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:
Jul. 30, 2024

Filed:

Dec. 21, 2020
Applicant:

Apple Inc., Cupertino, CA (US);

Inventors:

Stephen Cosman, San Jose, CA (US);

Kalu Onuka Kalu, Los Gatos, CA (US);

Marcelo Lotif Araujo, Campbell, CA (US);

Michael Chatzidakis, Mountain View, CA (US);

Thi Hai Van Do, Santa Clara, CA (US);

Alexis Hugo Louis Durocher, San Francisco, CA (US);

Guillaume Tartavel, Cupertino, CA (US);

Sowmya Gopalan, Santa Clara, CA (US);

Vignesh Jagadeesh, Cupertino, CA (US);

Abhishek Bhowmick, Sunnyvale, CA (US);

John Duchi, Menlo Park, CA (US);

Julien Freudiger, San Francisco, CA (US);

Gaurav Kapoor, Santa Clara, CA (US);

Ryan M. Rogers, Sunnyvale, CA (US);

Assignee:

Apple Inc., Cupertino, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
H04L 67/1097 (2022.01); G06F 16/2457 (2019.01); G06F 16/438 (2019.01); G06F 16/44 (2019.01); G06F 18/214 (2023.01); G06F 21/62 (2013.01); G06N 3/063 (2023.01); G06N 20/00 (2019.01); G06V 10/774 (2022.01); G06V 10/82 (2022.01); H04L 67/00 (2022.01);
U.S. Cl.
CPC ...
H04L 67/1097 (2013.01); G06F 16/24578 (2019.01); G06F 16/438 (2019.01); G06F 16/447 (2019.01); G06F 18/2148 (2023.01); G06F 21/6254 (2013.01); G06N 3/063 (2013.01); G06N 20/00 (2019.01); G06V 10/7747 (2022.01); G06V 10/82 (2022.01); H04L 67/34 (2013.01);
Abstract

Embodiments described herein provide for a non-transitory machine-readable medium storing instructions to cause one or more processors to receive, at a client device, a machine learning model from a server, detect a usage pattern for a content item, store an association between the content item and the detected usage pattern in local data, train the machine learning model using local data for the content item with the detected usage pattern to generate a trained machine learning model, generate an update for the machine learning model, privatize the update for the machine learning model, and transmit the privatized update for the machine learning model to the server.


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