Invention Grant
- Patent Title: Machine learning model with watermarked weights
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Application No.: US17487517Application Date: 2021-09-28
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Publication No.: US11704391B2Publication Date: 2023-07-18
- Inventor: Deepak Kumar Poddar , Mihir Mody , Veeramanikandan Raju , Jason A. T. Jones
- Applicant: TEXAS INSTRUMENTS INCORPORATED
- Applicant Address: US TX Dallas
- Assignee: Texas Instruments Incorporated
- Current Assignee: Texas Instruments Incorporated
- Current Assignee Address: US TX Dallas
- Agent Michael T. Gabrik; Frank D. Cimino
- Main IPC: G06F21/00
- IPC: G06F21/00 ; G06F21/16 ; G06N20/00 ; G06F21/12 ; G06N3/047

Abstract:
In some examples, a system includes storage storing a machine learning model, wherein the machine learning model comprises a plurality of layers comprising multiple weights. The system also includes a processing unit coupled to the storage and operable to group the weights in each layer into a plurality of partitions; determine a number of least significant bits to be used for watermarking in each of the plurality of partitions; insert one or more watermark bits into the determined least significant bits for each of the plurality of partitions; and scramble one or more of the weight bits to produce watermarked and scrambled weights. The system also includes an output device to provide the watermarked and scrambled weights to another device.
Public/Granted literature
- US20220012312A1 MACHINE LEARNING MODEL WITH WATERMARKED WEIGHTS Public/Granted day:2022-01-13
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