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Convergence of Stochastic Gradient Descent for PCA

Convergence of Stochastic Gradient Descent for PCA

30 September 2015
Ohad Shamir
ArXivPDFHTML

Papers citing "Convergence of Stochastic Gradient Descent for PCA"

45 / 45 papers shown
Title
Global Convergence of Adaptive Sensing for Principal Eigenvector Estimation
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
Black-Box kkk-to-111-PCA Reductions: Theory and Applications
A. Jambulapati
Syamantak Kumar
Jerry Li
Shourya Pandey
Ankit Pensia
Kevin Tian
39
2
0
06 Mar 2024
ADS: Approximate Densest Subgraph for Novel Image Discovery
ADS: Approximate Densest Subgraph for Novel Image Discovery
Shanfeng Hu
11
0
0
13 Feb 2024
The Effect of SGD Batch Size on Autoencoder Learning: Sparsity,
  Sharpness, and Feature Learning
The Effect of SGD Batch Size on Autoencoder Learning: Sparsity, Sharpness, and Feature Learning
Nikhil Ghosh
Spencer Frei
Wooseok Ha
Ting Yu
MLT
32
3
0
06 Aug 2023
Fast Detection of Burst Jamming for Delay-Sensitive Internet-of-Things
  Applications
Fast Detection of Burst Jamming for Delay-Sensitive Internet-of-Things Applications
Shao-Di Wang
Hui-Ming Wang
Peng Liu
11
1
0
02 Dec 2022
Universal Adversarial Directions
Universal Adversarial Directions
Ching Lam Choi
Farzan Farnia
AAML
9
0
0
28 Oct 2022
High-dimensional limit theorems for SGD: Effective dynamics and critical
  scaling
High-dimensional limit theorems for SGD: Effective dynamics and critical scaling
Gerard Ben Arous
Reza Gheissari
Aukosh Jagannath
62
58
0
08 Jun 2022
Nonconvex Stochastic Scaled-Gradient Descent and Generalized Eigenvector
  Problems
Nonconvex Stochastic Scaled-Gradient Descent and Generalized Eigenvector Problems
C. J. Li
Michael I. Jordan
23
2
0
29 Dec 2021
Bootstrapping the error of Oja's algorithm
Bootstrapping the error of Oja's algorithm
Robert Lunde
Purnamrita Sarkar
Rachel A. Ward
23
10
0
28 Jun 2021
On the Optimality of the Oja's Algorithm for Online PCA
On the Optimality of the Oja's Algorithm for Online PCA
Xin Liang
11
9
0
31 Mar 2021
FedPower: Privacy-Preserving Distributed Eigenspace Estimation
FedPower: Privacy-Preserving Distributed Eigenspace Estimation
Xiaoxun Guo
Xiang Li
Xiangyu Chang
Shusen Wang
Zhihua Zhang
FedML
24
3
0
01 Mar 2021
Streaming k-PCA: Efficient guarantees for Oja's algorithm, beyond
  rank-one updates
Streaming k-PCA: Efficient guarantees for Oja's algorithm, beyond rank-one updates
De Huang
Jonathan Niles-Weed
Rachel A. Ward
17
19
0
06 Feb 2021
EigenGame: PCA as a Nash Equilibrium
EigenGame: PCA as a Nash Equilibrium
I. Gemp
Brian McWilliams
Claire Vernade
T. Graepel
24
46
0
01 Oct 2020
A General Framework for Analyzing Stochastic Dynamics in Learning
  Algorithms
A General Framework for Analyzing Stochastic Dynamics in Learning Algorithms
Chi-Ning Chou
Juspreet Singh Sandhu
Mien Brabeeba Wang
Tiancheng Yu
11
4
0
11 Jun 2020
Scaling-up Distributed Processing of Data Streams for Machine Learning
Scaling-up Distributed Processing of Data Streams for Machine Learning
M. Nokleby
Haroon Raja
W. Bajwa
8
15
0
18 May 2020
Randomized spectral co-clustering for large-scale directed networks
Randomized spectral co-clustering for large-scale directed networks
Xiao Guo
Yixuan Qiu
Hai Zhang
Xiangyu Chang
21
14
0
25 Apr 2020
Communication-Efficient Distributed SVD via Local Power Iterations
Communication-Efficient Distributed SVD via Local Power Iterations
Xiang Li
Shusen Wang
Kun Chen
Zhihua Zhang
35
21
0
19 Feb 2020
ROIPCA: An online memory-restricted PCA algorithm based on rank-one
  updates
ROIPCA: An online memory-restricted PCA algorithm based on rank-one updates
Roy Mitz
Y. Shkolnisky
17
0
0
25 Nov 2019
ODE-Inspired Analysis for the Biological Version of Oja's Rule in
  Solving Streaming PCA
ODE-Inspired Analysis for the Biological Version of Oja's Rule in Solving Streaming PCA
Chi-Ning Chou
Mien Brabeeba Wang
11
7
0
04 Nov 2019
Exponentially convergent stochastic k-PCA without variance reduction
Exponentially convergent stochastic k-PCA without variance reduction
Cheng Tang
12
28
0
03 Apr 2019
Robust Streaming PCA
Robust Streaming PCA
D. Bienstock
Minchan Jeong
Apurv Shukla
Se-Young Yun
12
3
0
08 Feb 2019
Physical-Layer Supervised Learning Assisted by an Entangled Sensor
  Network
Physical-Layer Supervised Learning Assisted by an Entangled Sensor Network
Quntao Zhuang
Zheshen Zhang
10
96
0
28 Jan 2019
Incremental Principal Component Analysis Exact implementation and
  continuity corrections
Incremental Principal Component Analysis Exact implementation and continuity corrections
Vittorio Lippi
G. Ceccarelli
CLL
6
8
0
23 Jan 2019
Gen-Oja: A Two-time-scale approach for Streaming CCA
Gen-Oja: A Two-time-scale approach for Streaming CCA
Kush S. Bhatia
Aldo Pacchiano
Nicolas Flammarion
Peter L. Bartlett
Michael I. Jordan
8
2
0
20 Nov 2018
On the Regret Minimization of Nonconvex Online Gradient Ascent for
  Online PCA
On the Regret Minimization of Nonconvex Online Gradient Ascent for Online PCA
Dan Garber
ODL
14
8
0
27 Sep 2018
Compositional Stochastic Average Gradient for Machine Learning and
  Related Applications
Compositional Stochastic Average Gradient for Machine Learning and Related Applications
Tsung-Yu Hsieh
Y. El-Manzalawy
Yiwei Sun
Vasant Honavar
18
1
0
04 Sep 2018
Diffusion Approximations for Online Principal Component Estimation and
  Global Convergence
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
Streaming PCA and Subspace Tracking: The Missing Data Case
Laura Balzano
Yuejie Chi
Yue M. Lu
13
84
0
12 Jun 2018
Subspace Estimation from Incomplete Observations: A High-Dimensional
  Analysis
Subspace Estimation from Incomplete Observations: A High-Dimensional Analysis
Chuang Wang
Yonina C. Eldar
Yue M. Lu
29
17
0
17 May 2018
Average performance analysis of the stochastic gradient method for
  online PCA
Average performance analysis of the stochastic gradient method for online PCA
Stéphane Chrétien
C. Guyeux
Z. Ho
9
5
0
03 Apr 2018
Averaging Stochastic Gradient Descent on Riemannian Manifolds
Averaging Stochastic Gradient Descent on Riemannian Manifolds
Nilesh Tripuraneni
Nicolas Flammarion
Francis R. Bach
Michael I. Jordan
38
99
0
26 Feb 2018
Smooth Sensitivity Based Approach for Differentially Private Principal
  Component Analysis
Smooth Sensitivity Based Approach for Differentially Private Principal Component Analysis
Ran Gilad-Bachrach
Alon Gonen
28
10
0
29 Oct 2017
Accelerated Stochastic Power Iteration
Accelerated Stochastic Power Iteration
Christopher De Sa
Bryan D. He
Ioannis Mitliagkas
Christopher Ré
Peng Xu
35
89
0
10 Jul 2017
Communication-efficient Algorithms for Distributed Stochastic Principal
  Component Analysis
Communication-efficient Algorithms for Distributed Stochastic Principal Component Analysis
Dan Garber
Ohad Shamir
Nathan Srebro
6
42
0
27 Feb 2017
Follow the Compressed Leader: Faster Online Learning of Eigenvectors and
  Faster MMWU
Follow the Compressed Leader: Faster Online Learning of Eigenvectors and Faster MMWU
Zeyuan Allen-Zhu
Yuanzhi Li
22
44
0
06 Jan 2017
Lock-Free Optimization for Non-Convex Problems
Lock-Free Optimization for Non-Convex Problems
Shen-Yi Zhao
Gong-Duo Zhang
Wu-Jun Li
19
5
0
11 Dec 2016
Optimal Binary Autoencoding with Pairwise Correlations
Optimal Binary Autoencoding with Pairwise Correlations
Akshay Balsubramani
SSL
20
1
0
07 Nov 2016
First Efficient Convergence for Streaming k-PCA: a Global, Gap-Free, and
  Near-Optimal Rate
First Efficient Convergence for Streaming k-PCA: a Global, Gap-Free, and Near-Optimal Rate
Zeyuan Allen-Zhu
Yuanzhi Li
38
99
0
26 Jul 2016
Efficient Estimation of Partially Linear Models for Spatial Data over
  Complex Domain
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
Near-Optimal Stochastic Approximation for Online Principal Component
  Estimation
Near-Optimal Stochastic Approximation for Online Principal Component Estimation
C. J. Li
Mengdi Wang
Han Liu
Tong Zhang
18
66
0
16 Mar 2016
An Improved Gap-Dependency Analysis of the Noisy Power Method
An Improved Gap-Dependency Analysis of the Noisy Power Method
Maria-Florina Balcan
S. Du
Yining Wang
Adams Wei Yu
32
72
0
23 Feb 2016
Streaming PCA: Matching Matrix Bernstein and Near-Optimal Finite Sample
  Guarantees for Oja's Algorithm
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
31
128
0
22 Feb 2016
Robust Shift-and-Invert Preconditioning: Faster and More Sample
  Efficient Algorithms for Eigenvector Computation
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
Rivalry of Two Families of Algorithms for Memory-Restricted Streaming
  PCA
Rivalry of Two Families of Algorithms for Memory-Restricted Streaming PCA
Chun-Liang Li
Hsuan-Tien Lin
Chi-Jen Lu
23
29
0
04 Jun 2015
Stochastic Gradient Descent for Non-smooth Optimization: Convergence
  Results and Optimal Averaging Schemes
Stochastic Gradient Descent for Non-smooth Optimization: Convergence Results and Optimal Averaging Schemes
Ohad Shamir
Tong Zhang
104
571
0
08 Dec 2012
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