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:
Nov. 08, 2022

Filed:

Sep. 16, 2020
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 (2006.01);
U.S. Cl.
CPC ...
G06N 20/00 (2019.01); G06F 40/30 (2020.01); G06N 3/04 (2013.01); H04L 67/10 (2013.01);
Abstract

A method, a computer system, and a computer program product are provided for federated learning enhanced with semantic 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 aggregator may integrate the cluster information to define classes. The integrating may include identifying any redundant clusters amongst the identified clusters. A number of the classes may correspond to a total number of the clusters from the distributed computing devices reduced by any redundant clusters. A deep learning model may be sent from the aggregator to the distributed computing devices. The deep learning model may include an output layer having nodes that may correspond to the defined classes. The aggregator may receive results of federated learning performed by the distributed computing devices. The federated learning may train the deep learning model.


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