The regents of the university of california (20250139446). SYSTEMS AND METHODS FOR AUTOMATIC DATA ANNOTATION AND SELF-LEARNING FOR ADAPTIVE MACHINE LEARNING

SYSTEMS AND METHODS FOR AUTOMATIC DATA ANNOTATION AND SELF-LEARNING FOR ADAPTIVE MACHINE LEARNING

Organization Name

the regents of the university of california

Inventor(s)

Guann Pyng Li of Irvine CA US

Yutian Ren of Irvine CA US

SYSTEMS AND METHODS FOR AUTOMATIC DATA ANNOTATION AND SELF-LEARNING FOR ADAPTIVE MACHINE LEARNING

This abstract first appeared for US patent application 20250139446 titled 'SYSTEMS AND METHODS FOR AUTOMATIC DATA ANNOTATION AND SELF-LEARNING FOR ADAPTIVE MACHINE LEARNING

Original Abstract Submitted

a system for automatically self-labeling a digital dataset includes a first sensor for generating a first data stream, a second sensor for collecting information to generate a second data stream, and a causal model manager (cmm). the cmm is configured to determine a first causal event from a first data segment of the first data stream, and a causal relation between the first causal event and a second data segment selected from the second data stream. the system further includes (a) an interactive time model for determining an interaction time between the first and second data segments, and (b) a self-labeling subsystem configured to derive a label from the second data segment, associate the first data segment with the derived label, form a self-labeled data pair from the associated first data segment and the derived label, and automatically annotate the self-labeled data pair with the interaction time.