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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 11–20 of 158 papers

Title	Date	Tasks	Status	Score
Guaranteed Rank Minimization via Singular Value Projection	Sep 30, 2009	Low-Rank Matrix CompletionMatrix Completion	CodeCode Available	5
Algebraic Variety Models for High-Rank Matrix Completion	Mar 28, 2017	ClusteringLow-Rank Matrix Completion	CodeCode Available	5
GNMR: A provable one-line algorithm for low rank matrix recovery	Jun 24, 2021	Low-Rank Matrix CompletionMatrix 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
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
Efficient Compression of Overparameterized Deep Models through Low-Dimensional Learning Dynamics	Nov 8, 2023	Low-Rank Matrix Completion	CodeCode Available	5
Depth Image Inpainting: Improving Low Rank Matrix Completion with Low Gradient Regularization	Apr 20, 2016	Image InpaintingLow-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
Collaborative Filtering with Graph Information: Consistency and Scalable Methods	Dec 1, 2015	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

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