Iterative Methods for Matrix Factorization with Missing Data
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[1] Anders P. Eriksson,et al. Efficient computation of robust low-rank matrix approximations in the presence of missing data using the L1 norm , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.
[2] Takayuki Okatani,et al. On the Wiberg Algorithm for Matrix Factorization in the Presence of Missing Components , 2007, International Journal of Computer Vision.
[3] Andrew W. Fitzgibbon,et al. Damped Newton algorithms for matrix factorization with missing data , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).
[4] G. Golub,et al. Separable nonlinear least squares: the variable projection method and its applications , 2003 .
[5] Martin Hanke,et al. On Lanczos Based Methods for the Regularization of Discrete Ill-Posed Problems , 2001 .
[6] Peter F. Sturm,et al. A Factorization Based Algorithm for Multi-Image Projective Structure and Motion , 1996, ECCV.
[7] Takeo Kanade,et al. A Paraperspective Factorization Method for Shape and Motion Recovery , 1994, IEEE Trans. Pattern Anal. Mach. Intell..
[8] Takeo Kanade,et al. Shape and motion from image streams under orthography: a factorization method , 1992, International Journal of Computer Vision.
[9] R. Hartley,et al. PowerFactorization : 3D reconstruction with missing or uncertain data , 2003 .
[10] Kaj Madsen,et al. Methods for Non-Linear Least Squares Problems , 1999 .