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:
Aug. 26, 2025

Filed:

Aug. 16, 2022
Applicant:

Jpmorgan Chase Bank, N.a., New York, NY (US);

Inventors:

Antonios Georgiadis, London, GB;

Fanny Silavong, London, GB;

Sean Moran, London, GB;

Rob Otter, Witham, GB;

Varun Babbar, Cambridge, GB;

Assignee:

JPMORGAN CHASE BANK, N.A., New York, NY (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06V 10/772 (2022.01); G06V 10/774 (2022.01); G06V 10/82 (2022.01);
U.S. Cl.
CPC ...
G06V 10/772 (2022.01); G06V 10/774 (2022.01); G06V 10/82 (2022.01);
Abstract

Systems and methods for noise agnostic federated learning are disclosed. A method may include a client computer program executed by an electronic device in a federated learning computer network comprising a plurality of clients: receiving, from a federated learning computer program, a data format having desirable noise characteristics; transforming a client data set comprising variable noise characteristics to the data format using a client generative adversarial network (GAN); generating client weights for the transformed client data set, wherein the client weights indicate features of the client data set; communicating the client weights to the federated learning computer program; receiving, from the federated learning computer program, adjusted weights, wherein the adjusted weights are based on the client weights and a plurality client weights received from the clients in the federated learning computer network; and updating the client weights for a client machine learning model using the adjusted weights.


Find Patent Forward Citations

Loading…