Invention Grant
- Patent Title: Hierarchical models using self organizing learning topologies
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Application No.: US16894332Application Date: 2020-06-05
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Publication No.: US11290477B2Publication Date: 2022-03-29
- Inventor: Pierre-André Savalle , Grégory Mermoud , Laurent Sartran , Jean-Philippe Vasseur
- 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: Behmke Innovation Group
- Agent Kenneth J. Heywood; Jonathon P. Western
- Main IPC: H04L29/06
- IPC: H04L29/06 ; H04L41/142

Abstract:
In one embodiment, a device obtains characteristics of a first anomaly detection model executed by a first distributed learning agent in a network. The device receives a query from a second distributed learning agent in the network that requests identification of a similar anomaly detection to that of a second anomaly detection model executed by the second distributed learning agent. The device identifies, after receiving the query from the second distributed learning agent, the first anomaly detection model as being similar to that of the second anomaly detection model, based on the characteristics of the first anomaly detection model. The device causes the first anomaly detection model to be sent to the second distributed learning agent for execution.
Public/Granted literature
- US20200304530A1 HIERARCHICAL MODELS USING SELF ORGANIZING LEARNING TOPOLOGIES Public/Granted day:2020-09-24
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