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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 151–158 of 158 papers

Title	Date	Tasks	Status
A Rank-Corrected Procedure for Matrix Completion with Fixed Basis Coefficients	Oct 13, 2012	Low-Rank Matrix CompletionMatrix Completion	—Unverified
Fixed-rank matrix factorizations and Riemannian low-rank optimization	Sep 3, 2012	Low-Rank Matrix CompletionMatrix Completion	—Unverified
Low-rank optimization with trace norm penalty	Dec 11, 2011	Low-Rank Matrix CompletionMatrix Completion	—Unverified
RTRMC: A Riemannian trust-region method for low-rank matrix completion	Dec 1, 2011	Low-Rank Matrix CompletionMatrix Completion	—Unverified
Nuclear norm penalization and optimal rates for noisy low rank matrix completion	Nov 29, 2010	Low-Rank Matrix CompletionMatrix Completion	—Unverified
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

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