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:
Mar. 17, 2026

Filed:

May. 02, 2022
Applicant:

Microsoft Technology Licensing, Llc, Redmond, WA (US);

Inventors:

Boyi Chen, Cupertino, CA (US);

Tong Zhou, Sunnyvale, CA (US);

Siyao Sun, Santa Clara, CA (US);

Lijun Peng, Mountain View, CA (US);

Xinruo Jing, Foster City, CA (US);

Vakwadi Thejaswini Holla, San Jose, CA (US);

Yi Wu, Palo Alto, CA (US);

Pankhuri Goyal, San Jose, CA (US);

Souvik Ghosh, Saratoga, CA (US);

Zheng Li, Palo Alto, CA (US);

Yi Zhang, Los Altos, CA (US);

Onkar A. Dalal, Santa Clara, CA (US);

Jing Wang, Los Altos, CA (US);

Aarthi Jayaram, Palo Alto, CA (US);

Assignee:
Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06N 20/00 (2019.01);
U.S. Cl.
CPC ...
G06N 20/00 (2019.01);
Abstract

Embodiments of the disclosed technologies receive a first-party trained model and a first-party data set from a first-party system into a protected environment, receive a first third-party data set into the protected environment, and, in a data clean room, joining the first-party data set and the first third-party data set to create a joint data set for the particular segment, tuning a first-party trained model with the joint data set to create a third-party tuned model, sending model parameter data learned in the data clean room as a result of the tuning to an aggregator node, receiving a globally tuned version of the first-party trained model from the aggregator node, applying the globally tuned version of the first-party trained model to a second third-party data set to produce a scored third-party data set, and providing the scored third-party data set to a content distribution service of the first-party system.


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