Invention Grant
- Patent Title: Self-assessing deep representational units
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Application No.: US16651637Application Date: 2017-09-28
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Publication No.: US11657270B2Publication Date: 2023-05-23
- Inventor: Savitha Ramasamy , Rajaraman Kanagasabai
- Applicant: Agency for Science, Technology and Research
- Applicant Address: SG Singapore
- Assignee: Agency for Science, Technology and Research
- Current Assignee: Agency for Science, Technology and Research
- Current Assignee Address: SG Singapore
- Agency: Shackelford, Bowen, McKinley & Norton, LLP
- International Application: PCT/SG2017/050486 2017.09.28
- International Announcement: WO2019/066718A 2019.04.04
- Date entered country: 2020-03-27
- Main IPC: G06N3/08
- IPC: G06N3/08 ; G06N3/04

Abstract:
A method, a computer-readable medium, and an apparatus for feature learning are provided. The apparatus may receive a data sample as an input to a feature learning model. The apparatus may calculate a reconstruction error based on the data sample and a plurality of features of the feature learning model. The apparatus may determine whether the reconstruction error satisfies a first threshold. The apparatus may add a feature into the feature learning model to represent the data sample if the data sample satisfies the first threshold. The apparatus may determine whether the reconstruction error satisfies a second threshold. The apparatus may ignore the data sample if the reconstruction error satisfies the second threshold. The apparatus may update the weights associated with the plurality of features of the feature learning model if the reconstruction error satisfies neither the first threshold nor the second threshold.
Public/Granted literature
- US20200311544A1 SELF-ASSESSING DEEP REPRESENTATIONAL UNITS Public/Granted day:2020-10-01
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