Matrix Completion has No Spurious Local Minimum

24 May 2016

Papers citing "Matrix Completion has No Spurious Local Minimum"

50 / 102 papers shown

Title
Euclidean Distance Matrix Completion via Asymmetric Projected Gradient Descent Yicheng Li Xinghua Sun 39 0 0 28 Apr 2025
Preconditioned Gradient Descent for Over-Parameterized Nonconvex Matrix Factorization G. Zhang S. Fattahi Richard Y. Zhang 45 36 0 13 Apr 2025
A Piecewise Lyapunov Analysis of Sub-quadratic SGD: Applications to Robust and Quantile Regression Yixuan Zhang Dongyan Yudong Chen Qiaomin Xie 29 0 0 11 Apr 2025
Analyzing the Role of Permutation Invariance in Linear Mode Connectivity Keyao Zhan Puheng Li Lei Wu MoMe 82 0 0 13 Mar 2025
On Newton's Method to Unlearn Neural Networks Nhung Bui Xinyang Lu Rachael Hwee Ling Sim See-Kiong Ng Bryan Kian Hsiang Low MU 41 2 0 20 Jun 2024
Compressible Dynamics in Deep Overparameterized Low-Rank Learning & Adaptation Can Yaras Peng Wang Laura Balzano Qing Qu AI4CE 37 12 0 06 Jun 2024
Preparing for Black Swans: The Antifragility Imperative for Machine Learning Ming Jin 38 2 0 18 May 2024
Wave Physics-informed Matrix Factorizations Harsha Vardhan Tetali J. Harley B. Haeffele 35 0 0 21 Dec 2023
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 30 8 0 26 Jun 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 42 33 0 18 May 2023
Understanding Incremental Learning of Gradient Descent: A Fine-grained Analysis of Matrix Sensing Jikai Jin Zhiyuan Li Kaifeng Lyu S. Du Jason D. Lee MLT 54 34 0 27 Jan 2023
Escaping From Saddle Points Using Asynchronous Coordinate Gradient Descent Marco Bornstein Jin-Peng Liu Jingling Li Furong Huang 21 0 0 17 Nov 2022
Learning Single-Index Models with Shallow Neural Networks A. Bietti Joan Bruna Clayton Sanford M. Song 167 67 0 27 Oct 2022
Simple Alternating Minimization Provably Solves Complete Dictionary Learning Geyu Liang G. Zhang S. Fattahi Richard Y. Zhang 15 5 0 23 Oct 2022
Zeroth-Order Negative Curvature Finding: Escaping Saddle Points without Gradients Hualin Zhang Huan Xiong Bin Gu 32 7 0 04 Oct 2022
Are All Losses Created Equal: A Neural Collapse Perspective Jinxin Zhou Chong You Xiao Li Kangning Liu Sheng Liu Qing Qu Zhihui Zhu 36 58 0 04 Oct 2022
Behind the Scenes of Gradient Descent: A Trajectory Analysis via Basis Function Decomposition Jianhao Ma Li-Zhen Guo S. Fattahi 38 4 0 01 Oct 2022
On Quantum Speedups for Nonconvex Optimization via Quantum Tunneling Walks Yizhou Liu Weijie J. Su Tongyang Li 24 17 0 29 Sep 2022
A Validation Approach to Over-parameterized Matrix and Image Recovery Lijun Ding Zhen Qin Liwei Jiang Jinxin Zhou Zhihui Zhu 48 13 0 21 Sep 2022
Gradient-Free Methods for Deterministic and Stochastic Nonsmooth Nonconvex Optimization Tianyi Lin Zeyu Zheng Michael I. Jordan 59 51 0 12 Sep 2022
Implicit Full Waveform Inversion with Deep Neural Representation Jian Sun K. Innanen AI4CE 40 32 0 08 Sep 2022
Accelerating SGD for Highly Ill-Conditioned Huge-Scale Online Matrix Completion G. Zhang Hong-Ming Chiu Richard Y. Zhang 24 10 0 24 Aug 2022
Identifying good directions to escape the NTK regime and efficiently learn low-degree plus sparse polynomials Eshaan Nichani Yunzhi Bai Jason D. Lee 29 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 50 23 0 07 Jun 2022
Accelerating nuclear-norm regularized low-rank matrix optimization through Burer-Monteiro decomposition Ching-pei Lee Ling Liang Tianyun Tang Kim-Chuan Toh 24 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
Signal Recovery with Non-Expansive Generative Network Priors Jorio Cocola 21 1 0 24 Apr 2022
Tensor Completion for Causal Inference with Multivariate Longitudinal Data: A Reevaluation of COVID-19 Mandates Jonathan Auerbach M. Slawski Shixue Zhang 19 0 0 09 Mar 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 27 97 0 02 Mar 2022
Tackling benign nonconvexity with smoothing and stochastic gradients Harsh Vardhan Sebastian U. Stich 28 8 0 18 Feb 2022
Escape saddle points by a simple gradient-descent based algorithm Chenyi Zhang Tongyang Li ODL 25 15 0 28 Nov 2021
Nonparametric Matrix Estimation with One-Sided Covariates Chao Yu 21 3 0 26 Oct 2021
Private Alternating Least Squares: Practical Private Matrix Completion with Tighter Rates Steve Chien Prateek Jain Walid Krichene Steffen Rendle Shuang Song Abhradeep Thakurta Li Zhang 25 19 0 20 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 42 75 0 28 Jun 2021
Global Convergence of Gradient Descent for Asymmetric Low-Rank Matrix Factorization Tian-Chun Ye S. Du 21 46 0 27 Jun 2021
GNMR: A provable one-line algorithm for low rank matrix recovery Pini Zilber B. Nadler 48 13 0 24 Jun 2021
Escaping Saddle Points with Compressed SGD Dmitrii Avdiukhin G. Yaroslavtsev 19 4 0 21 May 2021
A Geometric Analysis of Neural Collapse with Unconstrained Features Zhihui Zhu Tianyu Ding Jinxin Zhou Xiao Li Chong You Jeremias Sulam Qing Qu 27 194 0 06 May 2021
Efficient Sparse Coding using Hierarchical Riemannian Pursuit Ye Xue Vincent K. N. Lau Songfu Cai 31 3 0 21 Apr 2021
Sharp Global Guarantees for Nonconvex Low-rank Recovery in the Noisy Overparameterized Regime Richard Y. Zhang 44 25 0 21 Apr 2021
Noisy Gradient Descent Converges to Flat Minima for Nonconvex Matrix Factorization Tianyi Liu Yan Li S. Wei Enlu Zhou T. Zhao 21 13 0 24 Feb 2021
Exact Linear Convergence Rate Analysis for Low-Rank Symmetric Matrix Completion via Gradient Descent Trung Vu Raviv Raich 40 10 0 04 Feb 2021
HePPCAT: Probabilistic PCA for Data with Heteroscedastic Noise David Hong Kyle Gilman Laura Balzano Jeffrey A. Fessler 40 19 0 10 Jan 2021
On the Efficient Implementation of the Matrix Exponentiated Gradient Algorithm for Low-Rank Matrix Optimization Dan Garber Atara Kaplan 14 4 0 18 Dec 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
Shape Matters: Understanding the Implicit Bias of the Noise Covariance Jeff Z. HaoChen Colin Wei J. Lee Tengyu Ma 29 93 0 15 Jun 2020
An Analysis of Constant Step Size SGD in the Non-convex Regime: Asymptotic Normality and Bias Lu Yu Krishnakumar Balasubramanian S. Volgushev Murat A. Erdogdu 35 50 0 14 Jun 2020
Accelerating Ill-Conditioned Low-Rank Matrix Estimation via Scaled Gradient Descent Tian Tong Cong Ma Yuejie Chi 27 113 0 18 May 2020
The Landscape of Matrix Factorization Revisited Hossein Valavi Sulin Liu Peter J. Ramadge 12 5 0 27 Feb 2020