SOTAVerified|Agents Browse Leaderboard About

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 Added Most Hyped Most Active Needs Verification Most Verified

Showing 101–110 of 796 papers

Title	Date	Tasks	Status	Score
Low-Rank Hankel Tensor Completion for Traffic Speed Estimation	May 21, 2021	Matrix CompletionState Estimation	CodeCode Available	5
Low-Rank Inducing Norms with Optimality Interpretations	Dec 9, 2016	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
Bayesian Matrix Completion via Adaptive Relaxed Spectral Regularization	Dec 3, 2015	Bayesian InferenceCollaborative Filtering	CodeCode Available	5
A Neural Network for Semigroups	Mar 12, 2021	DenoisingImage Reconstruction	CodeCode Available	5
Matrix Completion from Noisy Entries	Jun 11, 2009	Collaborative FilteringMatrix Completion	CodeCode Available	5
Collaborative Filtering with Graph Information: Consistency and Scalable Methods	Dec 1, 2015	Collaborative FilteringLow-Rank Matrix Completion	CodeCode Available	5
Matrix Completion via Nonconvex Regularization: Convergence of the Proximal Gradient Algorithm	Mar 2, 2019	Matrix Completion	CodeCode Available	5
Causal Inference with Noisy and Missing Covariates via Matrix Factorization	Jun 3, 2018	Causal InferenceMatrix Completion	CodeCode Available	5
A Generalized Latent Factor Model Approach to Mixed-data Matrix Completion with Entrywise Consistency	Nov 17, 2022	Collaborative FilteringMatrix Completion	CodeCode Available	5

Show:10 25 50

← PrevPage 11 of 80Next →

No leaderboard results yet.