Fast low-rank estimation by projected gradient descent: General statistical and algorithmic guarantees

10 September 2015

Papers citing "Fast low-rank estimation by projected gradient descent: General statistical and algorithmic guarantees"

50 / 57 papers shown

Title
Euclidean Distance Matrix Completion via Asymmetric Projected Gradient Descent Yicheng Li Xinghua Sun 39 0 0 28 Apr 2025
Preconditioned Gradient Descent for Over-Parameterized Nonconvex Matrix Factorization G. Zhang S. Fattahi Richard Y. Zhang 45 36 0 13 Apr 2025
Riemannian Optimization on Relaxed Indicator Matrix Manifold Jinghui Yuan Fangyuan Xie Feiping Nie Xuelong Li 75 0 0 26 Mar 2025
Matrix Completion with Graph Information: A Provable Nonconvex Optimization Approach Yao Wang Yiyang Yang Kaidong Wang Shanxing Gao Xiuwu Liao 63 0 0 12 Feb 2025
Exploiting Observation Bias to Improve Matrix Completion Yassir Jedra Sean Mann Charlotte Park Devavrat Shah 40 1 0 03 Jan 2025
COAP: Memory-Efficient Training with Correlation-Aware Gradient Projection Jinqi Xiao S. Sang Tiancheng Zhi Jing Liu Qing Yan Linjie Luo Bo Yuan Bo Yuan VLM 103 1 0 26 Nov 2024
VeLoRA: Memory Efficient Training using Rank-1 Sub-Token Projections Roy Miles Pradyumna Reddy Ismail Elezi Jiankang Deng VLM 43 3 0 28 May 2024
GaLore: Memory-Efficient LLM Training by Gradient Low-Rank Projection Jiawei Zhao Zhenyu Zhang Beidi Chen Zhangyang Wang A. Anandkumar Yuandong Tian 43 178 0 06 Mar 2024
Low-Tubal-Rank Tensor Recovery via Factorized Gradient Descent Zhiyu Liu Zhi Han Yandong Tang Xi-Le Zhao Yao Wang 50 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 18 9 0 09 Oct 2023
Semiparametric Modeling and Analysis for Longitudinal Network Data Yinqiu He Jiajin Sun Yuang Tian Z. Ying Yang Feng 39 1 0 23 Aug 2023
Gradient-Based Spectral Embeddings of Random Dot Product Graphs Marcelo Fiori Bernardo Marenco Federico Larroca P. Bermolen Gonzalo Mateos BDL 27 3 0 25 Jul 2023
PDPP: Projected Diffusion for Procedure Planning in Instructional Videos Hanlin Wang Yilu Wu Sheng Guo Limin Wang VGen DiffM 73 30 0 26 Mar 2023
Subspace based Federated Unlearning Guang-Ming Li Li Shen Yan Sun Yuejun Hu Han Hu Dacheng Tao MU FedML 28 20 0 24 Feb 2023
$Approximate message passing from random initialization with applications to $\mathbb{Z}_{2}$ synchronization$ Approximate message passing from random initialization with applications to $\mathbb{Z}_{2}$ synchronization Gen Li Wei Fan Yuting Wei 26 10 0 07 Feb 2023
Matrix Estimation for Individual Fairness Cindy Y. Zhang Sarah H. Cen Devavrat Shah FaML 36 4 0 04 Feb 2023
Nonconvex Matrix Factorization is Geodesically Convex: Global Landscape Analysis for Fixed-rank Matrix Optimization From a Riemannian Perspective Yuetian Luo Nicolas García Trillos 24 6 0 29 Sep 2022
A Validation Approach to Over-parameterized Matrix and Image Recovery Lijun Ding Zhen Qin Liwei Jiang Jinxin Zhou Zhihui Zhu 48 13 0 21 Sep 2022
Accelerating SGD for Highly Ill-Conditioned Huge-Scale Online Matrix Completion G. Zhang Hong-Ming Chiu Richard Y. Zhang 27 10 0 24 Aug 2022
Optimal tuning-free convex relaxation for noisy matrix completion Yuepeng Yang Cong Ma 28 8 0 12 Jul 2022
Robust Matrix Completion with Heavy-tailed Noise Bingyan Wang Jianqing Fan 21 4 0 09 Jun 2022
Convergence of gradient descent for deep neural networks S. Chatterjee ODL 21 20 0 30 Mar 2022
On Asymptotic Linear Convergence of Projected Gradient Descent for Constrained Least Squares Trung Vu Raviv Raich 27 13 0 22 Dec 2021
Large Learning Rate Tames Homogeneity: Convergence and Balancing Effect Yuqing Wang Minshuo Chen T. Zhao Molei Tao AI4CE 57 40 0 07 Oct 2021
Nonconvex Factorization and Manifold Formulations are Almost Equivalent in Low-rank Matrix Optimization Yuetian Luo Xudong Li Anru R. Zhang 33 9 0 03 Aug 2021
Mind Mappings: Enabling Efficient Algorithm-Accelerator Mapping Space Search Kartik Hegde Po-An Tsai Sitao Huang Vikas Chandra A. Parashar Christopher W. Fletcher 26 90 0 02 Mar 2021
Noisy Gradient Descent Converges to Flat Minima for Nonconvex Matrix Factorization Tianyi Liu Yan Li S. Wei Enlu Zhou T. Zhao 21 13 0 24 Feb 2021
Exact Linear Convergence Rate Analysis for Low-Rank Symmetric Matrix Completion via Gradient Descent Trung Vu Raviv Raich 40 10 0 04 Feb 2021
Spectral Methods for Data Science: A Statistical Perspective Yuxin Chen Yuejie Chi Jianqing Fan Cong Ma 44 165 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
Randomized Value Functions via Posterior State-Abstraction Sampling Dilip Arumugam Benjamin Van Roy OffRL 31 7 0 05 Oct 2020
Uncertainty quantification for nonconvex tensor completion: Confidence intervals, heteroscedasticity and optimality Changxiao Cai H. Vincent Poor Yuxin Chen 13 23 0 15 Jun 2020
Accelerating Ill-Conditioned Low-Rank Matrix Estimation via Scaled Gradient Descent Tian Tong Cong Ma Yuejie Chi 27 115 0 18 May 2020
$Policy Optimization for $\mathcal{H}_2$ Linear Control with $\mathcal{H}_\infty$ Robustness Guarantee: Implicit Regularization and Global Convergence$ Policy Optimization for $\mathcal{H}_2$ Linear Control with $\mathcal{H}_\infty$ Robustness Guarantee: Implicit Regularization and Global Convergence Kaipeng Zhang Bin Hu Tamer Basar 24 119 0 21 Oct 2019
Harnessing Structures for Value-Based Planning and Reinforcement Learning Yuzhe Yang Guo Zhang Zhi Xu Dina Katabi OffRL 27 31 0 26 Sep 2019
ME-Net: Towards Effective Adversarial Robustness with Matrix Estimation Yuzhe Yang Guo Zhang Dina Katabi Zhi Xu AAML 10 168 0 28 May 2019
On Robustness of Principal Component Regression Anish Agarwal Devavrat Shah Dennis Shen Dogyoon Song 29 81 0 28 Feb 2019
A Dictionary-Based Generalization of Robust PCA with Applications to Target Localization in Hyperspectral Imaging Sirisha Rambhatla Xingguo Li Jineng Ren Jarvis Haupt 19 2 0 21 Feb 2019
Noisy Matrix Completion: Understanding Statistical Guarantees for Convex Relaxation via Nonconvex Optimization Yuxin Chen Yuejie Chi Jianqing Fan Cong Ma Yuling Yan 20 128 0 20 Feb 2019
Defending Against Saddle Point Attack in Byzantine-Robust Distributed Learning Dong Yin Yudong Chen Kannan Ramchandran Peter L. Bartlett FedML 32 97 0 14 Jun 2018
Provably convergent acceleration in factored gradient descent with applications in matrix sensing Tayo Ajayi David Mildebrath Anastasios Kyrillidis Shashanka Ubaru Georgios Kollias K. Bouchard 18 1 0 01 Jun 2018
No Spurious Local Minima in Nonconvex Low Rank Problems: A Unified Geometric Analysis Rong Ge Chi Jin Yi Zheng 47 433 0 03 Apr 2017
Symmetry, Saddle Points, and Global Optimization Landscape of Nonconvex Matrix Factorization Xingguo Li Junwei Lu R. Arora Jarvis Haupt Han Liu Zhaoran Wang T. Zhao 43 52 0 29 Dec 2016
A Unified Computational and Statistical Framework for Nonconvex Low-Rank Matrix Estimation Lingxiao Wang Xiao Zhang Quanquan Gu 16 80 0 17 Oct 2016
Non-square matrix sensing without spurious local minima via the Burer-Monteiro approach Dohyung Park Anastasios Kyrillidis C. Caramanis Sujay Sanghavi 23 179 0 12 Sep 2016
Solving a Mixture of Many Random Linear Equations by Tensor Decomposition and Alternating Minimization Xinyang Yi C. Caramanis Sujay Sanghavi 27 59 0 19 Aug 2016
Fast Algorithms for Robust PCA via Gradient Descent Xinyang Yi Dohyung Park Yudong Chen C. Caramanis 24 265 0 25 May 2016
Matrix Completion has No Spurious Local Minimum Rong Ge J. Lee Tengyu Ma 25 596 0 24 May 2016
Global Optimality of Local Search for Low Rank Matrix Recovery Srinadh Bhojanapalli Behnam Neyshabur Nathan Srebro ODL 39 386 0 23 May 2016
Convergence Analysis for Rectangular Matrix Completion Using Burer-Monteiro Factorization and Gradient Descent Qinqing Zheng John D. Lafferty 34 160 0 23 May 2016