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US Patent 9990587 Machine learning heterogeneous edge device, method, and system

Patent 9990587 was granted and assigned to Preferred Networks, Inc on June, 2018 by the United States Patent and Trademark Office.

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Patent
Patent

Patent attributes

Patent Applicant
Preferred Networks, Inc
Preferred Networks, Inc
Current Assignee
Preferred Networks, Inc
Preferred Networks, Inc
Patent Jurisdiction
United States Patent and Trademark Office
United States Patent and Trademark Office
Patent Number
9990587
Patent Inventor Names
Daisuke Okanohara0
Justin B. Clayton0
Nobuyuki Kubota0
Nobuyuki Ota0
Seiya Tokui0
Shohei Hido0
Toru Nishikawa0
Date of Patent
June 5, 2018
Patent Application Number
14602867
Date Filed
January 22, 2015
Patent Citations Received
‌
US Patent 11663659 Methods for early credit risk escalation and management and devices thereof
0
0
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US Patent 11948157 Multi-source anomaly detection and automated dynamic resolution system
0
‌
US Patent 11881107 Systems and methods for inferring parking departures
0
Patent Primary Examiner
‌
Paulinho E Smith
Patent abstract

A machine learning heterogeneous edge device, method, and system are disclosed. In an example embodiment, an edge device includes a communication module, a data collection device, a memory, a machine learning module, a group determination module, and a leader election module. The edge device analyzes collected data with a model, outputs a result, and updates the model to create a local model. The edge device communicates with other edge devices in a heterogeneous group. The edge device determines group membership and determines a leader edge device. The edge device receives a request for the local model, transmits the local model to the leader edge device, receives a mixed model created by the leader edge device performing a mix operation of the local model and a different local model, and replaces the local model with the mixed model.

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