Invention Grant
- Patent Title: Distributed machine learning with privacy protection
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Application No.: US16545813Application Date: 2019-08-20
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Publication No.: US11755884B2Publication Date: 2023-09-12
- Inventor: Sean Stephen Eilert , Shivasankar Gunasekaran , Ameen D. Akel , Kenneth Marion Curewitz , Hongyu Wang
- Applicant: Micron Technology, Inc.
- Applicant Address: US ID Boise
- Assignee: Micron Technology, Inc.
- Current Assignee: Micron Technology, Inc.
- Current Assignee Address: US ID Boise
- Agency: Greenberg Traurig
- Main IPC: G06N3/04
- IPC: G06N3/04 ; G06N3/045 ; G06N20/20 ; G06N3/048

Abstract:
A system having multiple devices that can host different versions of an artificial neural network (ANN). In the system, changes to local versions of the ANN can be combined with a master version of the ANN. In the system, a first device can include memory that can store the master version, a second device can include memory that can store a local version of the ANN, and there can be many devices that store local versions of the ANN. The second device (or any other device of the system hosting a local version) can include a processor that can train the local version, and a transceiver that can transmit changes to the local version generated from the training. The first device can include a transceiver that can receive the changes to a local version, and a processing device that can combine the received changes with the master version.
Public/Granted literature
- US20210056387A1 DISTRIBUTED MACHINE LEARNING WITH PRIVACY PROTECTION Public/Granted day:2021-02-25
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