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Gins G, Smets IY, Van Impe JF (2008) Efficient tracking of the dominant eigenspace of a normalized kernel matrix. Neural Comput 20:523-54 [PubMed]

References and models cited by this paper

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Baglama J (2004) The irbleigs Matlab program for computing a few eigen values and eigenvectors of a large sparse hermitian matrix Available online at http:--www.math.uri.edu-jbaglama-

Blake CL, Merz CJ (1998) UCI Repository of Machine Learning Databases

Golub GH, van_Loan CF (1996) Matrix computations

Hoegaerts L, De Lathauwer L, Goethals I, Suykens JA, Vandewalle J, De Moor B (2007) Efficiently updating and tracking the dominant kernel principal components. Neural Netw 20:220-9 [Journal] [PubMed]

Hoegaerts L, De_Lathauwer L, Suykens JAK, Vandewalle J (2004) Efficiently updating and tracking the dominant kernel eigen space Proc 16th Intl Symposium Math Theory Networks and Systems

Kim K, Franz MO, Scholkopf B (2003) Kernel Hebbian algorithm for iterative kernel principal component analysis Tech Rep 109 Max Planck Institute Biologische Kybernetik

Larsen RM (2004) Propack software for large and sparse SVD calculations Available online at http:--sun.stanford.edu-rmunk-PROPACK-index.html

Ng AY, Jordan MI, Weiss Y (2002) On spectral clustering: Analysis and an algorithm Advances In Neural Information Processing Systems, Becker S:Dietterich TG:Ghahramani Z, ed.

Rosipal R, Girolami M (2001) An expectation-maximization approach to nonlinear component analysis Neural Comput 13:505-510

Scholkopf B, Smola A, Muller KR (1998) Nonlinear component analysis as a kernel eigenvalue problem Neural Comput 10:1299-1319

Scholkopf B, Smola AJ (2001) Learning with kernels: Support vector machines, regularization, optimization, and beyond

Suykens JAK, van_Gestel T, De_Bradanter J, De_Moor B, Vandewalle J (2002) Least squares support vector machines

Weiss Y (1999) Segmentation using eigen vectors: A unifying view Proc IEEE Intl Conf Computer Vision :975-982

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