Gradient Descent with Random Initialization: Fast Global Convergence for Nonconvex Phase Retrieval

21 March 2018

Papers citing "Gradient Descent with Random Initialization: Fast Global Convergence for Nonconvex Phase Retrieval"

50 / 53 papers shown

Title
Euclidean Distance Matrix Completion via Asymmetric Projected Gradient Descent Yicheng Li Xinghua Sun 39 0 0 28 Apr 2025
Gradient-based Learning in State-based Potential Games for Self-Learning Production Systems Steve Yuwono Marlon Löppenberg Dorothea Schwung Andreas Schwung 39 2 0 14 Jun 2024
Classifying Overlapping Gaussian Mixtures in High Dimensions: From Optimal Classifiers to Neural Nets Khen Cohen Noam Levi Yaron Oz BDL 36 1 0 28 May 2024
Top- $K$ ranking with a monotone adversary Yuepeng Yang Antares Chen Lorenzo Orecchia Cong Ma 37 1 0 12 Feb 2024
Gradient descent in matrix factorization: Understanding large initialization Hengchao Chen Xin Chen Mohamad Elmasri Qiang Sun AI4CE 31 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 44 33 0 18 May 2023
Convergence of Alternating Gradient Descent for Matrix Factorization R. Ward T. Kolda 29 6 0 11 May 2023
$Approximate message passing from random initialization with applications to $\mathbb{Z}_{2}$ synchronization$ Approximate message passing from random initialization with applications to $\mathbb{Z}_{2}$ synchronization Gen Li Wei Fan Yuting Wei 32 10 0 07 Feb 2023
Provable Phase Retrieval with Mirror Descent Jean-Jacques-Narcisse Godeme M. Fadili Xavier Buet M. Zerrad M. Lequime C. Amra 31 4 0 17 Oct 2022
From Gradient Flow on Population Loss to Learning with Stochastic Gradient Descent Satyen Kale Jason D. Lee Chris De Sa Ayush Sekhari Karthik Sridharan 36 4 0 13 Oct 2022
Misspecified Phase Retrieval with Generative Priors Zhaoqiang Liu Xinshao Wang Jiulong Liu 48 4 0 11 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 24 6 0 29 Sep 2022
Sudakov-Fernique post-AMP, and a new proof of the local convexity of the TAP free energy Michael Celentano 51 20 0 19 Aug 2022
Variational Bayesian inference for CP tensor completion with side information S. Budzinskiy N. Zamarashkin 21 1 0 24 Jun 2022
Robust Matrix Completion with Heavy-tailed Noise Bingyan Wang Jianqing Fan 24 4 0 09 Jun 2022
Model-Based Reinforcement Learning for Offline Zero-Sum Markov Games Yuling Yan Gen Li Yuxin Chen Jianqing Fan OffRL 31 10 0 08 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
Minimax Optimal Clustering of Bipartite Graphs with a Generalized Power Method Guillaume Braun Hemant Tyagi 27 5 0 24 May 2022
Accelerating nuclear-norm regularized low-rank matrix optimization through Burer-Monteiro decomposition Ching-pei Lee Ling Liang Tianyun Tang Kim-Chuan Toh 40 11 0 29 Apr 2022
Randomly Initialized Alternating Least Squares: Fast Convergence for Matrix Sensing Kiryung Lee Dominik Stöger 31 11 0 25 Apr 2022
An Algebraically Converging Stochastic Gradient Descent Algorithm for Global Optimization Bjorn Engquist Kui Ren Yunan Yang 19 6 0 12 Apr 2022
Tensor train completion: local recovery guarantees via Riemannian optimization S. Budzinskiy N. Zamarashkin 58 14 0 08 Oct 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
Global Convergence of Gradient Descent for Asymmetric Low-Rank Matrix Factorization Tian-Chun Ye S. Du 26 46 0 27 Jun 2021
Nonparametric Modeling of Higher-Order Interactions via Hypergraphons Krishnakumar Balasubramanian 22 12 0 18 May 2021
Efficient Sparse Coding using Hierarchical Riemannian Pursuit Ye Xue Vincent K. N. Lau Songfu Cai 35 3 0 21 Apr 2021
Spectral Methods for Data Science: A Statistical Perspective Yuxin Chen Yuejie Chi Jianqing Fan Cong Ma 51 165 0 15 Dec 2020
Low-Rank Matrix Recovery with Scaled Subgradient Methods: Fast and Robust Convergence Without the Condition Number Tian Tong Cong Ma Yuejie Chi 23 55 0 26 Oct 2020
Quickly Finding a Benign Region via Heavy Ball Momentum in Non-Convex Optimization Jun-Kun Wang Jacob D. Abernethy 24 7 0 04 Oct 2020
Uncertainty quantification for nonconvex tensor completion: Confidence intervals, heteroscedasticity and optimality Changxiao Cai H. Vincent Poor Yuxin Chen 18 23 0 15 Jun 2020
Hadamard Wirtinger Flow for Sparse Phase Retrieval Fan Wu Patrick Rebeschini 27 18 0 01 Jun 2020
On the Sample Complexity and Optimization Landscape for Quadratic Feasibility Problems Parth Thaker Gautam Dasarathy Angelia Nedić 24 5 0 04 Feb 2020
Consensus-Based Optimization on Hypersurfaces: Well-Posedness and Mean-Field Limit M. Fornasier Hui-Lin Huang L. Pareschi Philippe Sünnen 21 54 0 31 Jan 2020
Consensus-Based Optimization on the Sphere: Convergence to Global Minimizers and Machine Learning M. Fornasier Hui Huang L. Pareschi Philippe Sünnen 29 68 0 31 Jan 2020
Multicategory Angle-based Learning for Estimating Optimal Dynamic Treatment Regimes with Censored Data F. Xue Yanqing Zhang Wenzhuo Zhou H. Fu Annie Qu 12 14 0 14 Jan 2020
Revisiting Landscape Analysis in Deep Neural Networks: Eliminating Decreasing Paths to Infinity Shiyu Liang Ruoyu Sun R. Srikant 37 19 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
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 24 5 0 06 Oct 2019
Complex phase retrieval from subgaussian measurements Felix Krahmer Dominik Stöger 28 17 0 19 Jun 2019
A stochastic alternating minimizing method for sparse phase retrieval Jian-Feng Cai Yuling Jiao Xiliang Lu Juntao You 18 1 0 14 Jun 2019
Scale Invariant Power Iteration Cheolmin Kim Youngseok Kim Diego Klabjan 19 3 0 23 May 2019
A Selective Overview of Deep Learning Jianqing Fan Cong Ma Yiqiao Zhong BDL VLM 38 136 0 10 Apr 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 17 59 0 12 Nov 2018
Low-Rank Phase Retrieval via Variational Bayesian Learning Kaihui Liu Jiayi Wang Zhengli Xing Linxiao Yang Jun Fang BDL 19 13 0 05 Nov 2018
Defending Against Saddle Point Attack in Byzantine-Robust Distributed Learning Dong Yin Yudong Chen Kannan Ramchandran Peter L. Bartlett FedML 32 98 0 14 Jun 2018
Multichannel Sparse Blind Deconvolution on the Sphere Yanjun Li Y. Bresler 17 16 0 26 May 2018
Using Black-box Compression Algorithms for Phase Retrieval Milad Bakhshizadeh A. Maleki S. Jalali 13 8 0 08 Dec 2017
First-order Methods Almost Always Avoid Saddle Points Jason D. Lee Ioannis Panageas Georgios Piliouras Max Simchowitz Michael I. Jordan Benjamin Recht ODL 95 83 0 20 Oct 2017