发明申请
US20110071965A1 SYSTEM AND METHOD FOR CROSS DOMAIN LEARNING FOR DATA AUGMENTATION
有权
用于数据接收的跨域学习的系统和方法
- 专利标题： SYSTEM AND METHOD FOR CROSS DOMAIN LEARNING FOR DATA AUGMENTATION
- 专利标题（中）： 用于数据接收的跨域学习的系统和方法
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申请号： US12566270申请日： 2009-09-24
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公开(公告)号： US20110071965A1公开(公告)日： 2011-03-24
- 发明人: Bo Long , Belle Tseng , Sudarshan Lamkhede , Srinivas Vadrevu , Anne Ya Zhang
- 申请人： Bo Long , Belle Tseng , Sudarshan Lamkhede , Srinivas Vadrevu , Anne Ya Zhang
- 申请人地址： US CA Sunnyvale
- 专利权人： Yahoo! Inc.
- 当前专利权人： Yahoo! Inc.
- 当前专利权人地址： US CA Sunnyvale
- 主分类号： G06F15/18
- IPC分类号： G06F15/18 ; G06N5/02
摘要：
According to an example embodiment, a method comprises executing instructions by a special purpose computing apparatus to, for labeled source domain data having a plurality of original labels, generate a plurality of first predicted labels for the labeled source domain data using a target function, the target function determined by using a plurality of labels from labeled target domain data. The method further comprises executing instructions by the special purpose computing apparatus to apply a label relation function to the first predicted labels for the source domain data and the original labels for the source domain data to determine a plurality of weighting factors for the labeled source domain data. The method further comprises executing instructions by the special purpose computing apparatus to generate a new target function using the labeled target domain data, the labeled source domain data, and the weighting factors for the labeled source domain data, and evaluate a performance of the new target function to determine if there is a convergence.