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.

Date of Patent:
Aug. 31, 2021

Filed:

Aug. 03, 2018
Applicant:

Salesforce.com, Inc., San Francisco, CA (US);

Inventors:

Ehsan Hosseini-Asl, Palo Alto, CA (US);

Caiming Xiong, Palo Alto, CA (US);

Yingbo Zhou, San Jose, CA (US);

Richard Socher, Menlo Park, CA (US);

Assignee:

salesforce.com, inc., San Francisco, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G05B 13/02 (2006.01); G06N 3/02 (2006.01); G10L 21/003 (2013.01); G10L 15/065 (2013.01); G10L 15/07 (2013.01); G06K 9/62 (2006.01);
U.S. Cl.
CPC ...
G05B 13/027 (2013.01); G06N 3/02 (2013.01); G10L 21/003 (2013.01); G06K 9/6263 (2013.01); G10L 15/065 (2013.01); G10L 15/075 (2013.01);
Abstract

A method for training parameters of a first domain adaptation model includes evaluating a cycle consistency objective using a first task specific model associated with a first domain and a second task specific model associated with a second domain. The evaluating the cycle consistency objective is based on one or more first training representations adapted from the first domain to the second domain by a first domain adaptation model and from the second domain to the first domain by a second domain adaptation model, and one or more second training representations adapted from the second domain to the first domain by the second domain adaptation model and from the first domain to the second domain by the first domain adaptation model. The method further includes evaluating a learning objective based on the cycle consistency objective, and updating parameters of the first domain adaptation model based on learning objective.


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