TSVMPath: Fast Regularization Parameter Tuning Algorithm for Twin Support Vector Machine-Reference-Cited by-同舟云学术

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TSVMPath: Fast Regularization Parameter Tuning Algorithm for Twin Support Vector Machine

Published:2022-06-07 Issue:6 Volume:54 Page:5457-5482
ISSN:1370-4621
Container-title:Neural Processing Letters
language:en
Short-container-title:Neural Process Lett

Author:

Zhou Kanglei,Zhang Qiyang,Li Juntao^ORCID

Funder

>Natural Science Foundation of China

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Computer Networks and Communications,General Neuroscience,Software

Link

https://link.springer.com/content/pdf/10.1007/s11063-022-10870-1.pdf

Reference49 articles.

1. Kong L, He W, Yang C, Sun C (2020) Robust neurooptimal control for a robot via adaptive dynamic programming. IEEE Trans Neural Netw Learn Syst 32(6):2584–2594

2. Sun C, Li X, Sun Y (2020) A parallel framework of adaptive dynamic programming algorithm with off-policy learning. IEEE Trans Neural Netw Learn Syst 32:3578–3587

3. Liu J, Ran G, Wu Y, Xue L, Sun C (2021) Dynamic event-triggered practical fixed-time consensus for nonlinear multi-agent systems. IEEE Trans Circuits Syst II Express Briefs 69:2156–2160

4. Cortes C, Vapnik V (1995) Support-vector networks. Mach Learn 20(3):273–297

5. Khemchandani R, Chandra S et al (2007) Twin support vector machines for pattern classification. IEEE Trans Pattern Anal Mach Intell 29(5):905–910

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