Rank-Adaptive Tensor Completion Based on Tucker Decomposition

doi:10.3390/e25020225

	Rank-Adaptive Tensor Completion Based on Tucker Decomposition
	Liu, Siqi; Shi, Xiaoyu; Liao, Qifeng
	2023-02-01
发表期刊	ENTROPY; (IF:2.1[JCR-2023],2.2[5-Year])
ISSN	1099-4300
EISSN	1099-4300
卷号	25 期号:2
发表状态	已发表
DOI	10.3390/e25020225
摘要	Tensor completion is a fundamental tool to estimate unknown information from observed data, which is widely used in many areas, including image and video recovery, traffic data completion and the multi-input multi-output problems in information theory. Based on Tucker decomposition, this paper proposes a new algorithm to complete tensors with missing data. In decomposition-based tensor completion methods, underestimation or overestimation of tensor ranks can lead to inaccurate results. To tackle this problem, we design an alternative iterating method that breaks the original problem into several matrix completion subproblems and adaptively adjusts the multilinear rank of the model during optimization procedures. Through numerical experiments on synthetic data and authentic images, we show that the proposed method can effectively estimate the tensor ranks and predict the missing entries.
关键词	HOOI algorithm rank-adaptive methods SVT algorithm tensor completion Tucker decomposition
学科门类	Information Systems ; Mathematical Physics ; Physics and Astronomy (miscellaneous) ; Electrical and Electronic Engineering
URL	查看原文
收录类别	SCOPUS ; SCI
语种	英语
资助项目	National Natural Science Foundation of China[12071291] ; Science and Technology Commission of Shanghai Municipality[20JC1414300] ; Natural Science Foundation of Shanghai[20ZR1436200]
WOS研究方向	Physics
WOS类目	Physics, Multidisciplinary
WOS记录号	WOS:000944975200001
出版者	MDPI
原始文献类型	Article
Scopus 记录号	2-s2.0-85148957207
来源库	SCOPUS
引用统计	正在获取...
文献类型	期刊论文
条目标识符	https://kms.shanghaitech.edu.cn/handle/2MSLDSTB/286486
专题	信息科学与技术学院信息科学与技术学院_PI研究组_廖奇峰组信息科学与技术学院_硕士生
通讯作者	Liao, Qifeng
作者单位	ShanghaiTech Univ, Sch Informat Sci & Technol, Shanghai 201210, Peoples R China
第一作者单位	信息科学与技术学院
通讯作者单位	信息科学与技术学院
第一作者的第一单位	信息科学与技术学院
推荐引用方式 GB/T 7714	Liu, Siqi,Shi, Xiaoyu,Liao, Qifeng. Rank-Adaptive Tensor Completion Based on Tucker Decomposition[J]. ENTROPY;,2023,25(2).
APA	Liu, Siqi,Shi, Xiaoyu,&Liao, Qifeng.(2023).Rank-Adaptive Tensor Completion Based on Tucker Decomposition.ENTROPY;,25(2).
MLA	Liu, Siqi,et al."Rank-Adaptive Tensor Completion Based on Tucker Decomposition".ENTROPY; 25.2(2023).