Solving Random Quadratic Systems of Equations Is Nearly as Easy as Solving Linear Systems

19 May 2015

Emmanuel J. Candes

Papers citing "Solving Random Quadratic Systems of Equations Is Nearly as Easy as Solving Linear Systems"

50 / 57 papers shown

Title
AltGDmin: Alternating GD and Minimization for Partly-Decoupled (Federated) Optimization Namrata Vaswani 41 0 0 20 Apr 2025
Adversarial Phase Retrieval via Nonlinear Least Absolute Deviation Gao Huang Song Li Hang Xu 30 0 0 11 Dec 2023
Poisson-Gaussian Holographic Phase Retrieval with Score-based Image Prior Zongyu Li Jason Hu Xiaojian Xu Liyue Shen Jeffrey A. Fessler DiffM 24 3 0 12 May 2023
Synthetic Principal Component Design: Fast Covariate Balancing with Synthetic Controls Yiping Lu Jiajin Li Lexing Ying Jose H. Blanchet 19 2 0 28 Nov 2022
Provable Phase Retrieval with Mirror Descent Jean-Jacques-Narcisse Godeme M. Fadili Xavier Buet M. Zerrad M. Lequime C. Amra 23 4 0 17 Oct 2022
Misspecified Phase Retrieval with Generative Priors Zhaoqiang Liu Xinshao Wang Jiulong Liu 46 4 0 11 Oct 2022
Sudakov-Fernique post-AMP, and a new proof of the local convexity of the TAP free energy Michael Celentano 40 20 0 19 Aug 2022
Preconditioned Gradient Descent for Overparameterized Nonconvex Burer--Monteiro Factorization with Global Optimality Certification G. Zhang S. Fattahi Richard Y. Zhang 59 23 0 07 Jun 2022
Subspace Phase Retrieval Meng Xu Dekuan Dong J. Wang 19 2 0 06 Jun 2022
Group-invariant max filtering Jameson Cahill Joseph W. Iverson D. Mixon Dan Packer 30 21 0 27 May 2022
Randomly Initialized Alternating Least Squares: Fast Convergence for Matrix Sensing Kiryung Lee Dominik Stöger 31 11 0 25 Apr 2022
Convex Augmentation for Total Variation Based Phase Retrieval Jian-qiang Niu Hok Shing Wong T. Zeng 18 0 0 21 Apr 2022
Convergence of gradient descent for deep neural networks S. Chatterjee ODL 21 20 0 30 Mar 2022
Unfolding-Aided Bootstrapped Phase Retrieval in Optical Imaging Samuel Pinilla Kumar Vijay Mishra I. Shevkunov M. Soltanalian V. Katkovnik K. Egiazarian 13 13 0 03 Mar 2022
Optimal convex lifted sparse phase retrieval and PCA with an atomic matrix norm regularizer Andrew D. McRae Justin Romberg Mark A. Davenport 35 8 0 08 Nov 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
Small random initialization is akin to spectral learning: Optimization and generalization guarantees for overparameterized low-rank matrix reconstruction Dominik Stöger Mahdi Soltanolkotabi ODL 42 75 0 28 Jun 2021
Sharp Global Guarantees for Nonconvex Low-rank Recovery in the Noisy Overparameterized Regime Richard Y. Zhang 47 25 0 21 Apr 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
Solving Phase Retrieval with a Learned Reference Rakib Hyder Zikui Cai M. Salman Asif 13 24 0 29 Jul 2020
Positive Semidefinite Matrix Factorization: A Connection with Phase Retrieval and Affine Rank Minimization D. Lahat Yanbin Lang Vincent Y. F. Tan Cédric Févotte 15 3 0 24 Jul 2020
DeepInit Phase Retrieval M. Reiche P. Jung 27 3 0 16 Jul 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
When deep denoising meets iterative phase retrieval Yaotian Wang Xiaohang Sun Jason W. Fleischer 12 18 0 03 Mar 2020
The estimation error of general first order methods Michael Celentano Andrea Montanari Yuchen Wu 14 44 0 28 Feb 2020
An Optimal Statistical and Computational Framework for Generalized Tensor Estimation Rungang Han Rebecca Willett Anru R. Zhang 27 65 0 26 Feb 2020
A frequency-domain analysis of inexact gradient methods Oran Gannot 24 25 0 31 Dec 2019
Manifold Gradient Descent Solves Multi-Channel Sparse Blind Deconvolution Provably and Efficiently Laixi Shi Yuejie Chi 30 26 0 25 Nov 2019
$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
Max-Affine Regression: Provable, Tractable, and Near-Optimal Statistical Estimation Avishek Ghosh A. Pananjady Adityanand Guntuboyina Kannan Ramchandran 14 25 0 21 Jun 2019
Algorithmic Guarantees for Inverse Imaging with Untrained Network Priors Gauri Jagatap C. Hegde 26 70 0 20 Jun 2019
Alternating Phase Projected Gradient Descent with Generative Priors for Solving Compressive Phase Retrieval Rakib Hyder Viraj Shah C. Hegde M. Salman Asif 21 45 0 07 Mar 2019
Analysis of Spectral Methods for Phase Retrieval with Random Orthogonal Matrices Rishabh Dudeja Milad Bakhshizadeh Junjie Ma A. Maleki 21 20 0 07 Mar 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
Fast and Faster Convergence of SGD for Over-Parameterized Models and an Accelerated Perceptron Sharan Vaswani Francis R. Bach Mark W. Schmidt 30 296 0 16 Oct 2018
Continuous-time Models for Stochastic Optimization Algorithms Antonio Orvieto Aurelien Lucchi 19 31 0 05 Oct 2018
Quantization-Aware Phase Retrieval Subhadip Mukherjee C. Seelamantula MQ 11 2 0 02 Oct 2018
Stochastic model-based minimization of weakly convex functions Damek Davis Dmitriy Drusvyatskiy 33 370 0 17 Mar 2018
prDeep: Robust Phase Retrieval with a Flexible Deep Network Christopher A. Metzler Philip Schniter Ashok Veeraraghavan Richard G. Baraniuk OOD 36 168 0 01 Mar 2018
Misspecified Nonconvex Statistical Optimization for Phase Retrieval Zhuoran Yang Lin F. Yang Ethan X. Fang T. Zhao Zhaoran Wang Matey Neykov 16 15 0 18 Dec 2017
Using Black-box Compression Algorithms for Phase Retrieval Milad Bakhshizadeh A. Maleki S. Jalali 13 8 0 08 Dec 2017
Analysis of Biased Stochastic Gradient Descent Using Sequential Semidefinite Programs Bin Hu Peter M. Seiler Laurent Lessard 18 39 0 03 Nov 2017
Natasha 2: Faster Non-Convex Optimization Than SGD Zeyuan Allen-Zhu ODL 28 245 0 29 Aug 2017
Phase Retrieval via Randomized Kaczmarz: Theoretical Guarantees Yan Shuo Tan Roman Vershynin 14 99 0 30 Jun 2017
Solving Almost all Systems of Random Quadratic Equations G. Wang G. Giannakis Y. Saad Jie Chen 34 25 0 29 May 2017
Stochastic Methods for Composite and Weakly Convex Optimization Problems John C. Duchi Feng Ruan 15 126 0 24 Mar 2017
Phase Transitions of Spectral Initialization for High-Dimensional Nonconvex Estimation Yue M. Lu Gen Li 23 89 0 21 Feb 2017
Phase Retrieval Meets Statistical Learning Theory: A Flexible Convex Relaxation S. Bahmani Justin Romberg 21 120 0 13 Oct 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