Invention Grant
- Patent Title: Distributed machine learning autoscoring
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Application No.: US14339347Application Date: 2014-07-23
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Publication No.: US09836696B2Publication Date: 2017-12-05
- Inventor: Jean-Philippe Vasseur , Grégory Mermoud , Sukrit Dasgupta
- Applicant: Cisco Technology, Inc.
- Applicant Address: US CA San Jose
- Assignee: Cisco Technology, Inc.
- Current Assignee: Cisco Technology, Inc.
- Current Assignee Address: US CA San Jose
- Agency: Parker Ibrahim & Berg LLC
- Agent James M. Behmke; Stephen D. LeBarron
- Main IPC: G06F15/18
- IPC: G06F15/18 ; G06N5/04 ; G06N99/00

Abstract:
In one embodiment, a management system determines respective capability information of machine learning systems, the capability information including at least an action the respective machine learning system is configured to perform. The management system receives, for each of the machine learning systems, respective performance scoring information associated with the respective action, and computes a degree of freedom for each machine learning system to perform the respective action based on the performance scoring information. Accordingly, the management system then specifies the respective degree of freedom to the machine learning systems. In one embodiment, the management system comprises a management device that computes a respective trust level for the machine learning systems based on receiving the respective performance scoring feedback, and a policy engine that computes the degree of freedom based on receiving the trust level. In further embodiments, the machine learning system performs the action based on the degree of freedom.
Public/Granted literature
- US20160026922A1 Distributed Machine Learning Autoscoring Public/Granted day:2016-01-28
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