Generalized Low-rank plus Sparse Tensor Estimation by Fast Riemannian Optimization

16 March 2021

Papers citing "Generalized Low-rank plus Sparse Tensor Estimation by Fast Riemannian Optimization"

9 / 9 papers shown

Title
Outlier-aware Tensor Robust Principal Component Analysis with Self-guided Data Augmentation Yangyang Xu Kexin Li Li Yang You-wei Wen 17 0 0 25 Apr 2025
Fast and Provable Tensor-Train Format Tensor Completion via Precondtioned Riemannian Gradient Descent Fengmiao Bian Jian-Feng Cai Xiaoqun Zhang Yuanwei Zhang 70 0 0 23 Jan 2025
Low-Tubal-Rank Tensor Recovery via Factorized Gradient Descent Zhiyu Liu Zhi-Long Han Yandong Tang Xi-Le Zhao Yao Wang 27 1 0 22 Jan 2024
Provably Accelerating Ill-Conditioned Low-rank Estimation via Scaled Gradient Descent, Even with Overparameterization Cong Ma Xingyu Xu Tian Tong Yuejie Chi 11 9 0 09 Oct 2023
Robust Tensor CUR Decompositions: Rapid Low-Tucker-Rank Tensor Recovery with Sparse Corruption HanQin Cai Zehan Chao Longxiu Huang Deanna Needell 29 11 0 06 May 2023
Tensor-on-Tensor Regression: Riemannian Optimization, Over-parameterization, Statistical-computational Gap, and Their Interplay Yuetian Luo Anru R. Zhang 10 19 0 17 Jun 2022
Learned Robust PCA: A Scalable Deep Unfolding Approach for High-Dimensional Outlier Detection HanQin Cai Jialin Liu W. Yin 20 39 0 11 Oct 2021
Tensor Robust Principal Component Analysis with A New Tensor Nuclear Norm Canyi Lu Jiashi Feng Yudong Chen W. Liu Zhouchen Lin Shuicheng Yan 49 731 0 10 Apr 2018
A Shrinkage Principle for Heavy-Tailed Data: High-Dimensional Robust Low-Rank Matrix Recovery Jianqing Fan Weichen Wang Ziwei Zhu 42 95 0 28 Mar 2016