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Matrix Completion

Matrix Completion is a method for recovering lost information. It originates from machine learning and usually deals with highly sparse matrices. Missing or unknown data is estimated using the low-rank matrix of the known data.

Source: A Fast Matrix-Completion-Based Approach for Recommendation Systems

Papers

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Showing 126–150 of 796 papers

TitleStatusHype
High Dimensional Factor Analysis with Weak Factors—0
Mixed Matrix Completion in Complex Survey Sampling under Heterogeneous Missingness—0
Data-driven model selection within the matrix completion method for causal panel data models—0
Fast Dual-Regularized Autoencoder for Sparse Biological Data—0
On the Robustness of Cross-Concentrated Sampling for Matrix Completion—0
Matrix Completion with Hypergraphs:Sharp Thresholds and Efficient Algorithms—0
Effect of Beampattern on Matrix Completion with Sparse Arrays—0
Polynomial Precision Dependence Solutions to Alignment Research Center Matrix Completion Problems—0
Misclassification excess risk bounds for 1-bit matrix completion—0
Waveform Design for OFDM-based ISAC Systems Under Resource Occupancy Constraint—0
Automotive Radar Sensing with Sparse Linear Arrays Using One-Bit Hankel Matrix Completion—0
Multiple Testing of Linear Forms for Noisy Matrix Completion—0
Iterative missing value imputation based on feature importance—0
Harmonic Retrieval Using Weighted Lifted-Structure Low-Rank Matrix Completion—0
Blocked Collaborative Bandits: Online Collaborative Filtering with Per-Item Budget Constraints—0
Triple Simplex Matrix Completion for Expense Forecasting—0
A framework to generate sparsity-inducing regularizers for enhanced low-rank matrix completion—0
Robust matrix completion via Novel M-estimator Functions—0
Robust Low-Rank Matrix Completion via a New Sparsity-Inducing Regularizer—0
Matrix Completion-Informed Deep Unfolded Equilibrium Models for Self-Supervised k-Space Interpolation in MRI—0
IHT-Inspired Neural Network for Single-Snapshot DOA Estimation with Sparse Linear Arrays—0
L_2,1-Norm Regularized Quaternion Matrix Completion Using Sparse Representation and Quaternion QR Decomposition—0
Widely Separated MIMO Radar Using Matrix Completion—0
Applications of Nature-Inspired Metaheuristic Algorithms for Tackling Optimization Problems Across DisciplinesCode0
Matrix Completion in Almost-Verification Time—0
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