Invention Grant
- Patent Title: Machine learning using informed pseudolabels
-
Application No.: US16413730Application Date: 2019-05-16
-
Publication No.: US11669724B2Publication Date: 2023-06-06
- Inventor: Philip A. Sallee , James Mullen , Franklin Tanner
- Applicant: Raytheon Company
- Applicant Address: US MA Waltham
- Assignee: Raytheon Company
- Current Assignee: Raytheon Company
- Current Assignee Address: US MA Waltham
- Agency: Scwhegman Lundberg & Woessner, P.A.
- Main IPC: G06N3/08
- IPC: G06N3/08 ; G06N3/04

Abstract:
Subject matter regards improving machine learning techniques using informed pseudolabels. A method can include receiving previously assigned labels indicating an expected classification for data, the labels having a specified uncertainty, generating respective pseudolabels for the data based on the previously assigned labels, the data, a class vector determined by an ML model, and a noise model indicating, based on the specified uncertainty, a likelihood of the previously assigned label given the class, and substituting the pseudolabels for the previously assigned labels in a next epoch of training the ML model.
Public/Granted literature
- US20190354857A1 MACHINE LEARNING USING INFORMED PSEUDOLABELS Public/Granted day:2019-11-21
Information query