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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
Small random initialization is akin to spectral learning: Optimization and generalization guarantees for overparameterized low-rank matrix reconstruction Dominik Stöger Mahdi Soltanolkotabi ODL 80 78 0 28 Jun 2021
Global Convergence of Gradient Descent for Asymmetric Low-Rank Matrix Factorization Tian-Chun Ye S. Du 66 48 0 27 Jun 2021
On the Cryptographic Hardness of Learning Single Periodic Neurons M. Song Ilias Zadik Joan Bruna AAML 65 28 0 20 Jun 2021
Submodular + Concave Siddharth Mitra Moran Feldman Amin Karbasi 35 19 0 09 Jun 2021
Escaping Saddle Points Faster with Stochastic Momentum Jun-Kun Wang Chi-Heng Lin Jacob D. Abernethy ODL 77 22 0 05 Jun 2021
Bandit Phase Retrieval Tor Lattimore Botao Hao 84 13 0 03 Jun 2021
Lecture notes on non-convex algorithms for low-rank matrix recovery Irène Waldspurger 58 1 0 21 May 2021
Nonparametric Modeling of Higher-Order Interactions via Hypergraphons Krishnakumar Balasubramanian 59 12 0 18 May 2021
Sample Efficient Linear Meta-Learning by Alternating Minimization K. K. Thekumparampil Prateek Jain Praneeth Netrapalli Sewoong Oh 55 23 0 18 May 2021
Scaling and Scalability: Provable Nonconvex Low-Rank Tensor Estimation from Incomplete Measurements Tian Tong Cong Ma Ashley Prater-Bennette Erin E. Tripp Yuejie Chi 108 33 0 29 Apr 2021
Low-rank Tensor Estimation via Riemannian Gauss-Newton: Statistical Optimality and Second-Order Convergence Yuetian Luo Anru R. Zhang 157 20 0 24 Apr 2021
Efficient Sparse Coding using Hierarchical Riemannian Pursuit Ye Xue Vincent K. N. Lau Songfu Cai 152 3 0 21 Apr 2021
Stochasticity helps to navigate rough landscapes: comparing gradient-descent-based algorithms in the phase retrieval problem Francesca Mignacco Pierfrancesco Urbani Lenka Zdeborová 83 36 0 08 Mar 2021
Beyond Procrustes: Balancing-Free Gradient Descent for Asymmetric Low-Rank Matrix Sensing Cong Ma Yuanxin Li Yuejie Chi 48 3 0 13 Jan 2021
Fast Global Convergence for Low-rank Matrix Recovery via Riemannian Gradient Descent with Random Initialization T. Hou Zhenzhen Li Ziyun Zhang 72 18 0 31 Dec 2020
Stochastic Approximation for Online Tensorial Independent Component Analysis C. J. Li Michael I. Jordan 59 2 0 28 Dec 2020
Spectral Methods for Data Science: A Statistical Perspective Yuxin Chen Yuejie Chi Jianqing Fan Cong Ma 153 173 0 15 Dec 2020
Recent Theoretical Advances in Non-Convex Optimization Marina Danilova Pavel Dvurechensky Alexander Gasnikov Eduard A. Gorbunov Sergey Guminov Dmitry Kamzolov Innokentiy Shibaev 129 79 0 11 Dec 2020
Optimal Sample Complexity of Subgradient Descent for Amplitude Flow via Non-Lipschitz Matrix Concentration Paul Hand Oscar Leong V. Voroninski 39 1 0 31 Oct 2020
Low-Rank Matrix Recovery with Scaled Subgradient Methods: Fast and Robust Convergence Without the Condition Number Tian Tong Cong Ma Yuejie Chi 105 56 0 26 Oct 2020
Understanding How Over-Parametrization Leads to Acceleration: A case of learning a single teacher neuron Jun-Kun Wang Jacob D. Abernethy 16 1 0 04 Oct 2020
Quickly Finding a Benign Region via Heavy Ball Momentum in Non-Convex Optimization Jun-Kun Wang Jacob D. Abernethy 108 7 0 04 Oct 2020
Learning Mixtures of Low-Rank Models Yanxi Chen Cong Ma H. Vincent Poor Yuxin Chen 57 13 0 23 Sep 2020
Understanding and Detecting Convergence for Stochastic Gradient Descent with Momentum Jerry Chee Ping Li 43 12 0 27 Aug 2020
Convex and Nonconvex Optimization Are Both Minimax-Optimal for Noisy Blind Deconvolution under Random Designs Yuxin Chen Jianqing Fan B. Wang Yuling Yan 90 16 0 04 Aug 2020
From Symmetry to Geometry: Tractable Nonconvex Problems Yuqian Zhang Qing Qu John N. Wright 87 45 0 14 Jul 2020
Differentiable Programming for Hyperspectral Unmixing using a Physics-based Dispersion Model J. Janiczek Parth Thaker Gautam Dasarathy C. Edwards P. Christensen Suren Jayasuriya 139 3 0 12 Jul 2020
Optimization and Generalization of Shallow Neural Networks with Quadratic Activation Functions Stefano Sarao Mannelli Eric Vanden-Eijnden Lenka Zdeborová AI4CE 67 49 0 27 Jun 2020
Uncertainty quantification for nonconvex tensor completion: Confidence intervals, heteroscedasticity and optimality Changxiao Cai H. Vincent Poor Yuxin Chen 118 23 0 15 Jun 2020
Complex Dynamics in Simple Neural Networks: Understanding Gradient Flow in Phase Retrieval Stefano Sarao Mannelli Giulio Biroli C. Cammarota Florent Krzakala Pierfrancesco Urbani Lenka Zdeborová 53 28 0 12 Jun 2020
Homomorphic Sensing of Subspace Arrangements Liangzu Peng M. Tsakiris 47 13 0 09 Jun 2020
Exit Time Analysis for Approximations of Gradient Descent Trajectories Around Saddle Points Rishabh Dixit Mert Gurbuzbalaban W. Bajwa 41 3 0 01 Jun 2020
Hadamard Wirtinger Flow for Sparse Phase Retrieval Fan Wu Patrick Rebeschini 79 18 0 01 Jun 2020
Instability, Computational Efficiency and Statistical Accuracy Nhat Ho K. Khamaru Raaz Dwivedi Martin J. Wainwright Michael I. Jordan Bin Yu 70 20 0 22 May 2020
Online stochastic gradient descent on non-convex losses from high-dimensional inference Gerard Ben Arous Reza Gheissari Aukosh Jagannath 88 91 0 23 Mar 2020
$Complete Dictionary Learning via $\ell_p$-norm Maximization$ Complete Dictionary Learning via $\ell_p$ -norm Maximization Yifei Shen Ye Xue Jun Zhang Khaled B. Letaief Vincent K. N. Lau 66 15 0 24 Feb 2020
On the Sample Complexity and Optimization Landscape for Quadratic Feasibility Problems Parth Thaker Gautam Dasarathy Angelia Nedić 46 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 82 56 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 129 69 0 31 Jan 2020
Bridging Convex and Nonconvex Optimization in Robust PCA: Noise, Outliers, and Missing Data Yuxin Chen Jianqing Fan Cong Ma Yuling Yan 89 52 0 15 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 55 15 0 14 Jan 2020
Revisiting Landscape Analysis in Deep Neural Networks: Eliminating Decreasing Paths to Infinity Shiyu Liang Ruoyu Sun R. Srikant 81 20 0 31 Dec 2019
Manifold Gradient Descent Solves Multi-Channel Sparse Blind Deconvolution Provably and Efficiently Laixi Shi Yuejie Chi 86 26 0 25 Nov 2019
Nonconvex Low-Rank Tensor Completion from Noisy Data Changxiao Cai Gen Li H. Vincent Poor Yuxin Chen 145 82 0 11 Nov 2019
Online Stochastic Gradient Descent with Arbitrary Initialization Solves Non-smooth, Non-convex Phase Retrieval Yan Shuo Tan Roman Vershynin 79 35 0 28 Oct 2019
$Subspace Estimation from Unbalanced and Incomplete Data Matrices: $\ell_{2,\infty}$ Statistical Guarantees$ Subspace Estimation from Unbalanced and Incomplete Data Matrices: $\ell_{2,\infty}$ Statistical Guarantees Changxiao Cai Gen Li Yuejie Chi H. Vincent Poor Yuxin Chen 102 13 0 09 Oct 2019
Statistical Analysis of Stationary Solutions of Coupled Nonconvex Nonsmooth Empirical Risk Minimization Zhengling Qi Ying Cui Yufeng Liu J. Pang 92 5 0 06 Oct 2019
$Randomly initialized EM algorithm for two-component Gaussian mixture achieves near optimality in $O(\sqrt{n})$ iterations$ Randomly initialized EM algorithm for two-component Gaussian mixture achieves near optimality in $O(\sqrt{n})$ iterations Yihong Wu Harrison H. Zhou 275 43 0 28 Aug 2019
A Nonconvex Approach for Exact and Efficient Multichannel Sparse Blind Deconvolution Qing Qu Xiao Li Zhihui Zhu 103 31 0 28 Aug 2019
Distributed Global Optimization by Annealing Brian Swenson S. Kar H. Vincent Poor José M. F. Moura 101 3 0 20 Jul 2019