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Low-Rank Matrix Completion

Low-Rank Matrix Completion is an important problem with several applications in areas such as recommendation systems, sketching, and quantum tomography. The goal in matrix completion is to recover a low rank matrix, given a small number of entries of the matrix.

Source: Universal Matrix Completion

Papers

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Showing 21–30 of 158 papers

Title	Date	Tasks	Status	Score
A Gradient Descent Algorithm on the Grassman Manifold for Matrix Completion	Oct 27, 2009	Collaborative FilteringLow-Rank Matrix Completion	CodeCode Available	5
Distant Supervision for Relation Extraction with Matrix Completion	Jun 1, 2014	Low-Rank Matrix CompletionMatrix Completion	CodeCode Available	5
Collaborative Filtering with Graph Information: Consistency and Scalable Methods	Dec 1, 2015	Collaborative FilteringLow-Rank 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
Algebraic Variety Models for High-Rank Matrix Completion	Mar 28, 2017	ClusteringLow-Rank Matrix Completion	CodeCode Available	5
Mixed Membership Graph Clustering via Systematic Edge Query	Nov 25, 2020	ClusteringCommunity Detection	CodeCode Available	5
Efficient and Robust Freeway Traffic Speed Estimation under Oblique Grid using Vehicle Trajectory Data	Nov 6, 2024	Low-Rank Matrix CompletionMatrix Completion	CodeCode Available	5
Spectal Harmonics: Bridging Spectral Embedding and Matrix Completion in Self-Supervised Learning	May 31, 2023	Inductive BiasLow-Rank Matrix Completion	—Unverified	0
A Majorization-Minimization Gauss-Newton Method for 1-Bit Matrix Completion	Apr 27, 2023	Low-Rank Matrix CompletionMatrix Completion	—Unverified	0
Bounded Manifold Completion	Dec 19, 2019	Dimensionality ReductionImage Inpainting	—Unverified	0

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