Measuring the Algorithmic Convergence of Randomized Ensembles: The Regression Setting-Reference-Cited by-同舟云学术

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Measuring the Algorithmic Convergence of Randomized Ensembles: The Regression Setting

Published:2020-01 Issue:4 Volume:2 Page:921-943
ISSN:2577-0187
Container-title:SIAM Journal on Mathematics of Data Science
language:en
Short-container-title:SIAM Journal on Mathematics of Data Science

Author:

Lopes Miles E.,Wu Suofei,Lee Thomas C. M.

Funder

National Science Foundation

Publisher

Society for Industrial & Applied Mathematics (SIAM)

Link

https://epubs.siam.org/doi/pdf/10.1137/20M1343300

Reference50 articles.

1. Second-Order Properties of an Extrapolated Bootstrap without Replacement under Weak Assumptions

2. Extrapolation of subsampling distribution estimators: The i.i.d. and strong mixing cases

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Extrapolated Cross-Validation for Randomized Ensembles;Journal of Computational and Graphical Statistics;2023-11-27

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