Global Convergence of Stochastic Gradient Descent for Some Non-convex Matrix Problems

5 November 2014

Papers citing "Global Convergence of Stochastic Gradient Descent for Some Non-convex Matrix Problems"

31 / 31 papers shown

Title
Global Convergence of Adaptive Sensing for Principal Eigenvector Estimation Alex Saad-Falcon Brighton Ancelin Justin Romberg 19 0 0 16 May 2025
Black-Box $k$ -to- $1$ -PCA Reductions: Theory and Applications A. Jambulapati Syamantak Kumar Jerry Li Shourya Pandey Ankit Pensia Kevin Tian 39 2 0 06 Mar 2024
Demystifying the Myths and Legends of Nonconvex Convergence of SGD Aritra Dutta El Houcine Bergou Soumia Boucherouite Nicklas Werge M. Kandemir Xin Li 26 0 0 19 Oct 2023
QuIP: 2-Bit Quantization of Large Language Models With Guarantees Jerry Chee Yaohui Cai Volodymyr Kuleshov Chris De Sa MQ 45 189 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 52 8 0 08 Dec 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 27 4 0 13 Oct 2022
Preference Dynamics Under Personalized Recommendations Sarah Dean Jamie Morgenstern 75 34 0 25 May 2022
AgFlow: Fast Model Selection of Penalized PCA via Implicit Regularization Effects of Gradient Flow Haiyan Jiang Haoyi Xiong Dongrui Wu Ji Liu Dejing Dou 18 1 0 07 Oct 2021
A Practical Method for Constructing Equivariant Multilayer Perceptrons for Arbitrary Matrix Groups Marc Finzi Max Welling A. Wilson 79 185 0 19 Apr 2021
SGD for Structured Nonconvex Functions: Learning Rates, Minibatching and Interpolation Robert Mansel Gower Othmane Sebbouh Nicolas Loizou 25 74 0 18 Jun 2020
Diffusion Approximations for Online Principal Component Estimation and Global Convergence C. J. Li Mengdi Wang Han Liu Tong Zhang 34 12 0 29 Aug 2018
Streaming PCA and Subspace Tracking: The Missing Data Case Laura Balzano Yuejie Chi Yue M. Lu 13 84 0 12 Jun 2018
Taming Convergence for Asynchronous Stochastic Gradient Descent with Unbounded Delay in Non-Convex Learning Xin Zhang Jia-Wei Liu Zhengyuan Zhu 16 17 0 24 May 2018
History PCA: A New Algorithm for Streaming PCA Puyudi Yang Cho-Jui Hsieh Jane-ling Wang AI4TS 20 23 0 15 Feb 2018
Accelerated Stochastic Power Iteration Christopher De Sa Bryan D. He Ioannis Mitliagkas Christopher Ré Peng Xu 35 89 0 10 Jul 2017
A Nonconvex Splitting Method for Symmetric Nonnegative Matrix Factorization: Convergence Analysis and Optimality Songtao Lu Mingyi Hong Zhengdao Wang 24 47 0 24 Mar 2017
Learning an Invariant Hilbert Space for Domain Adaptation Samitha Herath Mehrtash Harandi Fatih Porikli 16 107 0 25 Nov 2016
Non-square matrix sensing without spurious local minima via the Burer-Monteiro approach Dohyung Park Anastasios Kyrillidis C. Caramanis Sujay Sanghavi 23 179 0 12 Sep 2016
Parallel SGD: When does averaging help? Jian Zhang Christopher De Sa Ioannis Mitliagkas Christopher Ré MoMe FedML 54 109 0 23 Jun 2016
Efficient Estimation of Partially Linear Models for Spatial Data over Complex Domain Elad Hazan Chi Jin Cameron Musco Praneeth Netrapalli 11 78 0 27 May 2016
Provable Efficient Online Matrix Completion via Non-convex Stochastic Gradient Descent Chi Jin Sham Kakade Praneeth Netrapalli 19 81 0 26 May 2016
Matrix Completion has No Spurious Local Minimum Rong Ge J. Lee Tengyu Ma 25 596 0 24 May 2016
Global Optimality of Local Search for Low Rank Matrix Recovery Srinadh Bhojanapalli Behnam Neyshabur Nathan Srebro ODL 36 386 0 23 May 2016
Trading-off variance and complexity in stochastic gradient descent Vatsal Shah Megasthenis Asteris Anastasios Kyrillidis Sujay Sanghavi 25 13 0 22 Mar 2016
Median-Truncated Nonconvex Approach for Phase Retrieval with Outliers Huishuai Zhang Yuejie Chi Yingbin Liang 22 55 0 11 Mar 2016
Streaming PCA: Matching Matrix Bernstein and Near-Optimal Finite Sample Guarantees for Oja's Algorithm Prateek Jain Chi Jin Sham Kakade Praneeth Netrapalli Aaron Sidford 28 128 0 22 Feb 2016
Robust Shift-and-Invert Preconditioning: Faster and More Sample Efficient Algorithms for Eigenvector Computation Chi Jin Sham Kakade Cameron Musco Praneeth Netrapalli Aaron Sidford 19 42 0 29 Oct 2015
Convergence of Stochastic Gradient Descent for PCA Ohad Shamir 19 85 0 30 Sep 2015
Dropping Convexity for Faster Semi-definite Optimization Srinadh Bhojanapalli Anastasios Kyrillidis Sujay Sanghavi 27 172 0 14 Sep 2015
A Riemannian low-rank method for optimization over semidefinite matrices with block-diagonal constraints Nicolas Boumal 21 67 0 01 Jun 2015
Guaranteed Matrix Completion via Non-convex Factorization Ruoyu Sun Zhi-Quan Luo 40 450 0 28 Nov 2014