Early Stopping for Kernel Boosting Algorithms: A General Analysis With Localized Complexities
DOI10.1109/TIT.2019.2927563zbMath1432.62115arXiv1707.01543OpenAlexW2961238573MaRDI QIDQ5211468
Martin J. Wainwright, Fanny Yang, Yuting Wei
Publication date: 28 January 2020
Published in: IEEE Transactions on Information Theory (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1707.01543
Nonparametric regression and quantile regression (62G08) Ridge regression; shrinkage estimators (Lasso) (62J07) Asymptotic properties of nonparametric inference (62G20) Generalized linear models (logistic models) (62J12) Order statistics; empirical distribution functions (62G30) Optimal stopping in statistics (62L15)
Related Items (6)
This page was built for publication: Early Stopping for Kernel Boosting Algorithms: A General Analysis With Localized Complexities