Phase Retrieval via Wirtinger Flow: Theory and Algorithms

3 July 2014

Emmanuel Candes

Papers citing "Phase Retrieval via Wirtinger Flow: Theory and Algorithms"

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Title
Phase retrieval in high dimensions: Statistical and computational phase transitions Antoine Maillard Bruno Loureiro Florent Krzakala Lenka Zdeborová 26 57 0 09 Jun 2020
Approximation Schemes for ReLU Regression Ilias Diakonikolas Surbhi Goel Sushrut Karmalkar Adam R. Klivans Mahdi Soltanolkotabi 18 51 0 26 May 2020
Accelerating Ill-Conditioned Low-Rank Matrix Estimation via Scaled Gradient Descent Tian Tong Cong Ma Yuejie Chi 27 115 0 18 May 2020
Reducibility and Statistical-Computational Gaps from Secret Leakage Matthew Brennan Guy Bresler 29 86 0 16 May 2020
High-Dimensional Robust Mean Estimation via Gradient Descent Yu Cheng Ilias Diakonikolas Rong Ge Mahdi Soltanolkotabi 17 31 0 04 May 2020
Inverse Problems, Deep Learning, and Symmetry Breaking Kshitij Tayal Chieh-Hsin Lai Vipin Kumar Ju Sun AI4CE 72 15 0 20 Mar 2020
Solving Inverse Problems with a Flow-based Noise Model Jay Whang Qi Lei A. Dimakis 64 36 0 18 Mar 2020
When deep denoising meets iterative phase retrieval Yaotian Wang Xiaohang Sun Jason W. Fleischer 14 18 0 03 Mar 2020
The estimation error of general first order methods Michael Celentano Andrea Montanari Yuchen Wu 16 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
Tuning-free Plug-and-Play Proximal Algorithm for Inverse Imaging Problems Kaixuan Wei Angelica Aviles-Rivero Jingwei Liang Ying Fu Carola-Bibiane Schönlieb Hua Huang 21 103 0 22 Feb 2020
Deep S $^3$ PR: Simultaneous Source Separation and Phase Retrieval Using Deep Generative Models Christopher A. Metzler Gordon Wetzstein 20 11 0 14 Feb 2020
On the Sample Complexity and Optimization Landscape for Quadratic Feasibility Problems Parth Thaker Gautam Dasarathy Angelia Nedić 24 5 0 04 Feb 2020
A frequency-domain analysis of inexact gradient methods Oran Gannot 24 25 0 31 Dec 2019
Revisiting Landscape Analysis in Deep Neural Networks: Eliminating Decreasing Paths to Infinity Shiyu Liang Ruoyu Sun R. Srikant 35 19 0 31 Dec 2019
Phase Retrieval Using Conditional Generative Adversarial Networks Tobias Uelwer Alexander Oberstrass Stefan Harmeling GAN 27 25 0 10 Dec 2019
Manifold Gradient Descent Solves Multi-Channel Sparse Blind Deconvolution Provably and Efficiently Laixi Shi Yuejie Chi 30 26 0 25 Nov 2019
ISLET: Fast and Optimal Low-rank Tensor Regression via Importance Sketching Anru R. Zhang Yuetian Luo Garvesh Raskutti M. Yuan 27 44 0 09 Nov 2019
Denoising and Regularization via Exploiting the Structural Bias of Convolutional Generators Reinhard Heckel Mahdi Soltanolkotabi DiffM 35 81 0 31 Oct 2019
Online Stochastic Gradient Descent with Arbitrary Initialization Solves Non-smooth, Non-convex Phase Retrieval Yan Shuo Tan Roman Vershynin 22 35 0 28 Oct 2019
Statistical Analysis of Stationary Solutions of Coupled Nonconvex Nonsmooth Empirical Risk Minimization Zhengling Qi Ying Cui Yufeng Liu J. Pang 16 5 0 06 Oct 2019
Short-and-Sparse Deconvolution -- A Geometric Approach Yenson Lau Qing Qu Han-Wen Kuo Pengcheng Zhou Yuqian Zhang John N. Wright 22 29 0 28 Aug 2019
Max-Affine Regression: Provable, Tractable, and Near-Optimal Statistical Estimation Avishek Ghosh A. Pananjady Adityanand Guntuboyina Kannan Ramchandran 17 25 0 21 Jun 2019
Alternating Phase Projected Gradient Descent with Generative Priors for Solving Compressive Phase Retrieval Rakib Hyder Viraj Shah C. Hegde Ulugbek S. Kamilov 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
Blind Over-the-Air Computation and Data Fusion via Provable Wirtinger Flow Jialin Dong Yuanming Shi Z. Ding 11 59 0 12 Nov 2018
Quantization-Aware Phase Retrieval Subhadip Mukherjee C. Seelamantula MQ 13 2 0 02 Oct 2018
Convergence of Cubic Regularization for Nonconvex Optimization under KL Property Yi Zhou Zhe Wang Yingbin Liang 24 23 0 22 Aug 2018
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
Hypergraph Spectral Clustering in the Weighted Stochastic Block Model Kwangjun Ahn Kangwook Lee Changho Suh 24 62 0 23 May 2018
End-to-end Learning of a Convolutional Neural Network via Deep Tensor Decomposition Samet Oymak Mahdi Soltanolkotabi 21 12 0 16 May 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 42 168 0 01 Mar 2018
Non-convex Optimization for Machine Learning Prateek Jain Purushottam Kar 33 479 0 21 Dec 2017
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
Blind Gain and Phase Calibration via Sparse Spectral Methods Yanjun Li Kiryung Lee Y. Bresler 24 27 0 30 Nov 2017
Theoretical insights into the optimization landscape of over-parameterized shallow neural networks Mahdi Soltanolkotabi Adel Javanmard J. Lee 36 415 0 16 Jul 2017
Accelerated Stochastic Power Iteration Christopher De Sa Bryan D. He Ioannis Mitliagkas Christopher Ré Peng Xu 35 89 0 10 Jul 2017
Phase Retrieval via Randomized Kaczmarz: Theoretical Guarantees Yan Shuo Tan Roman Vershynin 16 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
Learning ReLUs via Gradient Descent Mahdi Soltanolkotabi MLT 23 181 0 10 May 2017
Estimating the Coefficients of a Mixture of Two Linear Regressions by Expectation Maximization Jason M. Klusowski Dana Yang W. Brinda 34 41 0 26 Apr 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
Stochastic Methods for Composite and Weakly Convex Optimization Problems John C. Duchi Feng Ruan 15 126 0 24 Mar 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
Phase Transitions of Spectral Initialization for High-Dimensional Nonconvex Estimation Yue M. Lu Gen Li 23 89 0 21 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
Phase Retrieval Meets Statistical Learning Theory: A Flexible Convex Relaxation S. Bahmani Justin Romberg 23 120 0 13 Oct 2016