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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 791–796 of 796 papers

Title	Date	Tasks	Status
Online Identification and Tracking of Subspaces from Highly Incomplete Information	Jun 21, 2010	Matrix Completion	CodeCode Available
Matrix Completion from Power-Law Distributed Samples	Dec 1, 2009	Low-Rank Matrix CompletionMatrix Completion	—Unverified
A Gradient Descent Algorithm on the Grassman Manifold for Matrix Completion	Oct 27, 2009	Collaborative FilteringLow-Rank Matrix Completion	CodeCode Available
Guaranteed Rank Minimization via Singular Value Projection	Sep 30, 2009	Low-Rank Matrix CompletionMatrix Completion	CodeCode Available
Matrix Completion from Noisy Entries	Jun 11, 2009	Collaborative FilteringMatrix Completion	CodeCode Available
Matrix Completion from a Few Entries	Jan 20, 2009	Matrix Completion	CodeCode Available

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