US 2024/0403654 A1 · FEDERATED LEARNING PARTICIPANT SELECTION THROUGH LABEL DISTRIBUTION CLUSTERING

Abstract

Systems and techniques that facilitate participant selection in federated learning are provided. For example, one or more embodiments described herein can comprise a system, which can comprise a memory that can store computer executable components. The system can also comprise a processor, operably coupled to the memory that can execute the computer executable components stored in memory. The computer executable components can comprise a clustering component that clusters one or more participants in a federated learning system based on distributions of data classification labels for data sets of the one or more participants into one or more clusters of participants; and a selection component that selects participants equitably from across the one or more clusters of participants for a round of federated learning.

Claims20

Dependent claims

A system comprising:

a memory that stores computer executable components;
and
a processor, operatively coupled to the memory, that executes the computer executable components stored in the memory, wherein the computer executable components comprise:
a clustering component that clusters one or more participants in a federated learning system based on distributions of data classification labels for data sets of the one or more participants into one or more clusters of participants;
and
a selection component that selects participants equitably from across the one or more clusters of participants for a round of federated learning.

3 more elements

Dependencies are inferred from the claim text.

Federated learning participant selection through label distribution clustering

Life of this patent

Federated learning participant selection through label distribution clustering

Life of this patent

Abstract

Claims20