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:
Jun. 20, 2023

Filed:

Aug. 08, 2022
Applicant:

International Business Machines Corporation, Armonk, NY (US);

Inventors:

Vito Paolo Pastore, Lecce, IT;

Yi Zhou, San Jose, CA (US);

Nathalie Baracaldo Angel, San Jose, CA (US);

Ali Anwar, San Jose, CA (US);

Simone Bianco, San Francisco, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
H04L 29/08 (2006.01); G06F 40/30 (2020.01); G06N 20/00 (2019.01); H04L 67/10 (2022.01); G06N 3/04 (2023.01); G06N 3/088 (2023.01); G06N 3/045 (2023.01);
U.S. Cl.
CPC ...
G06N 20/00 (2019.01); G06F 40/30 (2020.01); G06N 3/04 (2013.01); G06N 3/045 (2023.01); G06N 3/088 (2013.01); H04L 67/10 (2013.01);
Abstract

A method, a computer system, and a computer program product are provided for federated learning. An aggregator may receive cluster information from distributed computing devices. The cluster information may relate to identified clusters in sample data of the distributed computing devices. The cluster information may include centroid information per cluster. The aggregator may include a processor. The aggregator may integrate the cluster information to define data classes for machine learning classification. The integrating may include computing a respective distance between centroids of the clusters in order to determine a total number of the data classes. The aggregator may send a deep learning model that includes an output layer that has a total number of nodes equal to the total number of the data classes. The deep learning model may be for the distributed computing devices to perform machine learning classification in federated learning.


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