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Mathematics
Volume 10
Issue 3
10.3390/math10030304
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Article

Maximum Correntropy Criterion with Distributed Method

by
Fan Xie
1,
Ting Hu
2,
Shixu Wang
1 and
Baobin Wang
1,*
1
School of Mathematics and Statistics, South-Central University for Nationalities, Wuhan 430074, China
2
School of Mathematics and Statistics, Wuhan University, Wuhan 430072, China
*
Author to whom correspondence should be addressed.
Mathematics 2022, 10(3), 304; https://doi.org/10.3390/math10030304
Submission received: 23 November 2021 / Revised: 5 January 2022 / Accepted: 14 January 2022 / Published: 19 January 2022
(This article belongs to the Topic Machine and Deep Learning)
Versions Notes

Abstract

The Maximum Correntropy Criterion (MCC) has recently triggered enormous research activities in engineering and machine learning communities since it is robust when faced with heavy-tailed noise or outliers in practice. This work is interested in distributed MCC algorithms, based on a divide-and-conquer strategy, which can deal with big data efficiently. By establishing minmax optimal error bounds, our results show that the averaging output function of this distributed algorithm can achieve comparable convergence rates to the algorithm processing the total data in one single machine.
Keywords: correntropy; maximum correntropy criterion; distributed method; robustness; error analysis correntropy; maximum correntropy criterion; distributed method; robustness; error analysis

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MDPI and ACS Style

Xie, F.; Hu, T.; Wang, S.; Wang, B. Maximum Correntropy Criterion with Distributed Method. Mathematics 2022, 10, 304. https://doi.org/10.3390/math10030304

AMA Style

Xie F, Hu T, Wang S, Wang B. Maximum Correntropy Criterion with Distributed Method. Mathematics. 2022; 10(3):304. https://doi.org/10.3390/math10030304

Chicago/Turabian Style

Xie, Fan, Ting Hu, Shixu Wang, and Baobin Wang. 2022. "Maximum Correntropy Criterion with Distributed Method" Mathematics 10, no. 3: 304. https://doi.org/10.3390/math10030304

APA Style

Xie, F., Hu, T., Wang, S., & Wang, B. (2022). Maximum Correntropy Criterion with Distributed Method. Mathematics, 10(3), 304. https://doi.org/10.3390/math10030304

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