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Low-Rank Matrix Factorization Under General Mixture Noise Distributions
Xiangyong Cao
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Oznake: computer science;computer vision
Many computer vision problems can be posed as learning a low-dimensional subspace from high dimensional data. The low rank matrix factorization (LRMF) represents a commonly utilized subspace learning strategy. Most of the current LRMF techniques are constructed on the optimization problem using L1 n ...
Leto: 2015 Vir: videolectures.net
Št. zadetkov: 1
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