发明申请
- 专利标题: METHOD FOR AN OPTIMIZING PREDICTIVE MODEL USING GRADIENT DESCENT AND CONJUGATE RESIDUALS
- 专利标题(中): 使用梯度和连续残差优化预测模型的方法
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申请号: US14165431申请日: 2014-01-27
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公开(公告)号: US20140214735A1公开(公告)日: 2014-07-31
- 发明人: Georges Harik
- 申请人: Georges Harik , PageBites, Inc.
- 申请人地址: US CA Palo Alto US CA Palo Alto
- 专利权人: PageBites, Inc.,Georges Harik
- 当前专利权人: PageBites, Inc.,Georges Harik
- 当前专利权人地址: US CA Palo Alto US CA Palo Alto
- 主分类号: G06N99/00
- IPC分类号: G06N99/00
摘要:
An optimization in machine learning is achieved using Newton's algorithm together with an efficient technique for solving linear equations, such as the method of conjugate residuals. The techniques of the present invention are applicable to learning language models, predicting classes of objects from images and videos, and classifying financial transactions for prevention of fraud. Other uses include determining a function from a sequence of words to a relevant web page for a search engine, or to inverting arbitrary output values of an analyzed system into an internally running simulation.
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