Non-square matrix sensing without spurious local minima via the Burer-Monteiro approach

12 September 2016

Dohyung Park

Anastasios Kyrillidis

C. Caramanis

Sujay Sanghavi

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Papers citing "Non-square matrix sensing without spurious local minima via the Burer-Monteiro approach"

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Title
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Escaping From Saddle Points Using Asynchronous Coordinate Gradient Descent Marco Bornstein Jin-Peng Liu Jingling Li Furong Huang 21 0 0 17 Nov 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
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 53 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 30 9 0 03 Aug 2021
Global Convergence of Gradient Descent for Asymmetric Low-Rank Matrix Factorization Tian-Chun Ye S. Du 21 46 0 27 Jun 2021
Sharp Restricted Isometry Property Bounds for Low-rank Matrix Recovery Problems with Corrupted Measurements Ziye Ma Yingjie Bi Javad Lavaei Somayeh Sojoudi 29 14 0 18 May 2021
Sharp Global Guarantees for Nonconvex Low-rank Recovery in the Noisy Overparameterized Regime Richard Y. Zhang 44 1 0 21 Apr 2021
HePPCAT: Probabilistic PCA for Data with Heteroscedastic Noise David Hong Kyle Gilman Laura Balzano Jeffrey A. Fessler 40 19 0 10 Jan 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
Accelerating Ill-Conditioned Low-Rank Matrix Estimation via Scaled Gradient Descent Tian Tong Cong Ma Yuejie Chi 27 115 0 18 May 2020
Replica Exchange for Non-Convex Optimization Jing-rong Dong Xin T. Tong 27 21 0 23 Jan 2020
Manifold Gradient Descent Solves Multi-Channel Sparse Blind Deconvolution Provably and Efficiently Laixi Shi Yuejie Chi 30 26 0 25 Nov 2019
Implicit Regularization in Deep Matrix Factorization Sanjeev Arora Nadav Cohen Wei Hu Yuping Luo AI4CE 38 491 0 31 May 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
A Deterministic Gradient-Based Approach to Avoid Saddle Points L. Kreusser Stanley J. Osher Bao Wang ODL 32 3 0 21 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 15 1 0 01 Jun 2018
Improved Learning of One-hidden-layer Convolutional Neural Networks with Overlaps S. Du Surbhi Goel MLT 30 17 0 20 May 2018
The Global Optimization Geometry of Shallow Linear Neural Networks Zhihui Zhu Daniel Soudry Yonina C. Eldar M. Wakin ODL 18 36 0 13 May 2018
Smoothed analysis for low-rank solutions to semidefinite programs in quadratic penalty form Srinadh Bhojanapalli Nicolas Boumal Prateek Jain Praneeth Netrapalli 23 42 0 01 Mar 2018
No Spurious Local Minima in Nonconvex Low Rank Problems: A Unified Geometric Analysis Rong Ge Chi Jin Yi Zheng 36 433 0 03 Apr 2017
How to Escape Saddle Points Efficiently Chi Jin Rong Ge Praneeth Netrapalli Sham Kakade Michael I. Jordan ODL 37 831 0 02 Mar 2017
Convergence Results for Neural Networks via Electrodynamics Rina Panigrahy Sushant Sachdeva Qiuyi Zhang MLT MDE 29 22 0 01 Feb 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