Invention Grant
- Patent Title: System and method of robust active learning method using noisy labels and domain adaptation
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Application No.: US16724109Application Date: 2019-12-20
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Publication No.: US11551084B2Publication Date: 2023-01-10
- Inventor: Rajshekhar Das , Filipe J. Cabrita Condessa , Jeremy Zieg Kolter
- Applicant: Robert Bosch GmbH
- Applicant Address: DE Stuttgart
- Assignee: Robert Bosch GmbH
- Current Assignee: Robert Bosch GmbH
- Current Assignee Address: DE Stuttgart
- Agency: Brooks Kushman P.C.
- Main IPC: G06N20/00
- IPC: G06N20/00 ; G06N3/08 ; G06N3/04 ; G06F9/48

Abstract:
A system and method is disclosed for labeling an unlabeled dataset, with a labeling budget constraint and noisy oracles (i.e. noisy labels provided by annotator), using a noisy labeled dataset from another domain or application. The system and method combine active learning with noisy labels and active learning with domain adaptation to enhance classification performance.
Public/Granted literature
- US20210192335A1 SYSTEM AND METHOD OF ROBUST ACTIVE LEARNING METHOD USING NOISY LABELS AND DOMAIN ADAPTATION Public/Granted day:2021-06-24
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