Efficient Computation of Robust Weighted Low-Rank Matrix Approximations Using the L_1 Norm

No abstract is available for this paper.

• Publication year

  2012

• Venue

  IEEE Transactions on Pattern Analysis and Machine Intelligence

• Publication date

  2012-09-01

• Fields of study

  Medicine, Computer Science, Mathematics

• Identifiers
  DOI 10.1109/TPAMI.2012.116PMID 22641698
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar, PubMed

• No claims are published for this paper.

• No concepts are published for this paper.

• Efficient computation of robust low-rank matrix approximations in the presence of missing data using the L1 norm

  2010cited by this paper
• Robust principal component analysis?

  2009cited by this paper
• Globally optimal bilinear programming for computer vision applications

  2008cited by this paper
• On the Wiberg Algorithm for Matrix Factorization in the Presence of Missing Components

  2007cited by this paper
• Robust L/sub 1/ norm factorization in the presence of outliers and missing data by alternative convex programming

  2005influential reference
• Damped Newton algorithms for matrix factorization with missing data

  2005influential reference
• A Framework for Robust Subspace Learning

  2003cited by this paper
• Learning Non-Rigid 3D Shape from 2D Motion

  2003cited by this paper
• Robust Factorization

  2002cited by this paper
• A subspace approach to layer extraction

  2001cited by this paper
• MASSACHUSETTS INSTITUTE OF TECHNOLOGY ARTIFICIAL INTELLIGENCE LABORATORY and CENTER FOR BIOLOGICAL AND COMPUTATIONAL LEARNING DEPARTMENT OF BRAIN AND COGNITIVE SCIENCES A.I. Memo No.XXXX C.B.C.L Paper No.XXX An Empirical Comparison of SNoW and SVMs For Face Detection

  2001cited by this paper
• Practical Methods of Optimization: Fletcher/Practical Methods of Optimization

  2000cited by this paper
• Robust Factorization of a Data Matrix

  1998cited by this paper
• Numerical Methods for Least Squares Problems

  1996cited by this paper
• EigenTracking: Robust Matching and Tracking of Articulated Objects Using a View-Based Representation

  1996cited by this paper
• Principal Component Analysis with Missing Data and Its Application to Polyhedral Object Modeling

  1995cited by this paper
• Photometric stereo under a light source with arbitrary motion

  1994cited by this paper
• Shape and motion from image streams under orthography: a factorization method

  1992cited by this paper
• Eigenfaces for Recognition

  1991cited by this paper
• Neural networks and principal component analysis: Learning from examples without local minima

  1989cited by this paper
• On the superlinear convergence of a trust region algorithm for nonsmooth optimization

  1985cited by this paper
• Some Properties of Trust Region Algorithms for Nonsmooth Optimization

  1983influential reference
• A model algorithm for composite nondifferentiable optimization problems

  1982cited by this paper
• Simplified neuron model as a principal component analyzer

  1982cited by this paper
• Approximation theory and numerical methods

  1980cited by this paper
• Noname manuscript No. (will be inserted by the editor) Generalized Convexity in Multiple View Geometry

  year unknowncited by this paper

• A Saddle Point Remedy: Power of Variable Elimination in Non-convex Optimization

  2025cites this paper
• When Can We Solve the Weighted Low Rank Approximation Problem in Truly Subquadratic Time?

  2025cites this paper
• Comparative study of Japanese nationwide epidemiological studies of myasthenia gravis using datasets of 2006 and 2018

  2025cites this paper
• Adaptive decoupled strategy for robust and efficient low-rank matrix decomposition

  2025cites this paper
• Efficient low rank matrix recovery with flexible group sparse regularization

  2024cites this paper
• Robust Variable Projection Algorithm for the Identification of Separable Nonlinear Models

  2024cites this paper
• Nonmonotone variable projection algorithms for matrix decomposition with missing data

  2023cites this paper
• A generalized inertial proximal alternating linearized minimization method for nonconvex nonsmooth problems

  2023cites this paper
• Matrix Factorization Techniques in Machine Learning, Signal Processing, and Statistics

  2023cites this paper
• A Linearly Convergent Algorithm for Rotationally Invariant $\ell_1$-Norm Principal Component Analysis

  2022cites this paper
• Denoising image by matrix factorization in U-shaped convolutional neural network

  2022cites this paper
• Sensor node calibration in presence of a dominant reflective plane

  2022cites this paper
• A Non-local Low-rank and Sparsity based Framework for Depth Map Inpainting

  2021cites this paper
• Multilabel Takagi-Sugeno-Kang Fuzzy System

  2021cites this paper
• Detail preserving image denoising with patch-based structure similarity via sparse representation and SVD

  2021cites this paper
• Computer Vision without Vision: Methods and Applications of Radio and Audio Based SLAM

  2020cites this paper
• Supplementary Material: Bilinear Parameterization For Differentiable Rank-Regularization

  2020cites this paper
• Feature Extraction

  2020cites this paper
• Exploiting Low Rank Prior for Depth Map Completion

  2020cites this paper
• Robust Matrix Completion via ℓP-Greedy Pursuits

  2020cites this paper
• “An Analysis of Sketched IRLS for Accelerated Sparse Residual Regression,” ECCV 2020

  2020cites this paper
• Cyclic Weighted Median Method for L1 Low-Rank with Nonlocal for Single color image denoising

  2020cites this paper
• Spectral Clustering-based Matrix Completion Method for Top-n Recommendation

  2019cites this paper
• An adaptive boosting procedure for low-rank based image denoising

  2019cites this paper
• Matrix Completion

  2019cites this paper
• Brief review of image denoising techniques

  2019cites this paper
• Robust Matrix Factorization by Majorization Minimization

  2018influential citation
• Financial Big Data Solutions for State Space Panel Regression in Interest Rate Dynamics

  2018cites this paper
• Structure preserving image denoising based on low-rank reconstruction and gradient histograms

  2018cites this paper
• Robust Low-Rank Approximation of Matrices in lp-Space

  2018cites this paper
• Structured Kernel Subspace Learning for Autonomous Robot Navigation †

  2018cites this paper
• Computational Methods for Computer Vision: Minimal Solvers and Convex Relaxations

  2018influential citation
• Non-Negative Sparse Regression and Column Subset Selection with L1 Error

  2018cites this paper
• Bilinear Parameterization For Differentiable Rank-Regularization

  2018cites this paper
• Compact Matrix Factorization with Dependent Subspaces

  2017cites this paper
• Factorization for projective and metric reconstruction via truncated nuclear norm

  2017cites this paper
• SVM ENSEMBLE CREATION

  2017cites this paper
• Technical review : performance of existing imputation methods for missing data in SVM ensemble creation

  2017cites this paper
• Weighted Singular Value Thresholding and its Application to Background Estimation

  2017cites this paper
• Robust time-of-arrival self calibration with missing data and outliers

  2016cites this paper
• Robust deformable shape reconstruction from monocular video with manifold forests

  2016cites this paper
• General, Nested, and Constrained Wiberg Minimization

  2016influential citation
• Robust Elastic-Net Subspace Representation

  2016cites this paper
• Recovery guarantee of weighted low-rank approximation via alternating minimization

  2016cites this paper
• Greedy Learning of Generalized Low-Rank Models

  2016influential citation
• Computationally Efficient Truncated Nuclear Norm Minimization for High Dynamic Range Imaging

  2016cites this paper
• Convex Low Rank Approximation

  2016cites this paper
• Learning of Generalized Low-Rank Models: A Greedy Approach

  2016influential citation
• Minimizing the Maximal Rank

  2016cites this paper
• Robust Elastic-Net Subspace Representation.

  2016cites this paper
• Weighted Low-Rank Approximation of Matrices:Some Analytical and Numerical Aspects

  2016cites this paper
• Efficient $l_{1}$ -Norm-Based Low-Rank Matrix Approximations for Large-Scale Problems Using Alternating Rectified Gradient Method

  2015cites this paper
• Robust orthogonal matrix factorization for efficient subspace learning

  2015cites this paper
• A Simple Method for Subspace Estimation with Corrupted Columns

  2015cites this paper
• An Effective Missing-Data Estimation Approach for Small-Size Image Sequences

  2015cites this paper
• Relaxed Majorization-Minimization for Non-Smooth and Non-Convex Optimization

  2015cites this paper
• Partial Sum Minimization of Singular Values in Robust PCA: Algorithm and Applications

  2015influential citation
• Elastic-net regularization of singular values for robust subspace learning

  2015cites this paper
• Fast Randomized Singular Value Thresholding for Low-Rank Optimization

  2015cites this paper
• Convex Envelopes for Low Rank Approximation

  2015cites this paper
• Fast randomized Singular Value Thresholding for Nuclear Norm Minimization

  2015cites this paper
• On the minimal problems of low-rank matrix factorization

  2015cites this paper
• Bayesian Robust Tensor Factorization for Incomplete Multiway Data

  2014cites this paper
• A Combinatorial Approach to L1\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$L_1$$\end{document}-Matrix Factorization

  2014cites this paper
• A Random Algorithm for Low-Rank Decomposition of Large-Scale Matrices With Missing Entries

  2014cites this paper
• Deformable Shape Reconstruction from Monocular Video with Manifold Forests

  2013cites this paper
• A Cyclic Weighted Median Method for L1 Low-Rank Matrix Factorization with Missing Entries

  2013cites this paper