Sample efficient nonparametric regression via low-rank regularization

IF 1.4 2区数学 Q2 STATISTICS & PROBABILITY

Journal of Computational and Graphical Statistics Pub Date : 2024-10-15 DOI:10.1080/10618600.2024.2414891

Jiakun Jiang, Jiahao Peng, Heng Lian

引用次数: 0

Abstract

Nonparametric regression suffers from curse of dimensionality, requiring a relatively large sample size for accurate estimation beyond the univariate case. In this paper, we consider a simple metho...

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通过低秩正则化实现样本高效非参数回归

非参数回归存在 "维度诅咒"（curse of dimensionality），需要相对较大的样本量才能进行超出单变量情况的精确估计。在本文中，我们考虑了一种简单的方法。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Journal of Computational and Graphical Statistics 数学-统计学与概率论

CiteScore

3.50

自引率

8.30%

发文量

153

审稿时长

>12 weeks

期刊介绍： The Journal of Computational and Graphical Statistics (JCGS) presents the very latest techniques on improving and extending the use of computational and graphical methods in statistics and data analysis. Established in 1992, this journal contains cutting-edge research, data, surveys, and more on numerical graphical displays and methods, and perception. Articles are written for readers who have a strong background in statistics but are not necessarily experts in computing. Published in March, June, September, and December.