Numerical comparisons between Bayesian and frequentist low-rank matrix completion: estimation accuracy and uncertainty quantification

DOI10.48550/arXiv.2103.11749arXiv2103.11749OpenAlexW4319661678MaRDI QIDQ123602

The Tien Mai, The Tien Mai

Publication date: 22 March 2021

Published in: Metron (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2103.11749

zbMATH Keywords

matrix completionBayesian methodconfidence intervaluncertainty quantificationde-biased estimator

Mathematics Subject Classification ID

Statistics (62-XX)

Related Items

dbMC

Cites Work

• Unnamed Item
• Unnamed Item
• Matrix Completion and Low-Rank SVD via Fast Alternating Least Squares
• Pseudo-Bayesian quantum tomography with rank-adaptation
• Nuclear-norm penalization and optimal rates for noisy low-rank matrix completion
• Matrix completion by singular value thresholding: sharp bounds
• 1-bit matrix completion: PAC-Bayesian analysis of a variational approximation
• Flexible low-rank statistical modeling with missing data and side information
• Concentration of tempered posteriors and of their variational approximations
• A Bayesian approach for noisy matrix completion: optimal rate under general sampling distribution
• Parallel stochastic gradient algorithms for large-scale matrix completion
• Exact matrix completion via convex optimization
• Bayesian Methods for Low-Rank Matrix Estimation: Short Survey and Theoretical Study
• Sparse Bayesian Methods for Low-Rank Matrix Estimation
• Multiview Matrix Completion for Multilabel Image Classification
• Fast Low-Rank Bayesian Matrix Completion With Hierarchical Gaussian Prior Models
• Inference and uncertainty quantification for noisy matrix completion
• The Power of Convex Relaxation: Near-Optimal Matrix Completion
• Restricted strong convexity and weighted matrix completion: Optimal bounds with noise