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Imputing Missing Entries of a Data Matrix: A Review
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Partial Least Squares
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Multiple Imputation for Nonresponse in Surveys
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Practical Methods of Optimization
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Molecular conformations from distance matrices
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Multiple imputation for missing data†‡
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Information enhancement for data mining
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Incremental Singular Value Decomposition of Uncertain Data with Missing Values
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The Elements of Statistical Learning
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Practical Optimization: Algorithms and Engineering Applications
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Estimation of Rank Deficient Matrices from Partial Observations: Two-Step Iterative Algorithms
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Principal Component Analysis for Large Scale Problems with Lots of Missing Values
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Missing Value Imputation Based on Data Clustering
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Algorithms and Literate Programs for Weighted Low-Rank Approximation with Missing Data
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Efficient Model Selection for Large-Scale Nearest-Neighbor Data Mining
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Shape and motion from image streams under orthography: a factorization method
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Accelerated Gauss-Newton algorithms for nonlinear least squares problems
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A variable projection method for solving separable nonlinear least squares problems
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The Approximation of One Matrix by Another of Lower Rank
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Multidimensional Scaling: I. Theory and Method
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Some Simple Procedures for Handling Missing Data in Multivariate Analysis
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Weighted Least Squares Fitting Using Ordinary Least Squares Algorithms
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Analysis of Individual Differences in Multidimensional Scaling Via an N-way Generalization of “Eckart-Young” Decomposition
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Fixed-rank matrix factorizations and Riemannian low-rank optimization
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Fixed point and Bregman iterative methods for matrix rank minimization
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Null space conditions and thresholds for rank minimization
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An implementable proximal point algorithmic framework for nuclear norm minimization
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Trust-Region Methods on Riemannian Manifolds
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Exact Matrix Completion via Convex Optimization
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Semi-parametric optimization for missing data imputation
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Grassmann algorithms for low rank approximation of matrices with missing values
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Low-rank tensor completion by Riemannian optimization
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A hybrid algorithm for solving linear inequalities in a least squares sense
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On the Wiberg Algorithm for Matrix Factorization in the Presence of Missing Components
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Optimization Algorithms on Subspaces: Revisiting Missing Data Problem in Low-Rank Matrix
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Solving a low-rank factorization model for matrix completion by a nonlinear successive over-relaxation algorithm
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Completing missing groundwater observations by interpolation
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Positive definite completions of partial Hermitian matrices
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Connections between the real positive semidefinite and distance matrix completion problems
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The completion problem for M-Matrices and Inverse M-Matrices
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The real positive semidefinite completion problem for series-parallel graphs
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Multidimensional Scaling I
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Constrained Optimization and Lagrange Multiplier Methods
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A minimum norm approach for low-rank approximations of a matrix
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PARAFAC and missing values
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Scalable tensor factorizations for incomplete data
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How many principal components? stopping rules for determining the number of non-trivial axes revisited
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A comparison of algorithms for fitting the PARAFAC model
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Nearest neighbour approach in the least-squares data imputation algorithms
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Review: A gentle introduction to imputation of missing values
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A review of techniques for treating missing data in OM survey research
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A collaborative framework for 3D alignment and classification of heterogeneous subvolumes in cryo-electron tomography
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A simultaneous reconstruction of missing data in DNA microarrays
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The distance between two convex sets
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On extremum properties of orthogonal quotients matrices
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Positive semidefinite matrix completion, universal rigidity and the Strong Arnold Property
inferredcites →https://doi.org/10.1016/j.laa.2017.02.028openalex-snapshot
Low rank tensor recovery via iterative hard thresholding
inferredcites →https://doi.org/10.1016/j.trc.2004.07.006openalex-snapshot
Estimation of missing traffic counts using factor, genetic, neural, and regression techniques
inferredcites →https://doi.org/10.1016/s0024-3795(00)00088-4openalex-snapshot
P-matrix completions under weak symmetry assumptions
inferredcites →https://doi.org/10.1016/s0024-3795(97)83714-7openalex-snapshot
A connection between positive semidefinite and Euclidean distance matrix completion problems
inferredcites →https://doi.org/10.1016/s0024-3795(98)10210-0openalex-snapshot
Maximum rank matrix completion
inferredcites →https://doi.org/10.1016/s0167-9473(03)00138-5openalex-snapshot
Partial least-squares vs. Lanczos bidiagonalization—I: analysis of a projection method for multiple regression
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13 Theory of multidimensional scaling
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Dealing with missing data: Part II
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PLS-regression: a basic tool of chemometrics
inferredcites →https://doi.org/10.1016/s0169-7439(96)00007-xopenalex-snapshot
Missing data methods in PCA and PLS: Score calculations with incomplete observations
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Missing values in principal component analysis
inferredcites →https://doi.org/10.1016/s0933-3657(98)00027-xopenalex-snapshot
Treatment of missing data values in a neural network based decision support system for acute abdominal pain
inferredcites →https://doi.org/10.1023/a:1008655427845openalex-snapshot
Solving Euclidean Distance Matrix Completion Problems Via Semidefinite Programming
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Distance Matrix Completion by Numerical Optimization
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Robust Learning with Missing Data
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Eigentaste: A Constant Time Collaborative Filtering Algorithm
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Effect of missing data on performance of learning algorithms for hydrologic predictions: Implications to an imputation technique
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A Nearest Neighbor Bootstrap For Resampling Hydrologic Time Series
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Comparison of five rules for determining the number of components to retain.
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Analysis of a complex of statistical variables into principal components.
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Distinct types of diffuse large B-cell lymphoma identified by gene expression profiling
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Optimization by Vector Space Methods
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Estimating Missing Values Using Neural Networks
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Acoustic echoes reveal room shape
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Cluster analysis and display of genome-wide expression patterns
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Broad patterns of gene expression revealed by clustering analysis of tumor and normal colon tissues probed by oligonucleotide arrays
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Distinctive gene expression patterns in human mammary epithelial cells and breast cancers
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Singular value decomposition for genome-wide expression data processing and modeling
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Lower Rank Approximation of Matrices by Least Squares With Any Choice of Weights
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Analysis of Incomplete Multivariate Data
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Estimation of Parameters from Incomplete Data
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Multiple Regression with Missing Observations Among the Independent Variables
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Maximum Likelihood Estimates for a Multivariate Normal Distribution when Some Observations are Missing
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The Interpolation of Time Series by Related Series
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Linear Regression Analysis With Missing Observations Among the Independent Variables
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Euclidean distance matrix completion problems
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Augmented Lagrangian alternating direction method for matrix separation based on low-rank factorization
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Separable nonlinear least squares: the variable projection method and its applications
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Tensor completion and low-n-rank tensor recovery via convex optimization
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Iteration Methods for Nonlinear Problems
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Missing value estimation methods for DNA microarrays
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Missing value estimation for DNA microarray gene expression data: local least squares imputation
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Collateral missing value imputation: a new robust missing value estimation algorithm for microarray data
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Evaluation and comparison of gene clustering methods in microarray analysis
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Towards clustering of incomplete microarray data without the use of imputation
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Microarray missing data imputation based on a set theoretic framework and biological knowledge
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LSimpute: accurate estimation of missing values in microarray data with least squares methods
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Principal component analysis with missing data and its application to polyhedral object modeling
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A rank minimization heuristic with application to minimum order system approximation
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Log-det heuristic for matrix rank minimization with applications to Hankel and Euclidean distance matrices
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Online identification and tracking of subspaces from highly incomplete information
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Low-rank optimization for distance matrix completion
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R3MC: A Riemannian three-factor algorithm for low-rank matrix completion
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Linear fitting with missing data: applications to structure-from-motion and to characterizing intensity images
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Damped Newton Algorithms for Matrix Factorization with Missing Data
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An Algorithm for Missing Value Estimation for DNA Microarray Data
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Low-rank matrix completion with geometric performance guarantees
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The use of genetic algorithms and neural networks to approximate missing data in database
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Scalable Collaborative Filtering with Jointly Derived Neighborhood Interpolation Weights
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Using Singular Value Decomposition Approximation for Collaborative Filtering
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Efficient and guaranteed rank minimization by atomic decomposition
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Matrix completion from a few entries
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Tensor Versus Matrix Completion: A Comparison With Application to Spectral Data
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Matrix Factorization Techniques for Recommender Systems
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The Power of Convex Relaxation: Near-Optimal Matrix Completion
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ADMiRA: Atomic Decomposition for Minimum Rank Approximation
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"Missing is useful": missing values in cost-sensitive decision trees
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Recovering the missing components in a large noisy low-rank matrix: application to SFM
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Tensor Completion for Estimating Missing Values in Visual Data
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Pattern Recognition with Partly Missing Data
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The geometry of weighted low-rank approximations
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Subspace Evolution and Transfer (SET) for Low-Rank Matrix Completion
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Calibration Using Matrix Completion With Application to Ultrasound Tomography
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A Review of Hot Deck Imputation for Survey Non‐response
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USING ARTIFICIAL NEURAL NETWORKS TO ESTIMATE MISSING RAINFALL DATA1
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A Method of Estimation of Missing Values in Multivariate Data Suitable for Use with an Electronic Computer
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Missing Data in Regression Analysis
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Maximum Likelihood from Incomplete Data Via the EM Algorithm
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Regression Shrinkage and Selection Via the Lasso
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Processing and modeling genome-wide expression data using singular value decomposition
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Molecular Classification of Cancer: Class Discovery and Class Prediction by Gene Expression Monitoring
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Orthogonalization Via Deflation: A Minimum Norm Approach for Low-Rank Approximations of a Matrix
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Relaxation Methods for Convex Problems
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A Newton–Grassmann Method for Computing the Best Multilinear Rank-$(r_1,$ $r_2,$ $r_3)$ Approximation of a Tensor
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Molecular Embedding via a Second Order Dissimilarity Parameterized Approach
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Guaranteed Minimum-Rank Solutions of Linear Matrix Equations via Nuclear Norm Minimization
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Tensor Decompositions and Applications
inferredcites →https://doi.org/10.1137/080738970openalex-snapshot
A Singular Value Thresholding Algorithm for Matrix Completion
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The Collinearity Problem in Linear Regression. The Partial Least Squares (PLS) Approach to Generalized Inverses
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Interior-Point Method for Nuclear Norm Approximation with Application to System Identification
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Matrix Methods in Data Mining and Pattern Recognition
inferredcites →https://doi.org/10.1137/1.9781611971163openalex-snapshot
The Symmetric Eigenvalue Problem
inferredcites →https://doi.org/10.1137/1.9781611971200openalex-snapshot
Numerical Methods for Unconstrained Optimization and Nonlinear Equations
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Numerical Methods for Least Squares Problems
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Fast online SVD revisions for lightweight recommender systems
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Recovering Low-Rank and Sparse Components of Matrices from Incomplete and Noisy Observations
inferredcites →https://doi.org/10.1137/100811404openalex-snapshot
Low-rank Matrix Recovery via Iteratively Reweighted Least Squares Minimization
inferredcites →https://doi.org/10.1137/1022057openalex-snapshot
Algorithms for Separable Nonlinear Least Squares Problems
inferredcites →https://doi.org/10.1137/110845768openalex-snapshot
Low-Rank Matrix Completion by Riemannian Optimization
inferredcites →https://doi.org/10.1137/120875909openalex-snapshot
Euclidean Distance Geometry and Applications
inferredcites →https://doi.org/10.1137/130905010openalex-snapshot
Robust Low-Rank Tensor Recovery: Models and Algorithms
inferredcites →https://doi.org/10.1137/s0097539704442696openalex-snapshot
Fast Monte Carlo Algorithms for Matrices II: Computing a Low-Rank Approximation to a Matrix
inferredcites →https://doi.org/10.1137/s0097539792240406openalex-snapshot
Sparse Approximate Solutions to Linear Systems
inferredcites →https://doi.org/10.1137/s0895479893249757openalex-snapshot
The Euclidian Distance Matrix Completion Problem
inferredcites →https://doi.org/10.1137/s0895479895290954openalex-snapshot
The Geometry of Algorithms with Orthogonality Constraints
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A collaborative filtering algorithm and evaluation metric that accurately model the user experience
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Fast monte-carlo algorithms for finding low-rank approximations
inferredcites →https://doi.org/10.1145/1102351.1102441openalex-snapshot
Fast maximum margin matrix factorization for collaborative prediction
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Matrix factorization and neighbor based algorithms for the netflix prize problem
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Robust principal component analysis?
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An Algorithmic Framework for Performing Collaborative Filtering
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Collaborative filtering with privacy via factor analysis
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Evaluating collaborative filtering recommender systems
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A Survey of Collaborative Filtering Techniques
inferredcites →https://doi.org/10.1186/1471-2105-7-32openalex-snapshot
Missing value estimation for DNA microarray gene expression data by Support Vector Regression imputation and orthogonal coding scheme
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Robust imputation method for missing values in microarray data
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Which missing value imputation method to use in expression profiles: a comparative study and two selection schemes
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The combinatorially symmetric P-matrix completion problem
inferredcites →https://doi.org/10.1515/9781400830244openalex-snapshot
Optimization Algorithms on Matrix Manifolds
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Application of Dimensionality Reduction in Recommender System - A Case Study
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Imputation of missing values in a precipitation–runoff process database
inferredcites →https://doi.org/10.2307/1909998openalex-snapshot
A Note on a Problem Caused by Assignment of Missing Data in Sample Surveys
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Stopping Rules in Principal Components Analysis: A Comparison of Heuristical and Statistical Approaches
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Statistical Analysis With Missing Data
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Maximum Likelihood Estimation from Incomplete Data
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Parallel Analysis: a method for determining significant principal components
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Empirical Note on the “Number of Factors” Problem in Factor Analysis
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Estimation of Missing Water-Level Data for the Everglades Depth Estimation Network (EDEN)
inferredcites →https://doi.org/10.3141/1879-09openalex-snapshot
Genetically Designed Models for Accurate Imputation of Missing Traffic Counts
inferredcites →https://doi.org/10.4236/alamt.2014.43015openalex-snapshot
Low-Rank Positive Approximants of Symmetric Matrices
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Compressive sensing: a paradigm shift in signal processing
inferredcites →https://doi.org/10.48550/arxiv.0905.1546openalex-snapshot
Fast and Near-Optimal Matrix Completion via Randomized Basis Pursuit
inferredcites →https://doi.org/10.48550/arxiv.0906.2034openalex-snapshot
Regularization methods for learning incomplete matrices
inferredcites →https://doi.org/10.48550/arxiv.0910.0651openalex-snapshot
A Simpler Approach to Matrix Completion
inferredcites →https://doi.org/10.48550/arxiv.1010.0789openalex-snapshot
Estimation of low-rank tensors via convex optimization
inferredcites →https://doi.org/10.48550/arxiv.1212.0467openalex-snapshot
Low-rank Matrix Completion using Alternating Minimization
inferredcites →https://doi.org/10.5120/1537-140openalex-snapshot
Multiple Imputation of Missing Data with Genetic Algorithm based Techniques
inferredcites →https://doi.org/10.5120/2419-3237openalex-snapshot
A Genetic Algorithm Approach for NonIgnorable Missing Data
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What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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GPS Environment Friendliness Estimation with Trajectory Data
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A gradual rank increasing process for matrix completion
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Semi-Supervised Classification of Wafer Map Based on Ladder Network
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Multi-Source Data Integration-Based Urban Road GPS Environment Friendliness Estimation
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A Semi-Supervised and Incremental Modeling Framework for Wafer Map Classification
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A One-Shot Learning Approach for Similarity Retrieval of Wafer Bin Maps With Unknown Failure Pattern
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Identifying Phenogroups in patients with subclinical diastolic dysfunction using unsupervised statistical learning
inferred← citeshttps://doi.org/10.2166/nh.2017.220openalex-snapshot
Imputing missing groundwater observations
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Estimating Urban Road GPS Environment Friendliness with Bus Trajectories: A City-Scale Approach
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Low-Rank Positive Approximants of Symmetric Matrices
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The Equivalence between Orthogonal Iterations and Alternating Least Squares
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