Degrees of freedom in low rank matrix estimation

DOI10.1007/s11425-016-0426-8zbMathNoneOpenAlexW2554076815MaRDI QIDQ525906

Ming Yuan

Publication date: 5 May 2017

Published in: Science China. Mathematics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s11425-016-0426-8

zbMATH Keywords

model selectiondegrees of freedomreduced rank regressionlow rank matrix approximationnuclear norm penalizationStein's unbiased risk estimator

Mathematics Subject Classification ID

Estimation in multivariate analysis (62H12) Linear inference, regression (62J99)

Related Items

Stability Approach to Regularization Selection for Reduced-Rank Regression, On the degrees of freedom of mixed matrix regression

Cites Work

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• Estimation of high-dimensional low-rank matrices
• Nuclear-norm penalization and optimal rates for noisy low-rank matrix completion
• Estimation of the mean of a multivariate normal distribution
• Reduced-rank regression for the multivariate linear model
• Smoothing noisy data with spline functions: Estimating the correct degree of smoothing by the method of generalized cross-validation
• Estimating the dimension of a model
• Multivariate reduced-rank regression
• The risk inflation criterion for multiple regression
• On the ``degrees of freedom of the lasso
• Exact matrix completion via convex optimization
• Adapting to Unknown Smoothness via Wavelet Shrinkage
• Estimating the Error Rate of a Prediction Rule: Improvement on Cross-Validation
• How Biased is the Apparent Error Rate of a Prediction Rule?
• On Measuring and Correcting the Effects of Data Mining and Model Selection
• Generalised bilinear regression
• Joint Continuum Regression for Multiple Predictands
• Adaptive Model Selection
• A Statistical View of Some Chemometrics Regression Tools
• Dimension Reduction and Coefficient Estimation in Multivariate Linear Regression
• Recovering Low-Rank Matrices From Few Coefficients in Any Basis
• The Power of Convex Relaxation: Near-Optimal Matrix Completion
• Model Averaging and Dimension Selection for the Singular Value Decomposition
• A Simpler Approach to Matrix Completion
• The biplot graphic display of matrices with application to principal component analysis
• Some Comments on C P
• The Estimation of Prediction Error
• RELATIONS BETWEEN TWO SETS OF VARIATES
• Estimating Linear Restrictions on Regression Coefficients for Multivariate Normal Distributions