A Geometric Analysis of Phase Retrieval

22 February 2016

Qing Qu

Papers citing "A Geometric Analysis of Phase Retrieval"

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Title
Preconditioned Gradient Descent for Over-Parameterized Nonconvex Matrix Factorization G. Zhang S. Fattahi Richard Y. Zhang 40 34 0 13 Apr 2025
Compressible Dynamics in Deep Overparameterized Low-Rank Learning & Adaptation Can Yaras Peng Wang Laura Balzano Qing Qu AI4CE 37 12 0 06 Jun 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
Nonconvex Stochastic Bregman Proximal Gradient Method with Application to Deep Learning Kuan-Fu Ding Jingyang Li Kim-Chuan Toh 25 8 0 26 Jun 2023
Gradient descent in matrix factorization: Understanding large initialization Hengchao Chen Xin Chen Mohamad Elmasri Qiang Sun AI4CE 23 1 0 30 May 2023
Smoothing the Landscape Boosts the Signal for SGD: Optimal Sample Complexity for Learning Single Index Models Alexandru Damian Eshaan Nichani Rong Ge Jason D. Lee MLT 36 33 0 18 May 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
Learning Single-Index Models with Shallow Neural Networks A. Bietti Joan Bruna Clayton Sanford M. Song 164 67 0 27 Oct 2022
Provable Phase Retrieval with Mirror Descent Jean-Jacques-Narcisse Godeme M. Fadili Xavier Buet M. Zerrad M. Lequime C. Amra 18 4 0 17 Oct 2022
Misspecified Phase Retrieval with Generative Priors Zhaoqiang Liu Xinshao Wang Jiulong Liu 38 4 0 11 Oct 2022
Zeroth-Order Negative Curvature Finding: Escaping Saddle Points without Gradients Hualin Zhang Huan Xiong Bin Gu 22 7 0 04 Oct 2022
Nonconvex Matrix Factorization is Geodesically Convex: Global Landscape Analysis for Fixed-rank Matrix Optimization From a Riemannian Perspective Yuetian Luo Nicolas García Trillos 17 6 0 29 Sep 2022
Gradient-Free Methods for Deterministic and Stochastic Nonsmooth Nonconvex Optimization Tianyi Lin Zeyu Zheng Michael I. Jordan 49 51 0 12 Sep 2022
Accelerating SGD for Highly Ill-Conditioned Huge-Scale Online Matrix Completion G. Zhang Hong-Ming Chiu Richard Y. Zhang 16 10 0 24 Aug 2022
SPIRAL: A superlinearly convergent incremental proximal algorithm for nonconvex finite sum minimization Pourya Behmandpoor P. Latafat Andreas Themelis Marc Moonen Panagiotis Patrinos 24 2 0 17 Jul 2022
Preconditioned Gradient Descent for Overparameterized Nonconvex Burer--Monteiro Factorization with Global Optimality Certification G. Zhang S. Fattahi Richard Y. Zhang 40 23 0 07 Jun 2022
Subspace Phase Retrieval Meng Xu Dekuan Dong J. Wang 16 2 0 06 Jun 2022
Signal Recovery with Non-Expansive Generative Network Priors Jorio Cocola 21 1 0 24 Apr 2022
Sharper Utility Bounds for Differentially Private Models Yilin Kang Yong Liu Jian Li Weiping Wang FedML 26 3 0 22 Apr 2022
On the Optimization Landscape of Neural Collapse under MSE Loss: Global Optimality with Unconstrained Features Jinxin Zhou Xiao Li Tian Ding Chong You Qing Qu Zhihui Zhu 22 97 0 02 Mar 2022
Escape saddle points by a simple gradient-descent based algorithm Chenyi Zhang Tongyang Li ODL 23 15 0 28 Nov 2021
A first-order primal-dual method with adaptivity to local smoothness Maria-Luiza Vladarean Yura Malitsky V. Cevher 11 15 0 28 Oct 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 25 9 0 03 Aug 2021
The loss landscape of deep linear neural networks: a second-order analysis E. M. Achour Franccois Malgouyres Sébastien Gerchinovitz ODL 22 9 0 28 Jul 2021
Improved Learning Rates for Stochastic Optimization: Two Theoretical Viewpoints Shaojie Li Yong Liu 20 13 0 19 Jul 2021
Small random initialization is akin to spectral learning: Optimization and generalization guarantees for overparameterized low-rank matrix reconstruction Dominik Stöger Mahdi Soltanolkotabi ODL 33 74 0 28 Jun 2021
Recursive Importance Sketching for Rank Constrained Least Squares: Algorithms and High-order Convergence Yuetian Luo Wen Huang Xudong Li Anru R. Zhang 21 15 0 17 Nov 2020
Second-Order Information in Non-Convex Stochastic Optimization: Power and Limitations Yossi Arjevani Y. Carmon John C. Duchi Dylan J. Foster Ayush Sekhari Karthik Sridharan 82 53 0 24 Jun 2020
Phase retrieval in high dimensions: Statistical and computational phase transitions Antoine Maillard Bruno Loureiro Florent Krzakala Lenka Zdeborová 18 56 0 09 Jun 2020
Accelerating Ill-Conditioned Low-Rank Matrix Estimation via Scaled Gradient Descent Tian Tong Cong Ma Yuejie Chi 19 113 0 18 May 2020
Likelihood landscape and maximum likelihood estimation for the discrete orbit recovery model Z. Fan Yi Sun Tianhao Wang Yihong Wu 22 18 0 31 Mar 2020
Inverse Problems, Deep Learning, and Symmetry Breaking Kshitij Tayal Chieh-Hsin Lai Vipin Kumar Ju Sun AI4CE 72 15 0 20 Mar 2020
Global Convergence and Variance-Reduced Optimization for a Class of Nonconvex-Nonconcave Minimax Problems Junchi Yang Negar Kiyavash Niao He 23 83 0 22 Feb 2020
On the Sample Complexity and Optimization Landscape for Quadratic Feasibility Problems Parth Thaker Gautam Dasarathy Angelia Nedić 16 5 0 04 Feb 2020
Revisiting Landscape Analysis in Deep Neural Networks: Eliminating Decreasing Paths to Infinity Shiyu Liang Ruoyu Sun R. Srikant 25 19 0 31 Dec 2019
Analysis of the Optimization Landscapes for Overcomplete Representation Learning Qing Qu Yuexiang Zhai Xiao Li Yuqian Zhang Zhihui Zhu 20 9 0 05 Dec 2019
Manifold Gradient Descent Solves Multi-Channel Sparse Blind Deconvolution Provably and Efficiently Laixi Shi Yuejie Chi 22 26 0 25 Nov 2019
Online Stochastic Gradient Descent with Arbitrary Initialization Solves Non-smooth, Non-convex Phase Retrieval Yan Shuo Tan Roman Vershynin 11 35 0 28 Oct 2019
On the Sample Complexity of Actor-Critic Method for Reinforcement Learning with Function Approximation Harshat Kumar Alec Koppel Alejandro Ribeiro 99 79 0 18 Oct 2019
A Deterministic Gradient-Based Approach to Avoid Saddle Points L. Kreusser Stanley J. Osher Bao Wang ODL 21 3 0 21 Jan 2019
On the Global Convergence of Imitation Learning: A Case for Linear Quadratic Regulator Qi Cai Mingyi Hong Yongxin Chen Zhaoran Wang 19 34 0 11 Jan 2019
On the Global Geometry of Sphere-Constrained Sparse Blind Deconvolution Yuqian Zhang Yenson Lau Han-Wen Kuo S. Cheung A. Pasupathy John N. Wright 19 49 0 07 Jan 2019
Diffusion Approximations for Online Principal Component Estimation and Global Convergence C. J. Li Mengdi Wang Han Liu Tong Zhang 26 12 0 29 Aug 2018
Convergence of Cubic Regularization for Nonconvex Optimization under KL Property Yi Zhou Zhe Wang Yingbin Liang 24 23 0 22 Aug 2018
On the Implicit Bias of Dropout Poorya Mianjy R. Arora René Vidal 19 66 0 26 Jun 2018
The Global Optimization Geometry of Shallow Linear Neural Networks Zhihui Zhu Daniel Soudry Yonina C. Eldar M. Wakin ODL 16 36 0 13 May 2018
Stochastic model-based minimization of weakly convex functions Damek Davis D. Drusvyatskiy 22 370 0 17 Mar 2018
Smoothed analysis for low-rank solutions to semidefinite programs in quadratic penalty form Srinadh Bhojanapalli Nicolas Boumal Prateek Jain Praneeth Netrapalli 20 42 0 01 Mar 2018
Stochastic Variance-Reduced Cubic Regularization for Nonconvex Optimization Zhe Wang Yi Zhou Yingbin Liang Guanghui Lan 29 46 0 20 Feb 2018