Guaranteed Matrix Completion via Non-convex Factorization

28 November 2014

Papers citing "Guaranteed Matrix Completion via Non-convex Factorization"

50 / 68 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 40 34 0 13 Apr 2025
Matrix Completion with Graph Information: A Provable Nonconvex Optimization Approach Yao Wang Yiyang Yang Kaidong Wang Shanxing Gao Xiuwu Liao 63 0 0 12 Feb 2025
Implicit Bias in Matrix Factorization and its Explicit Realization in a New Architecture Yikun Hou Suvrit Sra A. Yurtsever 29 0 0 28 Jan 2025
Fast and Provable Tensor-Train Format Tensor Completion via Precondtioned Riemannian Gradient Descent Fengmiao Bian Jian-Feng Cai Xiaoqun Zhang Yuanwei Zhang 70 0 0 23 Jan 2025
Computational and Statistical Guarantees for Tensor-on-Tensor Regression with Tensor Train Decomposition Zhen Qin Zhihui Zhu 74 4 0 10 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
$Discrete Aware Matrix Completion via Convexized $\ell_0$-Norm Approximation$ Discrete Aware Matrix Completion via Convexized $\ell_0$ -Norm Approximation Niclas Führling Kengo Ando Giuseppe Thadeu Freitas de Abreu David González González Osvaldo Gonsa 28 1 0 03 May 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
Gradient-Based Spectral Embeddings of Random Dot Product Graphs Marcelo Fiori Bernardo Marenco Federico Larroca P. Bermolen Gonzalo Mateos BDL 27 3 0 25 Jul 2023
A Novel Stochastic Gradient Descent Algorithm for Learning Principal Subspaces Charline Le Lan Joshua Greaves Jesse Farebrother Mark Rowland Fabian Pedregosa Rishabh Agarwal Marc G. Bellemare 44 8 0 08 Dec 2022
Learning Transition Operators From Sparse Space-Time Samples C. Kümmerle Mauro Maggioni Sui Tang 26 1 0 01 Dec 2022
Nonconvex Matrix Factorization is Geodesically Convex: Global Landscape Analysis for Fixed-rank Matrix Optimization From a Riemannian Perspective Yuetian Luo Nicolas García Trillos 19 6 0 29 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
Personalized PCA: Decoupling Shared and Unique Features Naichen Shi Raed Al Kontar 22 14 0 17 Jul 2022
Robust Matrix Completion with Heavy-tailed Noise Bingyan Wang Jianqing Fan 21 3 0 09 Jun 2022
Preconditioned Gradient Descent for Overparameterized Nonconvex Burer--Monteiro Factorization with Global Optimality Certification G. Zhang S. Fattahi Richard Y. Zhang 42 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 19 11 0 29 Apr 2022
Convergence of gradient descent for deep neural networks S. Chatterjee ODL 21 20 0 30 Mar 2022
On Uniform Boundedness Properties of SGD and its Momentum Variants Xiaoyu Wang M. Johansson 23 3 0 25 Jan 2022
Fair and efficient contribution valuation for vertical federated learning Zhenan Fan Huang Fang Zirui Zhou Jian Pei M. Friedlander Yong Zhang TDI FedML 19 25 0 07 Jan 2022
On Asymptotic Linear Convergence of Projected Gradient Descent for Constrained Least Squares Trung Vu Raviv Raich 15 13 0 22 Dec 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
Global Convergence of Gradient Descent for Asymmetric Low-Rank Matrix Factorization Tian-Chun Ye S. Du 19 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
Time Series Forecasting via Learning Convolutionally Low-Rank Models Guangcan Liu AI4TS 29 13 0 23 Apr 2021
Sharp Global Guarantees for Nonconvex Low-rank Recovery in the Noisy Overparameterized Regime Richard Y. Zhang 39 1 0 21 Apr 2021
Exact Linear Convergence Rate Analysis for Low-Rank Symmetric Matrix Completion via Gradient Descent Trung Vu Raviv Raich 25 10 0 04 Feb 2021
Spectral Methods for Data Science: A Statistical Perspective Yuxin Chen Yuejie Chi Jianqing Fan Cong Ma 34 165 0 15 Dec 2020
Recursive Importance Sketching for Rank Constrained Least Squares: Algorithms and High-order Convergence Yuetian Luo Wen Huang Xudong Li Anru R. Zhang 23 15 0 17 Nov 2020
Accelerating Ill-Conditioned Low-Rank Matrix Estimation via Scaled Gradient Descent Tian Tong Cong Ma Yuejie Chi 19 113 0 18 May 2020
An Optimal Statistical and Computational Framework for Generalized Tensor Estimation Rungang Han Rebecca Willett Anru R. Zhang 27 65 0 26 Feb 2020
Stochastic Polyak Step-size for SGD: An Adaptive Learning Rate for Fast Convergence Nicolas Loizou Sharan Vaswani I. Laradji Simon Lacoste-Julien 27 181 0 24 Feb 2020
Online high rank matrix completion Jicong Fan Madeleine Udell OffRL 21 34 0 20 Feb 2020
Rank $2r$ iterative least squares: efficient recovery of ill-conditioned low rank matrices from few entries Jonathan Bauch B. Nadler Pini Zilber 19 13 0 05 Feb 2020
A frequency-domain analysis of inexact gradient methods Oran Gannot 16 25 0 31 Dec 2019
Revisiting Landscape Analysis in Deep Neural Networks: Eliminating Decreasing Paths to Infinity Shiyu Liang Ruoyu Sun R. Srikant 25 19 0 31 Dec 2019
Factor Group-Sparse Regularization for Efficient Low-Rank Matrix Recovery Jicong Fan Lijun Ding Yudong Chen Madeleine Udell 12 69 0 13 Nov 2019
Latent Function Decomposition for Forecasting Li-ion Battery Cells Capacity: A Multi-Output Convolved Gaussian Process Approach Abdallah A. Chehade A. Hussein BDL 13 16 0 19 Jul 2019
Testing Matrix Rank, Optimally Maria-Florina Balcan Yi Li David P. Woodruff Hongyang R. Zhang 16 23 0 18 Oct 2018
Fast and Faster Convergence of SGD for Over-Parameterized Models and an Accelerated Perceptron Sharan Vaswani Francis R. Bach Mark W. Schmidt 30 296 0 16 Oct 2018
Continuous-time Models for Stochastic Optimization Algorithms Antonio Orvieto Aurelien Lucchi 11 31 0 05 Oct 2018
A Survey on Nonconvex Regularization Based Sparse and Low-Rank Recovery in Signal Processing, Statistics, and Machine Learning Fei Wen L. Chu Peilin Liu Robert C. Qiu 23 153 0 16 Aug 2018
A review on distance based time series classification A. Abanda U. Mori Jose A. Lozano AI4TS 11 248 0 12 Jun 2018
Fast and Sample Efficient Inductive Matrix Completion via Multi-Phase Procrustes Flow Xiao Zhang S. Du Quanquan Gu 23 24 0 03 Mar 2018
Smoothed analysis for low-rank solutions to semidefinite programs in quadratic penalty form Srinadh Bhojanapalli Nicolas Boumal Prateek Jain Praneeth Netrapalli 23 42 0 01 Mar 2018
Asynchronous Stochastic Proximal Methods for Nonconvex Nonsmooth Optimization Rui Zhu Di Niu Zongpeng Li 6 4 0 24 Feb 2018
Non-convex Optimization for Machine Learning Prateek Jain Purushottam Kar 24 478 0 21 Dec 2017
Blind Gain and Phase Calibration via Sparse Spectral Methods Yanjun Li Kiryung Lee Y. Bresler 19 27 0 30 Nov 2017
Analysis of Biased Stochastic Gradient Descent Using Sequential Semidefinite Programs Bin Hu Peter M. Seiler Laurent Lessard 16 38 0 03 Nov 2017