Invention Application
- Patent Title: MACHINE LEARNING WITH FEATURE OBFUSCATION
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Application No.: PCT/US2020/046157Application Date: 2020-08-13
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Publication No.: WO2021034602A1Publication Date: 2021-02-25
- Inventor: BRADSHAW, Samuel E. , GUNASEKARAN, Shivasankar , EILERT, Sean Stephen , AKEL, Ameen D. , CUREWITZ, Kenneth Marion
- Applicant: MICRON TECHNOLOGY, INC.
- Applicant Address: 8000 South Federal Way
- Assignee: MICRON TECHNOLOGY, INC.
- Current Assignee: MICRON TECHNOLOGY, INC.
- Current Assignee Address: 8000 South Federal Way
- Agency: WARD, John P. et al.
- Priority: US16/545, 837 2019-08-20
- Main IPC: G06N3/08
- IPC: G06N3/08 ; G06N3/04 ; G06N20/00 ; G06F21/14
Abstract:
A system having multiple devices that can host different versions of an artificial neural network (ANN). In the system, inputs for the ANN can be obfuscated for centralized training of a master version of the ANN at a first computing device. A second computing device in the system includes memory that stores a local version of the ANN and user data for inputting into the local version. The second computing device includes a processor that extracts features from the user data and obfuscates the extracted features to generate obfuscated user data. The second device includes a transceiver that transmits the obfuscated user data. The first computing device includes a memory that stores the master version of the ANN, a transceiver that receives obfuscated user data transmitted from the second computing device, and a processor that trains the master version based on the received obfuscated user data using machine learning.
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