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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 131–140 of 796 papers

Title	Date	Tasks	Status	Score
Decomposition into Low-rank plus Additive Matrices for Background/Foreground Separation: A Review for a Comparative Evaluation with a Large-Scale Dataset	Nov 4, 2015	Matrix Completion	CodeCode Available	5
DeepVir -- Graphical Deep Matrix Factorization for "In Silico" Antiviral Repositioning: Application to COVID-19	Sep 22, 2020	Matrix Completion	CodeCode Available	5
Collaborative Filtering with Graph Information: Consistency and Scalable Methods	Dec 1, 2015	Collaborative FilteringLow-Rank Matrix Completion	CodeCode Available	5
Spectral Geometric Matrix Completion	Nov 17, 2019	Matrix CompletionRecommendation Systems	CodeCode Available	5
Collective Matrix Completion	Jul 24, 2018	Matrix Completion	CodeCode Available	5
Adaptive Matrix Completion for the Users and the Items in Tail	Apr 22, 2019	Collaborative FilteringLow-Rank Matrix Completion	CodeCode Available	5
A Perturbation Bound on the Subspace Estimator from Canonical Projections	Jun 28, 2022	ClusteringMatrix Completion	CodeCode Available	5
Graph Signal Sampling for Inductive One-Bit Matrix Completion: a Closed-form Solution	Feb 8, 2023	FormMatrix Completion	CodeCode Available	5
A Gradient Descent Algorithm on the Grassman Manifold for Matrix Completion	Oct 27, 2009	Collaborative FilteringLow-Rank Matrix Completion	CodeCode Available	5
Matrix Completion with Cross-Concentrated Sampling: Bridging Uniform Sampling and CUR Sampling	Aug 20, 2022	Matrix Completion	CodeCode Available	5

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