Work

A Riemannian conjugate gradient method for solving the tensor fixed-rank least-squares problem

Year: 2025

Type: article

Abstract: In this paper, we consider the tensor fixed-rank least-squares problem arising in image restoration. The Riemannian conjugate gradient method with an exact line search technique is designed to solve this problem. A convergence analysis of this method is given. Numerical experiments with synthetic data and real images demonstrate the feasibility and effectiveness of the new method.

Source: ETNA - Electronic Transactions on Numerical Analysis

DOI: 10.1553/etna_vol63s231

Authors: Chun-Mei Li, Yu-Ying Gu, Xue-Feng Duan, Hui-Yan Peng

Institution: Guilin University of Electronic Technology

Language: English

Topic: Tensor decomposition and applications

Subfield: Computational Mathematics

Field: Mathematics

Domain: Physical Sciences

Open Access status: bronze

Funders: National Natural Science Foundation of China, Natural Science Foundation of Guangxi Province

Awards: G25043811, G464533592, G4946175697, G82881679