Logistic regression with total variation regularization

zbMath1458.62153arXiv2003.02678MaRDI QIDQ5146339

Sara van de Geer

Publication date: 25 January 2021

Full work available at URL: https://arxiv.org/abs/2003.02678

zbMATH Keywords

logistic regressionoracle inequalitytotal variation penalty

Mathematics Subject Classification ID

Ridge regression; shrinkage estimators (Lasso) (62J07) Nonparametric estimation (62G05) Generalized linear models (logistic models) (62J12)

Related Items (1)

Prediction bounds for higher order total variation regularized least squares

Cites Work

• Nonlinear total variation based noise removal algorithms
• Estimation and testing under sparsity. École d'Été de Probabilités de Saint-Flour XLV -- 2015
• On the prediction performance of the Lasso
• Splines in higher order TV regularization
• On the total variation regularized estimator over a class of tree graphs
• Weak convergence and empirical processes. With applications to statistics
• Adaptive risk bounds in univariate total variation denoising and trend filtering
• Additive models with trend filtering
• Adaptive piecewise polynomial estimation via trend filtering
• The DFS Fused Lasso: Linear-Time Denoising over General Graphs
• Sparsity and Smoothness Via the Fused Lasso

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