SOTAVerified

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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 711–720 of 796 papers

TitleStatusHype
A General Framework for Fast Stagewise Algorithms—0
Matrix Completion under Interval Uncertainty—0
Matrix Coherence and the Nystrom Method—0
Matrix Completion on GraphsCode0
Fast matrix completion without the condition number—0
On the Power of Adaptivity in Matrix Completion and Approximation—0
Relevance Singular Vector Machine for low-rank matrix sensing—0
Online Optimization for Large-Scale Max-Norm Regularization—0
Truncated Nuclear Norm Minimization for Image Restoration Based On Iterative Support Detection—0
Algebraic-Combinatorial Methods for Low-Rank Matrix Completion with Application to Athletic Performance Prediction—0
Show:102550
← PrevPage 72 of 80Next →

No leaderboard results yet.