Invention Grant
- Patent Title: Systems and methods for compression and distribution of machine learning models
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Application No.: US16624497Application Date: 2017-07-06
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Publication No.: US11531932B2Publication Date: 2022-12-20
- Inventor: Jyrki Alakuijala , Robert Obryk
- Applicant: Google LLC
- Applicant Address: US CA Mountain View
- Assignee: Google LLC
- Current Assignee: Google LLC
- Current Assignee Address: US CA Mountain View
- Agency: Dority & Manning, P.A.
- International Application: PCT/US2017/040798 WO 20170706
- International Announcement: WO2019/009897 WO 20190110
- Main IPC: G06N20/00
- IPC: G06N20/00 ; G06N3/04 ; G06N3/08

Abstract:
The present disclosure provides systems and methods for compressing and/or distributing machine learning models. In one example, a computer-implemented method is provided to compress machine-learned models, which includes obtaining, by one or more computing devices, a machine-learned model. The method includes selecting, by the one or more computing devices, a weight to be quantized and quantizing, by the one or more computing devices, the weight. The method includes propagating, by the one or more computing devices, at least a part of a quantization error to one or more non-quantized weights and quantizing, by the one or more computing devices, one or more of the non-quantized weights. The method includes providing, by the one or more computing devices, a quantized machine-learned model.
Public/Granted literature
- US20210027195A1 Systems and Methods for Compression and Distribution of Machine Learning Models Public/Granted day:2021-01-28
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