Alternating Least-Squares for Low-Rank Matrix Reconstruction
نویسندگان
چکیده
منابع مشابه
Matrix completion and low-rank SVD via fast alternating least squares
The matrix-completion problem has attracted a lot of attention, largely as a result of the celebrated Netflix competition. Two popular approaches for solving the problem are nuclear-norm-regularized matrix approximation (Candès and Tao, 2009; Mazumder et al., 2010), and maximum-margin matrix factorization (Srebro et al., 2005). These two procedures are in some cases solving equivalent problems,...
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ژورنال
عنوان ژورنال: IEEE Signal Processing Letters
سال: 2012
ISSN: 1070-9908,1558-2361
DOI: 10.1109/lsp.2012.2188026