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Archaeology International
Architecture_MPS
Europe and the World: A law review
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International Journal of Development Education and Global Learning
International Journal of Social Pedagogy
Jewish Historical Studies: A Journal of English-Speaking Jewry
Journal of Bentham Studies
London Review of Education
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Research for All
The Journal of the Sylvia Townsend Warner Society
The London Journal of Canadian Studies
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Handbook of Robust Low-Rank and Sparse Matrix Decomposition
Unifying Nuclear Norm and Bilinear Factorization Methods
edited-book
Publication date
(Online):
June 16 2016
Publisher:
CRC Press
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Improved approximation algorithms for maximum cut and satisfiability problems using semidefinite programming
Michel X. Goemans
,
David P. Williamson
(1995)
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What is the best multi-stage architecture for object recognition?
Kevin Jarrett
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Koray Kavukcuoglu
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Marc' Aurelio Ranzato
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(2009)
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Neural networks and principal component analysis: Learning from examples without local minima
Pierre Baldi
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Kurt Hornik
(1989)
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Book Chapter
Publication date (Print):
July 31 2016
Publication date (Online):
June 16 2016
Pages
: 6-1-6-33
DOI:
10.1201/b20190-7
SO-VID:
d31e1d2a-6ed6-4b6c-ad4e-3d5dca9540f4
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Book chapters
pp. 10-1
Online (Recursive) Robust Principal Components Analysis
pp. 1-1
Robust Principal Component Analysis
pp. 11-1
Incremental Methods for Robust Local Subspace Estimation
pp. 12-1
Robust Orthonormal Subspace Learning (ROSL) for Efficient Low-Rank Recovery
pp. 13-1
A Unified View of Nonconvex Heuristic Approach for Low-Rank and Sparse Structure Learning
pp. 14-1
A Variational Approach for Sparse Component Estimation and Low-Rank Matrix Recovery
pp. 15-1
Recovering Low-Rank and Sparse Matrices with Missing and Grossly Corrupted Observations
pp. 16-1
Applications of Low-Rank and Sparse Matrix Decompositions in Hyperspectral Video Processing
pp. 17-1
Low-Rank plus Sparse Spatiotemporal MRI: Acceleration, Background Suppression, and Motion Learning
pp. 18-1
LRSLibrary: Low-Rank and Sparse Tools for Background Modeling and Subtraction in Videos
pp. 19-1
Dynamic Mode Decomposition for Robust PCA with Applications to Foreground/Background Subtraction in Video Streams and Multi-Resolution Analysis
pp. 20-1
Stochastic RPCA for Background/Foreground Separation
pp. 2-1
Algorithms for Stable PCA
pp. 21-1
Bayesian Sparse Estimation for Background/Foreground Separation
pp. 3-1
Dual Smoothing and Value Function Techniques for Variational Matrix Decomposition
pp. 4-1
Robust Principal Component Analysis Based on Low-Rank and Block-Sparse Matrix Decomposition
pp. 5-1
Robust PCA by Controlling Sparsity in Model Residuals
pp. 6-1
Unifying Nuclear Norm and Bilinear Factorization Methods
pp. 7-1
Robust Non-Negative Matrix Factorization under Separability Assumption
pp. 8-1
Robust Matrix Completion through Nonconvex Approaches and Efficient Algorithms
pp. 9-1
Factorized Robust Matrix Completion
pp. 425
Applications in Background/Foreground Separation for Video Surveillance
pp. 426
LRSLibrary: Low-Rank and Sparse Tools for Background Modeling and Subtraction in Videos
pp. 441
Dynamic Mode Decomposition for Robust PCA with Applications to Foreground/Background Subtraction in Video Streams and Multi-Resolution Analysis
pp. 457
Stochastic RPCA for Background/Foreground Separation
pp. 481
Bayesian Sparse Estimation for Background/Foreground Separation
pp. 499
Index
pp. 501
Color Insert
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