The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.
The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.
Patent No.:
Date of Patent:
Dec. 20, 2022
Filed:
Nov. 27, 2017
Applicant:
D-wave Systems Inc., Burnaby, CA;
Inventor:
Arash Vahdat, Coquitlam, CA;
Assignee:
D-WAVE SYSTEMS INC., Burnaby, CA;
Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G06K 9/62 (2022.01); G06N 3/04 (2006.01); G06N 5/04 (2006.01); G06N 3/08 (2006.01); G06N 7/00 (2006.01);
U.S. Cl.
CPC ...
G06K 9/6278 (2013.01); G06K 9/6232 (2013.01); G06K 9/6256 (2013.01); G06N 3/0427 (2013.01); G06N 3/0454 (2013.01); G06N 3/0472 (2013.01); G06N 3/08 (2013.01); G06N 5/04 (2013.01); G06N 7/005 (2013.01);
Abstract
Machine learning classification models which are robust against label noise are provided. Noise may be modelled explicitly by modelling 'label flips', where incorrect binary labels are 'flipped' relative to their ground truth value. Distributions of label flips may be modelled as prior and posterior distributions in a flexible architecture for machine learning systems. An arbitrary classification model may be provided within the system. The classification model is made more robust to label noise by operation of the prior and posterior distributions. Particular prior and approximating posterior distributions are disclosed.