Streaming PCA: Matching Matrix Bernstein and Near-Optimal Finite Sample Guarantees for Oja's Algorithm

22 February 2016

Papers citing "Streaming PCA: Matching Matrix Bernstein and Near-Optimal Finite Sample Guarantees for Oja's Algorithm"

27 / 27 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
The Edge of Orthogonality: A Simple View of What Makes BYOL Tick Pierre Harvey Richemond Allison C. Tam Yunhao Tang Florian Strub Bilal Piot Felix Hill SSL 31 9 0 09 Feb 2023
Preference Dynamics Under Personalized Recommendations Sarah Dean Jamie Morgenstern 75 34 0 25 May 2022
Nonconvex Stochastic Scaled-Gradient Descent and Generalized Eigenvector Problems C. J. Li Michael I. Jordan 23 2 0 29 Dec 2021
EigenGame: PCA as a Nash Equilibrium I. Gemp Brian McWilliams Claire Vernade T. Graepel 24 46 0 01 Oct 2020
An Implicit Form of Krasulina's k-PCA Update without the Orthonormality Constraint Ehsan Amid Manfred K. Warmuth 15 11 0 11 Sep 2019
PowerSGD: Practical Low-Rank Gradient Compression for Distributed Optimization Thijs Vogels Sai Praneeth Karimireddy Martin Jaggi 19 317 0 31 May 2019
Winner-Take-All Computation in Spiking Neural Networks Nancy A. Lynch Cameron Musco M. Parter 17 23 0 25 Apr 2019
Stochastic Linear Bandits with Hidden Low Rank Structure Sahin Lale Kamyar Azizzadenesheli Anima Anandkumar B. Hassibi 15 28 0 28 Jan 2019
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
SPIDER: Near-Optimal Non-Convex Optimization via Stochastic Path Integrated Differential Estimator Cong Fang C. J. Li Zhouchen Lin Tong Zhang 50 570 0 04 Jul 2018
Streaming PCA and Subspace Tracking: The Missing Data Case Laura Balzano Yuejie Chi Yue M. Lu 13 84 0 12 Jun 2018
Eigenvector Computation and Community Detection in Asynchronous Gossip Models Frederik Mallmann-Trenn Cameron Musco Christopher Musco 21 9 0 23 Apr 2018
Averaging Stochastic Gradient Descent on Riemannian Manifolds Nilesh Tripuraneni Nicolas Flammarion Francis R. Bach Michael I. Jordan 38 99 0 26 Feb 2018
History PCA: A New Algorithm for Streaming PCA Puyudi Yang Cho-Jui Hsieh Jane-ling Wang AI4TS 20 23 0 15 Feb 2018
Katyusha X: Practical Momentum Method for Stochastic Sum-of-Nonconvex Optimization Zeyuan Allen-Zhu ODL 44 52 0 12 Feb 2018
Accelerated Stochastic Power Iteration Christopher De Sa Bryan D. He Ioannis Mitliagkas Christopher Ré Peng Xu 35 89 0 10 Jul 2017
Learning Mixture of Gaussians with Streaming Data Aditi Raghunathan Ravishankar Krishnaswamy Prateek Jain 36 8 0 08 Jul 2017
Fixed-Rank Approximation of a Positive-Semidefinite Matrix from Streaming Data J. Tropp A. Yurtsever Madeleine Udell V. Cevher 23 80 0 18 Jun 2017
Average whenever you meet: Opportunistic protocols for community detection L. Becchetti A. Clementi Pasin Manurangsi Emanuele Natale F. Pasquale P. Raghavendra Luca Trevisan 16 2 0 15 Mar 2017
PCA in Data-Dependent Noise (Correlated-PCA): Nearly Optimal Finite Sample Guarantees Namrata Vaswani Praneeth Narayanamurthy 39 2 0 10 Feb 2017
Follow the Compressed Leader: Faster Online Learning of Eigenvectors and Faster MMWU Zeyuan Allen-Zhu Yuanzhi Li 22 44 0 06 Jan 2017
Parallelizing Stochastic Gradient Descent for Least Squares Regression: mini-batching, averaging, and model misspecification Prateek Jain Sham Kakade Rahul Kidambi Praneeth Netrapalli Aaron Sidford MoMe 21 36 0 12 Oct 2016
Practical sketching algorithms for low-rank matrix approximation J. Tropp A. Yurtsever Madeleine Udell V. Cevher 22 201 0 31 Aug 2016
LazySVD: Even Faster SVD Decomposition Yet Without Agonizing Pain Zeyuan Allen-Zhu Yuanzhi Li 30 128 0 12 Jul 2016
Provable Efficient Online Matrix Completion via Non-convex Stochastic Gradient Descent Chi Jin Sham Kakade Praneeth Netrapalli 19 81 0 26 May 2016