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:
Sep. 01, 2020
Filed:
Dec. 29, 2016
Google Llc, Mountain View, CA (US);
Tal Shaked, Los Altos, CA (US);
Rohan Anil, San Francisco, CA (US);
Hrishikesh Balkrishna Aradhye, Mountain View, CA (US);
Mustafa Ispir, Mountain View, CA (US);
Glen Anderson, Palo Alto, CA (US);
Wei Chai, Cupertino, CA (US);
Mehmet Levent Koc, Mountain View, CA (US);
Jeremiah Harmsen, San Jose, CA (US);
Xiaobing Liu, Mountain View, CA (US);
Gregory Sean Corrado, San Francisco, CA (US);
Tushar Deepak Chandra, Los Altos, CA (US);
Heng-Tze Cheng, Mountain View, CA (US);
Google LLC, Mountain View, CA (US);
Abstract
A system includes one or more computers and one or more storage devices storing instructions that when executed by the one or more computers cause the computers to implement a combined machine learning model for processing an input including multiple features to generate a predicted output for the machine learning input. The combined model includes: a deep machine learning model configured to process the features to generate a deep model output; a wide machine learning model configured to process the features to generate a wide model output; and a combining layer configured to process the deep model output generated by the deep machine learning model and the wide model output generated by the wide machine learning model to generate the predicted output, in which the deep model and the wide model have been trained jointly on training data to generate the deep model output and the wide model output.