Linearized augmented Lagrangian and alternating direction methods for nuclear norm minimization
نویسندگان
چکیده
منابع مشابه
Linearized augmented Lagrangian and alternating direction methods for nuclear norm minimization
The nuclear norm is widely used to induce low-rank solutions for many optimization problems with matrix variables. Recently, it has been shown that the augmented Lagrangian method (ALM) and the alternating direction method (ADM) are very efficient for many convex programming problems arising from various applications, provided that the resulting subproblems are sufficiently simple to have close...
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ژورنال
عنوان ژورنال: Mathematics of Computation
سال: 2012
ISSN: 0025-5718,1088-6842
DOI: 10.1090/s0025-5718-2012-02598-1