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: | , , , |
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其他作者: | |
格式: | Conference or Workshop Item |
語言: | English |
出版: |
2013
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主題: | |
在線閱讀: | https://hdl.handle.net/10356/102001 http://hdl.handle.net/10220/12713 |
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機構: | Nanyang Technological University |
語言: | English |