A low-rank and sparse enhanced Tucker decomposition approach for tensor completion

2023/11/09 by Chenjian Pan, Chen Ling, Hongjin He +2 · 15 citations
Engineering · Mathematics · Medicine · #Advanced Neuroimaging Techniques and Applications #Algorithm #Artificial intelligence #Combinatorics #Computer science #Decomposition #Mathematical optimization #Mathematics #Matrix decomposition #Rank (graph theory) #Regularization (linguistics) #Sparse and Compressive Sensing Techniques #Sparse matrix #Tensor (intrinsic definition) #Tensor decomposition #Tensor decomposition and applications #Theoretical computer science #Tucker decomposition

paper · doi:10.1016/j.amc.2023.128432

published in Applied Mathematics and Computation 465, 128432 (Elsevier BV)

openalex publication_date 2023/11/09 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/25

Citations

• Some Mathematical Notes on Three-Mode Factor Analysis
• Tensor Decompositions and Applications
• Most Tensor Problems Are NP-Hard
• Robust principal component analysis?

Cited by

• LRTuckerRep: Low-rank Tucker Representation Model for Multi-dimensional Data Completion