- 专利标题: METHOD FOR MACHINE LEARNING WITH STATE INFORMATION
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申请号: US12134073申请日: 2008-06-05
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公开(公告)号: US20080306891A1公开(公告)日: 2008-12-11
- 发明人: Elad Eliezer Hazan , Nimrod Megiddo
- 申请人: Elad Eliezer Hazan , Nimrod Megiddo
- 申请人地址: US NY Armonk
- 专利权人: INTERNATIONAL BUSINESS MACHINES CORPORATION
- 当前专利权人: INTERNATIONAL BUSINESS MACHINES CORPORATION
- 当前专利权人地址: US NY Armonk
- 主分类号: G06F15/18
- IPC分类号: G06F15/18
摘要:
Methods, systems, and computer program products are provided for the online convex optimization problem, in which the decision maker has knowledge of the all past states and resulting cost functions for his previous choices and attempts to make a new choice that results in minimum regret. The method does not rely upon the structure of the cost function or the characterization of the states and takes advantage of the similarity between successive states to enable the method to converge to a reasonably optimal result.
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