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http://dspace.mediu.edu.my:8181/xmlui/handle/1721.1/7262| Title: | On the V(subscript gamma) Dimension for Regression in Reproducing Kernel Hilbert Spaces |
| Issue Date: | 9-Oct-2013 |
| Description: | This paper presents a computation of the $V_gamma$ dimension for regression in bounded subspaces of Reproducing Kernel Hilbert Spaces (RKHS) for the Support Vector Machine (SVM) regression $epsilon$-insensitive loss function, and general $L_p$ loss functions. Finiteness of the RV_gamma$ dimension is shown, which also proves uniform convergence in probability for regression machines in RKHS subspaces that use the $L_epsilon$ or general $L_p$ loss functions. This paper presenta a novel proof of this result also for the case that a bias is added to the functions in the RKHS. |
| URI: | http://koha.mediu.edu.my:8181/xmlui/handle/1721 |
| Other Identifiers: | AIM-1656 CBCL-172 http://hdl.handle.net/1721.1/7262 |
| Appears in Collections: | MIT Items |
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