Matrix Completion via Generalized Low Rank Approximations of Matrices
- Release time:2024-08-09
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Affiliation of Author(s):
理学院
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Journal:
ICIC Express Letters, Part B: Applications
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Key Words:
中文关键字：矩阵补全；广义低秩矩阵逼近；交替方向法；三分解；压缩率，英文关键字：Matrix completion; generalized low rank approximat
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Abstract:
Matrix completion tasks are usually achieved by the aid of low rank structure of the underlying data. For the data collection of many incomplete matrices, this paper proposes a matrix completion technique through generalized low rank approximations of matrices (GLRAM). Firstly, the matrix completion problem is formulated as a non-convex minimization model on the basis of each datum’s tri-factorization. Then, an alternating direction method (ADM) is employed to solving the proposed optimization problem. Finally, numerical results demonstrate that the proposed method has the attractive efficiency for recovering missing entries and improving compression ratio.
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Note:
EI期刊检索
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Co-author:
雍龙泉
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First Author:
shijiarong
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Indexed by:
Journal paper
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Volume:
卷：5
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Issue:
期：6
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Page Number:
页：1619-1625
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Translation or Not:
no
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Date of Publication:
2014-12-01
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