Revised online learning with kernels for classification and regression

Author

Guoqi LI
Kiruthika RAMANATHAN, Singapore Management UniversityFollow
Kiruthika RAMANATHAN
Luping SHI

Publication Type

Conference Proceeding Article

Publication Date

9-2013

Abstract

Revised algorithm for online learning with kernels (OLK) in classification and regression is proposed in a reproducing kernel hilbert space (RKHS). Compared with the original OLK, the revised algorithm allows that the new data points arrive either one by one or two by two

Discipline

Databases and Information Systems

Research Areas

Data Science and Engineering

Publication

Proceedings of the 2013 IEEE Symposium on Computational Intelligence and Data Mining, Singapore, April 16-19

Identifier

10.1109/CIDM.2013.6597247

Publisher

IEEE

City or Country

Singapore

Citation

LI, Guoqi; RAMANATHAN, Kiruthika; RAMANATHAN, Kiruthika; and SHI, Luping. Revised online learning with kernels for classification and regression. (2013). Proceedings of the 2013 IEEE Symposium on Computational Intelligence and Data Mining, Singapore, April 16-19.
Available at: https://ink.library.smu.edu.sg/sis_research/7431

Additional URL

http://doi.org/10.1109/CIDM.2013.6597247