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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 76–100 of 796 papers

TitleStatusHype
Online Policy Learning and Inference by Matrix Completion—0
Structured Conformal Inference for Matrix Completion with Applications to Group Recommender Systems—0
Concentration properties of fractional posterior in 1-bit matrix completion—0
Energy-modified Leverage Sampling for Radio Map Construction via Matrix Completion—0
Statistical Inference For Noisy Matrix Completion Incorporating Auxiliary Information—0
Matrix Completion via Nonsmooth Regularization of Fully Connected Neural Networks—0
Projected Gradient Descent for Spectral Compressed Sensing via Symmetric Hankel FactorizationCode0
Sensor Network Localization via Riemannian Conjugate Gradient and Rank Reduction: An Extended Version—0
Collaborative Automotive Radar Sensing via Mixed-Precision Distributed Array Completion—0
Power-Flow-Embedded Projection Conic Matrix Completion for Low-Observable Distribution Systems—0
Improving Matrix Completion by Exploiting Rating Ordinality in Graph Neural Networks—0
Randomized Approach to Matrix Completion: Applications in Collaborative Filtering and Image InpaintingCode1
Entry-Specific Bounds for Low-Rank Matrix Completion under Highly Non-Uniform Sampling—0
BlockEcho: Retaining Long-Range Dependencies for Imputing Block-Wise Missing Data—0
Discovering Abstract Symbolic Relations by Learning Unitary Group Representations—0
Causal Imputation for Counterfactual SCMs: Bridging Graphs and Latent Factor Models—0
Doubly Robust Inference in Causal Latent Factor Models—0
Convergence of Gradient Descent with Small Initialization for Unregularized Matrix Completion—0
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
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