发明名称 |
Computationally efficient probabilistic linear regression |
摘要 |
A computationally efficient method of performing probabilistic linear regression is described. In an embodiment, the method involves adding a white noise term to a weighted linear sum of basis functions and then normalizing the combination. This generates a linear model comprising a set of sparse, normalized basis functions and a modulated noise term. When using the linear model to perform linear regression, the modulated noise term increases the variance associated with output values which are distant from any data points. |
申请公布号 |
US8250003(B2) |
申请公布日期 |
2012.08.21 |
申请号 |
US20080209621 |
申请日期 |
2008.09.12 |
申请人 |
CANDELA JOAQUIN QUINONERO;SNELSON EDWARD LLOYD;WILLIAMS OLLIVER MICHAEL CHRISTIAN;MICROSOFT CORPORATION |
发明人 |
CANDELA JOAQUIN QUINONERO;SNELSON EDWARD LLOYD;WILLIAMS OLLIVER MICHAEL CHRISTIAN |
分类号 |
G06F15/18 |
主分类号 |
G06F15/18 |
代理机构 |
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代理人 |
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主权项 |
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地址 |
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