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A block coordinate descent method for regularized multiconvex optimization with applications to nonnegative tensor factorization and completion
Yangyang Xu, Wotao Yin
Research output
:
Contribution to journal
›
Review article
›
peer-review
790
Scopus citations
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Dive into the research topics of 'A block coordinate descent method for regularized multiconvex optimization with applications to nonnegative tensor factorization and completion'. Together they form a unique fingerprint.
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Mathematics
Coordinate Descent
100%
Completion
66%
Factorization
60%
Tensor
59%
Optimization
55%
Non-negative
50%
Hyperspectral Data
44%
Hyperspectral Image
40%
Non-negative Matrix Factorization
36%
Tensor Decomposition
35%
Matrix Decomposition
31%
Synthetic Data
29%
Asymptotic Convergence
28%
Nonnegative Matrices
26%
Nash Equilibrium
26%
Limit Point
26%
MATLAB
25%
Recovery
23%
Global Convergence
23%
Convergence Rate
20%
Objective function
20%
Review
17%
Observation
15%
Demonstrate
14%
Performance
14%
Estimate
11%
Engineering & Materials Science
Factorization
73%
Tensors
72%
MATLAB
19%
Decomposition
17%
Recovery
16%
Set theory
15%