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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 / 124 papers shown

Title
Euclidean Distance Matrix Completion via Asymmetric Projected Gradient Descent Yicheng Li Xinghua Sun 77 0 0 28 Apr 2025
Learning a Class of Mixed Linear Regressions: Global Convergence under General Data Conditions Yujing Liu Zhixin Liu Lei Guo 80 0 0 24 Mar 2025
$k$ -SVD with Gradient Descent Emily Gan Yassir Jedra Devavrat Shah 128 0 0 01 Feb 2025
Stability properties of gradient flow dynamics for the symmetric low-rank matrix factorization problem Hesameddin Mohammadi Mohammad Tinati Stephen Tu Mahdi Soltanolkotabi M. Jovanović 156 0 0 24 Nov 2024
Sample and Computationally Efficient Robust Learning of Gaussian Single-Index Models Puqian Wang Nikos Zarifis Ilias Diakonikolas Jelena Diakonikolas 68 1 0 08 Nov 2024
Global convergence of gradient descent for phase retrieval Théodore Fougereux Cédric Josz Xiaopeng Li 68 0 0 13 Oct 2024
In-depth Analysis of Low-rank Matrix Factorisation in a Federated Setting Constantin Philippenko Kevin Scaman Laurent Massoulié FedML 110 1 0 13 Sep 2024
A Sample Efficient Alternating Minimization-based Algorithm For Robust Phase Retrieval Adarsh Barik Anand Krishna Vincent Y. F. Tan 57 0 0 07 Sep 2024
Smoothed Robust Phase Retrieval Zhong Zheng Lingzhou Xue 58 2 0 03 Sep 2024
Non-convex matrix sensing: Breaking the quadratic rank barrier in the sample complexity Dominik Stoger Yizhe Zhu 84 2 0 20 Aug 2024
Gradient-based Learning in State-based Potential Games for Self-Learning Production Systems Steve Yuwono Marlon Löppenberg Dorothea Schwung Andreas Schwung 56 3 0 14 Jun 2024
Tilting the Odds at the Lottery: the Interplay of Overparameterisation and Curricula in Neural Networks Stefano Sarao Mannelli Yaraslau Ivashinka Andrew M. Saxe Luca Saglietti 67 2 0 03 Jun 2024
Agnostic Learning of Mixed Linear Regressions with EM and AM Algorithms A. Ghosh Arya Mazumdar FedML 59 0 0 03 Jun 2024
Classifying Overlapping Gaussian Mixtures in High Dimensions: From Optimal Classifiers to Neural Nets Khen Cohen Noam Levi Yaron Oz BDL 74 1 0 28 May 2024
Incorporating Gradients to Rules: Towards Lightweight, Adaptive Provenance-based Intrusion Detection Lingzhi Wang Xiangmin Shen Weijian Li Zhenyuan Li R. Sekar Han Liu Yan Chen AAML 66 1 0 23 Apr 2024
Top- $K$ ranking with a monotone adversary Yuepeng Yang Antares Chen Lorenzo Orecchia Cong Ma 90 1 0 12 Feb 2024
The Local Landscape of Phase Retrieval Under Limited Samples Kaizhao Liu Zihao Wang Lei Wu 55 2 0 26 Nov 2023
Acceleration and Implicit Regularization in Gaussian Phase Retrieval Tyler Maunu M. Molina-Fructuoso 82 0 0 21 Nov 2023
EM for Mixture of Linear Regression with Clustered Data Amirhossein Reisizadeh Khashayar Gatmiry Asuman Ozdaglar FedML 45 1 0 22 Aug 2023
Near Optimal Heteroscedastic Regression with Symbiotic Learning Dheeraj Baby Aniket Das Dheeraj M. Nagaraj Praneeth Netrapalli 86 3 0 25 Jun 2023
Gradient descent in matrix factorization: Understanding large initialization Hengchao Chen Xin Chen Mohamad Elmasri Qiang Sun AI4CE 52 1 0 30 May 2023
Escaping mediocrity: how two-layer networks learn hard generalized linear models with SGD Luca Arnaboldi Florent Krzakala Bruno Loureiro Ludovic Stephan MLT 99 5 0 29 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 96 39 0 18 May 2023
Convergence of Alternating Gradient Descent for Matrix Factorization R. Ward T. Kolda 82 9 0 11 May 2023
SGD learning on neural networks: leap complexity and saddle-to-saddle dynamics Emmanuel Abbe Enric Boix-Adserà Theodor Misiakiewicz FedML MLT 162 86 0 21 Feb 2023
Sharp analysis of EM for learning mixtures of pairwise differences A. Dhawan Cheng Mao A. Pananjady 60 1 0 20 Feb 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 91 12 0 07 Feb 2023
The Power of Preconditioning in Overparameterized Low-Rank Matrix Sensing Xingyu Xu Yandi Shen Yuejie Chi Cong Ma 122 37 0 02 Feb 2023
Rank-1 Matrix Completion with Gradient Descent and Small Random Initialization Daesung Kim Hye Won Chung 86 2 0 19 Dec 2022
Provable Phase Retrieval with Mirror Descent Jean-Jacques-Narcisse Godeme M. Fadili Xavier Buet M. Zerrad M. Lequime C. Amra 57 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 42 4 0 13 Oct 2022
Misspecified Phase Retrieval with Generative Priors Zhaoqiang Liu Xinshao Wang Jiulong Liu 79 6 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 52 7 0 29 Sep 2022
Sudakov-Fernique post-AMP, and a new proof of the local convexity of the TAP free energy Michael Celentano 89 21 0 19 Aug 2022
Improved Global Guarantees for the Nonconvex Burer--Monteiro Factorization via Rank Overparameterization Richard Y. Zhang 106 24 0 05 Jul 2022
Variational Bayesian inference for CP tensor completion with side information S. Budzinskiy N. Zamarashkin 47 2 0 24 Jun 2022
Robust Matrix Completion with Heavy-tailed Noise Bingyan Wang Jianqing Fan 68 7 0 09 Jun 2022
Model-Based Reinforcement Learning for Offline Zero-Sum Markov Games Yuling Yan Gen Li Yuxin Chen Jianqing Fan OffRL 102 11 0 08 Jun 2022
Preconditioned Gradient Descent for Overparameterized Nonconvex Burer--Monteiro Factorization with Global Optimality Certification G. Zhang Salar Fattahi Richard Y. Zhang 163 24 0 07 Jun 2022
Minimax Optimal Clustering of Bipartite Graphs with a Generalized Power Method Guillaume Braun Hemant Tyagi 77 5 0 24 May 2022
Can We Do Better Than Random Start? The Power of Data Outsourcing Yi Chen Jing-rong Dong Xin T. Tong 33 0 0 17 May 2022
Accelerating nuclear-norm regularized low-rank matrix optimization through Burer-Monteiro decomposition Ching-pei Lee Ling Liang Tianyun Tang Kim-Chuan Toh 92 13 0 29 Apr 2022
Randomly Initialized Alternating Least Squares: Fast Convergence for Matrix Sensing Kiryung Lee Dominik Stöger 65 11 0 25 Apr 2022
An Algebraically Converging Stochastic Gradient Descent Algorithm for Global Optimization Bjorn Engquist Kui Ren Yunan Yang 123 6 0 12 Apr 2022
An Oracle Gradient Regularized Newton Method for Quadratic Measurements Regression Jun Fan Jie Sun Ailing Yan Shenglong Zhou 40 3 0 19 Feb 2022
Learning a Single Neuron for Non-monotonic Activation Functions Lei Wu MLT 60 11 0 16 Feb 2022
Towards Statistical and Computational Complexities of Polyak Step Size Gradient Descent Zhaolin Ren Fuheng Cui Alexia Atsidakou Sujay Sanghavi Nhat Ho 31 6 0 15 Oct 2021
Tensor train completion: local recovery guarantees via Riemannian optimization S. Budzinskiy N. Zamarashkin 103 15 0 08 Oct 2021
Inference for Heteroskedastic PCA with Missing Data Yuling Yan Yuxin Chen Jianqing Fan 122 19 0 26 Jul 2021
Towards Sample-Optimal Compressive Phase Retrieval with Sparse and Generative Priors Zhaoqiang Liu Subhro Ghosh Jonathan Scarlett 47 18 0 29 Jun 2021