A new method of online learning with kernels for regression
New optimization models and algorithms for online learning with kernels (OLK) in regression are proposed in a Reproducing Kernel Hilbert Space (RKHS) by solving a constrained optimization model. The “forgetting” factor in the model makes it possible that the memory requirement of the algorithm can b...
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Main Authors: | Li, Guoqi, Wen, Changyun, Cui, Dongyao, Yang, Feng |
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Other Authors: | School of Electrical and Electronic Engineering |
Format: | Conference or Workshop Item |
Language: | English |
Published: |
2013
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Subjects: | |
Online Access: | https://hdl.handle.net/10356/102001 http://hdl.handle.net/10220/12713 |
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Institution: | Nanyang Technological University |
Language: | English |
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