Invention Grant
- Patent Title: Machine learning models based on altered data and systems and methods for training and using the same
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Application No.: US16854107Application Date: 2020-04-21
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Publication No.: US11861493B2Publication Date: 2024-01-02
- Inventor: Dmitry Vengertsev , Zahra Hosseinimakarem , Jonathan D. Harms
- 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: Dorsey & Whitney LLP
- Main IPC: G06N3/08
- IPC: G06N3/08 ; G06N3/04 ; G06F18/24 ; G06F18/214 ; G06V10/764 ; G06V10/82

Abstract:
Data may be abstracted and/or masked prior to being provided to a machine learning model for training. A machine learning model may provide a confidence level associated with a result. If the confidence level is too high, the machine learning model or an application including the machine learning model may refrain from providing the result as an output. In some examples, the machine learning model may provide a “second best” result that has an acceptable confidence level. In other examples, an error signal may be provided as the output. In accordance with examples of the present disclosure, data may be abstracted and/or masked prior to being provided to a machine learning model for training and confidence levels of results of the trained machine learning model may be used to determine when a result should be withheld.
Public/Granted literature
- US20210201195A1 MACHINE LEARNING MODELS BASED ON ALTERED DATA AND SYSTEMS AND METHODS FOR TRAINING AND USING THE SAME Public/Granted day:2021-07-01
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