Incremental Huber-Support vector regression based online robust parameter design-Reference-Cited by-同舟云学术

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Incremental Huber-Support vector regression based online robust parameter design

Published:2022-11-27 Issue: Volume: Page:1-21
ISSN:0361-0926
Container-title:Communications in Statistics - Theory and Methods
language:en
Short-container-title:Communications in Statistics - Theory and Methods

Author:

Zhou Xiaojian¹,Xiao Dan²,Yu Jieyao¹,Jiang Ting³

Affiliation:

1. School of Management, Nanjing University of Posts and Telecommunications, Nanjing, China

2. China United Network Communications Co., Ltd., China Unicom Guizhou Branch, Guiyang, China

3. School of Information Engineering, Nanjing University of Finance and Economics, Nanjing, China

Funder

National Natural Science Foundation of China

Publisher

Informa UK Limited

Subject

Statistics and Probability

Link

https://www.tandfonline.com/doi/pdf/10.1080/03610926.2022.2150056

Reference33 articles.

1. Robust Support Vector Regression in Primal with Asymmetric Huber Loss

2. Robust twin support vector regression based on Huber loss function

3. Functional iterative approaches for solving support vector classification problems based on generalized Huber loss

4. Robust regularized extreme learning machine with asymmetric Huber loss function

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. Online robust parameter design using sequential support vector regression based Bayesian optimization;Journal of Mathematical Analysis and Applications;2024-12

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