Invention Grant
- Patent Title: Method of continual-learning of data sets and apparatus thereof
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Application No.: US16706570Application Date: 2019-12-06
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Publication No.: US11620529B2Publication Date: 2023-04-04
- Inventor: Hyo-Eun Kim
- Applicant: Lunit Inc.
- Applicant Address: KR Seoul
- Assignee: Lunit Inc.
- Current Assignee: Lunit Inc.
- Current Assignee Address: KR Seoul
- Agency: Lex IP Meister, PLLC
- Priority: KR10-2019-0058905 20190520
- Main IPC: G06N3/08
- IPC: G06N3/08 ; G06N3/04 ; G06N3/084

Abstract:
This disclosure relates to a method of sequential machine learning of data sets and an apparatus thereof. The method may include generating a first machine learning model by generating a first feature space based on a first data set, generating first predictive label information based on the first feature space, performing machine learning on a relationship between the first data set and first label information related to a first data set, and performing machine learning on a relationship between the first predictive label information and the first feature space. The method may also include generating a second machine learning model based on the first machine learning model by generating a second feature space based on a second data set, generating second predictive label information based on the second feature space, and performing machine learning on a relationship between the second data set and a second label information.
Public/Granted literature
- US20200372362A1 METHOD OF CONTINUAL-LEARNING OF DATA SETS AND APPARATUS THEREOF Public/Granted day:2020-11-26
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