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Oja's algorithm has been the cornerstone of streaming methods in Principal Component Analysis (PCA) since it was first proposed in 1982.
Simplified neuron model as a principal component analyzer
Erkki Oja · 1982
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Global convergence of oja’s pca learning algorithm with a non-zero-approaching adaptive learning rate
Jian Cheng Lv, Zhang Yi, and K.K. Tan · 2006
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Learning multiple layers of features from tiny images
Alex Krizhevsky · 2009
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Adaptive bound optimization for online convex optimization
H. Brendan McMahan and Matthew J. Streeter · 2010
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Adaptive subgradient methods for online learning and stochastic optimization
John Duchi, Elad Hazan, and Yoram Singer · 2011
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Lecture 6a overview of mini-batch gradient descent”
G. Hinton, N. Srivastava, and K. Swersky · 2012
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Memory Limited, Streaming PCA
I. Mitliagkas, C. Caramanis, and P. Jain · 2013
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Minimax sparse principal subspace estimation in high dimensions
Vincent Q. Vu and Jing Lei · 2013
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The noisy power method: A meta algorithm with applications
Moritz Hardt and Eric Price · 2014
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Adam: A method for stochastic optimization
Diederik P. Kingma and Jimmy Ba · 2014
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A stochastic pca and svd algorithm with an exponential convergence rate
Ohad Shamir · 2015
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First Efficient Convergence for Streaming k-PCA: a Global, Gap-Free, and Near-Optimal Rate
Z. Allen-Zhu and Y. Li · 2016
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An Improved Gap-Dependency Analysis of the Noisy Power Method
Maria Florina Balcan, Simon S. Du, Yining Wang, and Adams Wei Yu · 2016
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Prateek Jain, Chi Jin, Sham M. Kakade, Praneeth Netrapalli, and Aaron Sidford · 2016
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Near-Optimal Stochastic Approximation for Online Principal Component Estimation
Chris Junchi Li, Mengdi Wang, Han Liu, and Tong Zhang · 2016
Online principal component analysis in high dimension: Which algorithm to choose?
Hervé Cardot and David Degras · 2018
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Dimensionality reduction for stationary time series via stochastic nonconvex optimization
Minshuo Chen, Lin Yang, Mengdi Wang, and Tuo Zhao · 2018
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Average performance analysis of the stochastic gradient method for online PCA
Stephane Chretien, Christophe Guyeux, and Zhen-Wai Olivier HO · 2018
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Near-optimal stochastic approximation for online principal component estimation
Chris Junchi Li, Mengdi Wang, Han Liu, and Tong Zhang · 2018
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Streaming principal component analysis in noisy setting
Teodor Vanislavov Marinov, Poorya Mianjy, and Raman Arora · 2018
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Image alignment by online robust pca via stochastic gradient descent
W. Song, J. Zhu, Y. Li, and C. Chen · 2016
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Accelerated Stochastic Power Iteration
Christopher De Sa, Bryan He, Ioannis Mitliagkas, Christopher Ré, and Peng Xu · 2017
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UCI machine learning repository, 2017
Dheeru Dua and Efi Karra Taniskidou · 2017
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An Acceleration Scheme for Memory Limited, Streaming PCA
Salaheddin Alakkari and John Dingliana · 2018
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Streaming pca and subspace tracking: The missing data case
L. Balzano, Y. Chi, and Y. M. Lu · 2018
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AdaGrad stepsizes: Sharp convergence over nonconvex landscapes, from any initialization
Rachel Ward, Xiaoxia Wu, and Leon Bottou · 2018
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Accelerated stochastic power iteration
Peng Xu, Bryan He, Christopher De Sa, Ioannis Mitliagkas, and Chris Re · 2018
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History PCA: A New Algorithm for Streaming PCA
P. Yang, C.-J. Hsieh, and J.-L. Wang · 2018
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On the convergence of adagrad with momentum for training deep neural networks
Fangyu Zou and Li Shen · 2018
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