An improved way to make large-scale SVR learning practical

DOI10.1155/S1110865704312096zbMath1101.68796OpenAlexW2099331724MaRDI QIDQ1773787

Jie Yang, Lixiu Yao, Chenzhou Ye, Quan Yong

Publication date: 3 May 2005

Published in: EURASIP Journal on Applied Signal Processing (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1155/s1110865704312096

zbMATH Keywords

support vector regressionsequential minimal optimization

Mathematics Subject Classification ID

Numerical optimization and variational techniques (65K10) Learning and adaptive systems in artificial intelligence (68T05) Signal theory (characterization, reconstruction, filtering, etc.) (94A12) Artificial intelligence for robotics (68T40)

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