A Convergent Gradient Descent Algorithm for Rank Minimization and Semidefinite Programming from Random Linear Measurements

19 June 2015

Papers citing "A Convergent Gradient Descent Algorithm for Rank Minimization and Semidefinite Programming from Random Linear Measurements"

34 / 34 papers shown

Title
Preconditioned Gradient Descent for Over-Parameterized Nonconvex Matrix Factorization G. Zhang S. Fattahi Richard Y. Zhang 47 36 0 13 Apr 2025
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
How Over-Parameterization Slows Down Gradient Descent in Matrix Sensing: The Curses of Symmetry and Initialization Nuoya Xiong Lijun Ding Simon S. Du 48 11 0 03 Oct 2023
Unrolling SVT to obtain computationally efficient SVT for n-qubit quantum state tomography S. Shanmugam Sheetal Kalyani 13 7 0 17 Dec 2022
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
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
Tensor-on-Tensor Regression: Riemannian Optimization, Over-parameterization, Statistical-computational Gap, and Their Interplay Yuetian Luo Anru R. Zhang 29 19 0 17 Jun 2022
Supervised Dictionary Learning with Auxiliary Covariates Joo-Hyun Lee Hanbaek Lyu W. Yao 30 1 0 14 Jun 2022
Preconditioned Gradient Descent for Overparameterized Nonconvex Burer--Monteiro Factorization with Global Optimality Certification G. Zhang S. Fattahi Richard Y. Zhang 62 23 0 07 Jun 2022
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
GNMR: A provable one-line algorithm for low rank matrix recovery Pini Zilber B. Nadler 48 14 0 24 Jun 2021
Sharp Global Guarantees for Nonconvex Low-rank Recovery in the Noisy Overparameterized Regime Richard Y. Zhang 47 25 0 21 Apr 2021
Rank-One Measurements of Low-Rank PSD Matrices Have Small Feasible Sets T. Roddenberry Santiago Segarra Anastasios Kyrillidis 21 0 0 17 Dec 2020
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
Quickly Finding a Benign Region via Heavy Ball Momentum in Non-Convex Optimization Jun-Kun Wang Jacob D. Abernethy 11 7 0 04 Oct 2020
Positive Semidefinite Matrix Factorization: A Connection with Phase Retrieval and Affine Rank Minimization D. Lahat Yanbin Lang Vincent Y. F. Tan Cédric Févotte 29 3 0 24 Jul 2020
Accelerating Ill-Conditioned Low-Rank Matrix Estimation via Scaled Gradient Descent Tian Tong Cong Ma Yuejie Chi 27 115 0 18 May 2020
Sharp Restricted Isometry Bounds for the Inexistence of Spurious Local Minima in Nonconvex Matrix Recovery Richard Y. Zhang Somayeh Sojoudi Javad Lavaei 11 51 0 07 Jan 2019
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
Fast and Sample Efficient Inductive Matrix Completion via Multi-Phase Procrustes Flow Xiao Zhang S. Du Quanquan Gu 26 24 0 03 Mar 2018
Nonconvex Low-Rank Matrix Recovery with Arbitrary Outliers via Median-Truncated Gradient Descent Yuanxin Li Yuejie Chi Huishuai Zhang Yingbin Liang 24 29 0 23 Sep 2017
On the Gap Between Strict-Saddles and True Convexity: An Omega(log d) Lower Bound for Eigenvector Approximation Max Simchowitz A. Alaoui Benjamin Recht 18 13 0 14 Apr 2017
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
Biconvex Relaxation for Semidefinite Programming in Computer Vision Sohil Shah A. Yadav Carlos D. Castillo David Jacobs Christoph Studer Tom Goldstein 16 24 0 31 May 2016
Fast Algorithms for Robust PCA via Gradient Descent Xinyang Yi Dohyung Park Yudong Chen C. Caramanis 24 265 0 25 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
Median-Truncated Nonconvex Approach for Phase Retrieval with Outliers Huishuai Zhang Yuejie Chi Yingbin Liang 22 55 0 11 Mar 2016
When Are Nonconvex Problems Not Scary? Ju Sun Qing Qu John N. Wright 24 166 0 21 Oct 2015
Dropping Convexity for Faster Semi-definite Optimization Srinadh Bhojanapalli Anastasios Kyrillidis Sujay Sanghavi 27 172 0 14 Sep 2015
Complete Dictionary Recovery over the Sphere Ju Sun Qing Qu John N. Wright 33 202 0 26 Apr 2015
Finding a sparse vector in a subspace: Linear sparsity using alternating directions Qing Qu Ju Sun John N. Wright 16 111 0 15 Dec 2014