Laplace function based nonconvex surrogate for low-rank tensor completion
作者：
Highlights：
• We suggest a new surrogate of tensor multi rank based on the Laplace function.
• An efficient algorithm is designed to tackle the corresponding tensor completion model.
• Extensive experiments demonstrate the superiority of the proposed method.
摘要
•We suggest a new surrogate of tensor multi rank based on the Laplace function.•An efficient algorithm is designed to tackle the corresponding tensor completion model.•Extensive experiments demonstrate the superiority of the proposed method.
论文关键词：Nonconvex optimization,Tensor completion,Laplace function,Tensor singular value decomposition (t-SVD)
论文评审过程：Received 10 February 2018, Revised 23 November 2018, Accepted 26 November 2018, Available online 1 December 2018, Version of Record 12 March 2019.
论文官网地址：https://doi.org/10.1016/j.image.2018.11.007
