI:10.1109/TPAMI.2008.114]
[6]
Yang J, Zhang D, Frangi A F, et al. Two-dimensional PCA:a new approach to appearance-based face representation and recognition[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2004, 26(1):131-137.[DOI:10.1109/TPAMI.2004.1261097]
[7]
Li X L, Pang Y W, Yuan Y. L1-norm-based 2DPCA[J]. IEEE Transactions on Systems, Man, and Cybernetics. Part B, Cybernetics, 2010, 40(4):1170-1175.[DOI:10.1109/TSMCB. 2009. 2035629]
[8]
Wang H X. Block principal component analysis with L1-norm for image analysis[J]. Pattern Recognition Letters, 2012, 33(5):537-542.[DOI:10.1016/j.patrec.2011.11.029]
[9]
Pang Y W, Li X L, Yuan Y. Robust tensor analysis with L1-Norm[J]. IEEE Transactions on Circuits and Systems for Video Technology, 2010, 20(2):172-178.[DOI:10.1109/TCSVT.2009.2020337]
[10]
Principe J C, Xu D, Fisher J. Information theoretic learning[C]//Proceedings of Unsupervised Adaptive Filtering, Haykin S, ed. New York:Wiley, 2000, 1:265-319.
[11]
Xu D. Energy, entropy and information potential for neural computation[D]. Gainesville, USA:University of Florida, 1999.
[12]
Viola P, Schraudolph N, Sejnowski T J. Empirical entropy manipulation for real-world problems[J]. Advances in Neural Information Processing Systems, 1996:851-857.
[13]
Liu W F, Pokharel P P, Principe J C. Correntropy:properties and applications in non-Gaussian signal processing[J]. IEEE Transactions on Signal Processing, 2007, 55(11):5286-5298.[DOI:10.1109/TSP.2007.896065]
[14]
Yuan X T and Hu B G. Robust feature extraction via information theoretic learning[C]//Proceedings of the 26th Annual International Conference on Machine Learning. Montreal, Canada:ACM, 2009:1193-1200.
[15]
Rockafellar R T. Convex Analysis[M]. Princeton Mathematical Series:Princeton University Press, 1970:46-49.
[16]
He R, Hu B G., Zheng W S, et al. Two-stage sparse representation for robust recognition on large-scale database[C]//Proceedings of the Twenty-Fourth AAAI Conference on Artificial Intelligence. Westin Peachtree Plaza, Atlanta, Georgia, USA:AAAI Press, 2010.
[17]
He R, Zheng W S, Hu B G.. Maximum correntropy criterion for robust face recognition[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2010, 33(8):1561-1576.[DOI:10.1109/TPAMI.2010.220]
