On two recent nonconvex penalties for regularization in machine learning

DOI10.1016/j.rinam.2022.100256OpenAlexW4220659530MaRDI QIDQ2143527

Sujit Vettam, Majnu John

Publication date: 31 May 2022

Published in: Results in Applied Mathematics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.rinam.2022.100256

zbMATH Keywords

regularizationdeep learningconvolutional neural networknonconvex penalties

Mathematics Subject Classification ID

Artificial neural networks and deep learning (68T07)

Uses Software

• PRMLT

Cites Work

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• Nearly unbiased variable selection under minimax concave penalty
• High-dimensional regression with noisy and missing data: provable guarantees with nonconvexity
• Variable selection and parameter estimation with the Atan regularization method
• DC programming and DCA: thirty years of developments
• Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties
• High-Dimensional Statistics
• A Statistical View of Some Chemometrics Regression Tools
• Difference-of-Convex Learning: Directional Stationarity, Optimality, and Sparsity
• Regularized M-estimators with nonconvexity: Statistical and algorithmic theory for local optima
• Ridge Regression: Biased Estimation for Nonorthogonal Problems

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