Invention Grant
US07730000B2 Method of developing solutions for online convex optimization problems when a decision maker has knowledge of all past states and resulting cost functions for previous choices and attempts to make new choices resulting in minimal regret
失效
在决策者了解所有过去状态并为之前的选择产生成本函数的情况下开发在线凸优化问题解决方案的方法,并尝试做出新的选择,导致最小的遗憾
- Patent Title: Method of developing solutions for online convex optimization problems when a decision maker has knowledge of all past states and resulting cost functions for previous choices and attempts to make new choices resulting in minimal regret
- Patent Title (中): 在决策者了解所有过去状态并为之前的选择产生成本函数的情况下开发在线凸优化问题解决方案的方法,并尝试做出新的选择,导致最小的遗憾
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Application No.: US12134073Application Date: 2008-06-05
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Publication No.: US07730000B2Publication Date: 2010-06-01
- Inventor: Elad Eliezer Hazan , Nimrod Megiddo
- Applicant: Elad Eliezer Hazan , Nimrod Megiddo
- Applicant Address: US NY Armonk
- Assignee: International Business Machines Corporation
- Current Assignee: International Business Machines Corporation
- Current Assignee Address: US NY Armonk
- Agency: Shimokaji & Assoc, P.C.
- Main IPC: G06F15/18
- IPC: G06F15/18 ; G06F17/16

Abstract:
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.
Public/Granted literature
- US20080306891A1 METHOD FOR MACHINE LEARNING WITH STATE INFORMATION Public/Granted day:2008-12-11
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