Low-Rank Matrix Recovery with Scaled Subgradient Methods: Fast and Robust Convergence Without the Condition Number

26 October 2020

Papers citing "Low-Rank Matrix Recovery with Scaled Subgradient Methods: Fast and Robust Convergence Without the Condition Number"

26 / 26 papers shown

Title
Preconditioned Gradient Descent for Over-Parameterized Nonconvex Matrix Factorization G. Zhang S. Fattahi Richard Y. Zhang 42 34 0 13 Apr 2025
A Stronger Mixture of Low-Rank Experts for Fine-Tuning Foundation Models Mengyang Sun Yihao Wang Tao Feng Dan Zhang Yifan Zhu J. Tang MoE 43 0 0 20 Feb 2025
Guarantees of a Preconditioned Subgradient Algorithm for Overparameterized Asymmetric Low-rank Matrix Recovery Paris Giampouras HanQin Cai René Vidal 35 3 0 22 Oct 2024
Robust Low-rank Tensor Train Recovery Zhen Qin Zhihui Zhu 46 1 0 19 Oct 2024
Provable Acceleration of Nesterov's Accelerated Gradient for Rectangular Matrix Factorization and Linear Neural Networks Zhenghao Xu Yuqing Wang T. Zhao Rachel Ward Molei Tao 29 0 0 12 Oct 2024
Computational and Statistical Guarantees for Tensor-on-Tensor Regression with Tensor Train Decomposition Zhen Qin Zhihui Zhu 74 4 0 10 Jun 2024
Riemannian Preconditioned LoRA for Fine-Tuning Foundation Models Fangzhao Zhang Mert Pilanci AI4CE 59 14 0 04 Feb 2024
Computationally Efficient and Statistically Optimal Robust High-Dimensional Linear Regression Yinan Shen Jingyang Li Jian-Feng Cai Dong Xia 32 1 0 10 May 2023
The Power of Preconditioning in Overparameterized Low-Rank Matrix Sensing Xingyu Xu Yandi Shen Yuejie Chi Cong Ma 40 36 0 02 Feb 2023
Deep Unfolded Tensor Robust PCA with Self-supervised Learning Harry Dong Megna Shah S. Donegan Yuejie Chi SSL 28 6 0 21 Dec 2022
Unrolling SVT to obtain computationally efficient SVT for n-qubit quantum state tomography S. Shanmugam Sheetal Kalyani 11 7 0 17 Dec 2022
Accelerating SGD for Highly Ill-Conditioned Huge-Scale Online Matrix Completion G. Zhang Hong-Ming Chiu Richard Y. Zhang 18 10 0 24 Aug 2022
Fast and Provable Tensor Robust Principal Component Analysis via Scaled Gradient Descent Harry Dong Tian Tong Cong Ma Yuejie Chi 40 12 0 18 Jun 2022
Robust Matrix Completion with Heavy-tailed Noise Bingyan Wang Jianqing Fan 21 4 0 09 Jun 2022
Uncertainty Quantification For Low-Rank Matrix Completion With Heterogeneous and Sub-Exponential Noise Matej Zevcević Andrew A. Li Kristian Kersting 11 6 0 22 Oct 2021
Rank Overspecified Robust Matrix Recovery: Subgradient Method and Exact Recovery Lijun Ding Liwei Jiang Yudong Chen Qing Qu Zhihui Zhu 25 29 0 23 Sep 2021
Nonconvex Factorization and Manifold Formulations are Almost Equivalent in Low-rank Matrix Optimization Yuetian Luo Xudong Li Anru R. Zhang 25 9 0 03 Aug 2021
GNMR: A provable one-line algorithm for low rank matrix recovery Pini Zilber B. Nadler 48 13 0 24 Jun 2021
Scaling and Scalability: Provable Nonconvex Low-Rank Tensor Estimation from Incomplete Measurements Tian Tong Cong Ma Ashley Prater-Bennette Erin E. Tripp Yuejie Chi 23 32 0 29 Apr 2021
Sign-RIP: A Robust Restricted Isometry Property for Low-rank Matrix Recovery Jianhao Ma S. Fattahi 13 12 0 05 Feb 2021
Beyond Procrustes: Balancing-Free Gradient Descent for Asymmetric Low-Rank Matrix Sensing Cong Ma Yuanxin Li Yuejie Chi 16 3 0 13 Jan 2021
Spectral Methods for Data Science: A Statistical Perspective Yuxin Chen Yuejie Chi Jianqing Fan Cong Ma 40 165 0 15 Dec 2020
Recursive Importance Sketching for Rank Constrained Least Squares: Algorithms and High-order Convergence Yuetian Luo Wen Huang Xudong Li Anru R. Zhang 23 15 0 17 Nov 2020
Learning Mixtures of Low-Rank Models Yanxi Chen Cong Ma H. Vincent Poor Yuxin Chen 20 13 0 23 Sep 2020
Accelerating Ill-Conditioned Low-Rank Matrix Estimation via Scaled Gradient Descent Tian Tong Cong Ma Yuejie Chi 21 113 0 18 May 2020
Nonconvex Matrix Factorization from Rank-One Measurements Yuanxin Li Cong Ma Yuxin Chen Yuejie Chi 25 51 0 17 Feb 2018