Neural Network Parameter Scaling Method for Federated Learning
Summary
The USPTO published patent application US20260099768A1 on April 9, 2026. The application discloses a method for scaling model parameters in federated learning systems where a user equipment applies a scaling factor to parameters based on the number of local training samples before transmitting scaled parameters to a network node. The application was filed on October 11, 2023.
What changed
The USPTO published patent application US20260099768A1 disclosing a method for scaling neural network parameters in federated learning environments. The invention relates to a user equipment obtaining a scaling factor, selectively applying it based on local training sample count, and transmitting scaled parameters to a network node. CPC classification is G06N 20/00.
For technology companies and AI developers working on federated learning systems, this published application provides insight into potential intellectual property claims in the parameter aggregation space. Parties developing similar scaling mechanisms should review the claims upon patent grant to assess potential freedom-to-operate implications.
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Apr 13, 2026GovPing captured this document from the original source. If the source has since changed or been removed, this is the text as it existed at that time.
SCALING MODEL PARAMETERS
Application US20260099768A1 Kind: A1 Apr 09, 2026
Inventors
Shuanshuan WU, Stelios STEFANATOS, Libin LIU, Arthur GUBESKYS
Abstract
Various aspects of the present disclosure generally relate to wireless communication. In some aspects, a user equipment (UE) may obtain information associated with a scaling factor to be applied to a parameter for updating a model. The UE may selectively apply the scaling factor to the parameter, based at least in part on a number of training samples associated with the UE, to obtain a scaled parameter. The UE may transmit the scaled parameter to a network node. Numerous other aspects are described.
CPC Classifications
G06N 20/00
Filing Date
2023-10-11
Application No.
19115402
Named provisions
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