- 专利标题: MACHINE LEARNING MODEL WITH WATERMARKED WEIGHTS
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申请号: US17487517申请日: 2021-09-28
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公开(公告)号: US20220012312A1公开(公告)日: 2022-01-13
- 发明人: Deepak Kumar PODDAR , Mihir MODY , Veeramanikandan RAJU , Jason A.T. JONES
- 申请人: TEXAS INSTRUMENTS INCORPORATED
- 申请人地址: US TX Dallas
- 专利权人: TEXAS INSTRUMENTS INCORPORATED
- 当前专利权人: TEXAS INSTRUMENTS INCORPORATED
- 当前专利权人地址: US TX Dallas
- 主分类号: G06F21/16
- IPC分类号: G06F21/16 ; G06N3/04 ; G06N20/00 ; G06F21/12
摘要:
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.
公开/授权文献
- US11704391B2 Machine learning model with watermarked weights 公开/授权日:2023-07-18
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