Capacity dependent estimations by integral operator techniques
In this paper, we study the learning performance of least square regularized regression based on some capacity conditions. An iid setting is considered, where the sequence of probability measures for sampling is identical and the samples are independently drawn. We improve the learning rate to O(m -...
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creator | Qin Guo Yukui Zhu Hongwei Sun |
description | In this paper, we study the learning performance of least square regularized regression based on some capacity conditions. An iid setting is considered, where the sequence of probability measures for sampling is identical and the samples are independently drawn. We improve the learning rate to O(m -β/(1+2β) ) by integral operator techniques. |
doi_str_mv | 10.1109/CISP.2010.5648072 |
format | Conference Proceeding |
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An iid setting is considered, where the sequence of probability measures for sampling is identical and the samples are independently drawn. 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An iid setting is considered, where the sequence of probability measures for sampling is identical and the samples are independently drawn. We improve the learning rate to O(m -β/(1+2β) ) by integral operator techniques.</abstract><pub>IEEE</pub><doi>10.1109/CISP.2010.5648072</doi><tpages>4</tpages></addata></record> |
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subjects | Algorithm design and analysis Approximation error Educational institutions Eigenvalues and eigenfunctions Kernel Least squares approximation Sun |
title | Capacity dependent estimations by integral operator techniques |
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