Fixed-rank matrix factorizations and Riemannian low-rank optimization
نویسندگان
چکیده
منابع مشابه
Fixed-rank matrix factorizations and Riemannian low-rank optimization
Motivated by the problem of learning a linear regression model whose parameter is a large fixed-rank non-symmetric matrix, we consider the optimization of a smooth cost function defined on the set of fixed-rank matrices. We adopt the geometric framework of optimization on Riemannian quotient manifolds. We study the underlying geometries of several well-known fixed-rank matrix factorizations and...
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ژورنال
عنوان ژورنال: Computational Statistics
سال: 2013
ISSN: 0943-4062,1613-9658
DOI: 10.1007/s00180-013-0464-z