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Tensor completion method based on nonconvex optimization and mode-k convolution lifting

delete2026-09-25
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PRE
AI
Z
Zihan Zhang
H
Huanmin Ge *
Y
Yue Zhang
X
Xinhua Su
DOI：10.1016/j.apm.2026.117334delete
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Abstract

Abstract

En 中文
• A non-convex tensor completion model for structured missing data. • Mode-k convolution lifting disperses structured missing entries. • MCP regularization provides tighter tubal rank approximation. • An efficient ADMM algorithm with Fourier-domain closed-form updates.
Keywords:
Tensor completion
Minimax concave penalty
Mode-k convolution tensor
Structured missingness

Journal

Applied Mathematical Modelling cover
Applied Mathematical Modelling
IF:
5.1
Papers:
1.3K
Citations:
2.8W

Organization

No organization information available
Cited Papers

Cited Papers

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