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Adaptive multi-dimensional low-rank balance methods for tensor completion problems

发布日期:2022-06-27点击数:

报告人:凌晨(杭州电子科技大学)

时间2022年06月28日16:00-

地址:理科楼LA106


摘要:This paper proposes two tensor product based approaches to tensor completion, which recovers missing entries of data represented by tensors. The proposed approaches are based on the tensor singular-value decomposition and the related tensor tubal rank, which are able to capture hidden information from tensors thanks to the balanced consideration of multi-dimensional low-rank features. Accordingly, new optimization formulations for tensor completion are proposed as well as two new algorithms for their solutions. Some computational results for color images, multi-spectral images, videos, and magnetic resonance imaging data recovery show that our approaches perform better than some existing state-of-the-art tensor-based completion methods.


简介:杭州电子科技大学理学院教授,博士生导师。现任中国运筹学会数学规划分会副理事长、中国经济数学与管理数学研究会副理事长,曾任中国运筹学会理事、中国系统工程学会理事、浙江省数学会常务理事。近十年来,主持国家自科基金和浙江省自科基金各4项、其中省基金重点项目1项。在国内外重要刊物发表论文80余篇,多篇发表在Math. Program.、SIAM J. on Optim.和 SIAM J.on Matrix Anal.and Appl. 、COAP、JOTA、JOGO等。


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重庆大学数学与统计学院的前身是始建于1929年的重庆大学理学院和1937年建立的重庆大学商学院,理学院是重庆大学最早设立的三个学院之一,首任院长为数学家何鲁先生。