A generalized power iteration method for solving quadratic problem on the Stiefel manifold

Green, B.: The orthogonal approximation of an oblique simple structure in factor analysis. Psychometrika. 17

1952

Earlier work this paper cites.

Hurley, J., Cattell, R.: The procrustes program: producing direct rotation to test a hypothesized factor structure. Behavioural Science. 6

1962

Earlier work this paper cites.

Green, B., Goers, J.: A problem with congruence. The Annual Meeting of the Psychometric Society. Monterey, California (1979)

1979

Earlier work this paper cites.

Golub, G. H., Van Loan, C. F.: Matrix Computations. The Johns Hopkins University Press (1989)

1989

Earlier work this paper cites.

Park, H.: A parallel algorithm for the unbalanced orthogonal procrustes problem. Parallel Computing. 17

1991

Earlier work this paper cites.

Bojanczyk, A., Lutoborski, A.: The procrustes problem for orthogonal stiefel matrices. SIAM. J. Sci. Comput. 21

1999

Earlier work this paper cites.

Chu, M., Trendafilov, N.: The orthogonally constrained regression revisted. J. Comput. Graph. Stat. 10

2001

Cited alongside, same era.

Zhang, Z., Huang, Y.: A projection method for least square problems with quadratic equality constraint. SIAM. J. Matr. Anal. Appl. 25

2003

Cited alongside, same era.

Fiori, S.: Formulation and integration of learning differential equations on the Stiefel manifold. IEEE Transactions on Neural Networks. 16

2005

Cited alongside, same era.

Thomas, V.: Algorithms for the weighted orthogonal procrustes problem and other least squares problems: [D]. (2006) Umeå University, Sweden

2006

Cited alongside, same era.

Zhang, Z., Du, K.: Successive projection method for solving the unbalanced procrustes problem. Science in China: Series A Mathematics. 49

2006

Cited alongside, same era.

Journée, M., Nesterov, Y., Richtárik, P., Sepulchre, R.: Generalized power method for sparse principal component analysis. Journal of Machine Learning Research. 11

2008

Later among the works it cites.

Souza, P., Leite, C., Borges, H., Fonseca, R.: Online algorithm based on support vectors for orthogonal regression. Pattern Recognition Letters 34

2013

Later among the works it cites.

Kaneko, T., Fiori, S., Tanaka, T.: Empirical arithmetic averaging over the compact stiefel manifold. IEEE Transactions on Signal Processing. 61

2013

Later among the works it cites.

Xia, Y., Han, Y.: Partial lagrangian relaxation for the unbalanced orthogonal procrustes problem. Math. Meth. Oper. Res. 79

2014

Later among the works it cites.

Nie, F., Yuan, J., Huang, H.: Optimal mean robust principal component analysis. in Proc. ICML. (2014) 2755-2763

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