Patents by Inventor William DAGUE

William DAGUE has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • SYSTEMS AND METHODS OF GENERATING DATASETS FROM HETEROGENEOUS SOURCES FOR MACHINE LEARNING
    Publication number: 20260187495
    Abstract: A computer system is provided that is programmed to select feature sets from a large number of features. Features for a set are selected based on metagradient information returned from a machine learning process that has been performed on an earlier selected feature set. The process can iterate until a selected feature set converges or otherwise meets or exceeds a given threshold.
    Type: Application
    Filed: February 17, 2026
    Publication date: July 2, 2026
    Inventors: Douglas HAMILTON, Michael O'ROURKE, Xuyang LIN, Hyunsoo JEONG, William DAGUE, Tudor MOROSAN
  • Systems and methods of generating datasets from heterogeneous sources for machine learning
    Patent number: 12561581
    Abstract: A computer system is provided that is programmed to select feature sets from a large number of features. Features for a set are selected based on metagradient information returned from a machine learning process that has been performed on an earlier selected feature set. The process can iterate until a selected feature set converges or otherwise meets or exceeds a given threshold.
    Type: Grant
    Filed: November 27, 2024
    Date of Patent: February 24, 2026
    Assignee: Nasdaq, Inc.
    Inventors: Douglas Hamilton, Michael O'Rourke, Xuyang Lin, Hyunsoo Jeong, William Dague, Tudor Morosan
  • SYSTEMS AND METHODS OF GENERATING DATASETS FROM HETEROGENEOUS SOURCES FOR MACHINE LEARNING
    Publication number: 20250086482
    Abstract: A computer system is provided that is programmed to select feature sets from a large number of features. Features for a set are selected based on metagradient information returned from a machine learning process that has been performed on an earlier selected feature set. The process can iterate until a selected feature set converges or otherwise meets or exceeds a given threshold.
    Type: Application
    Filed: November 27, 2024
    Publication date: March 13, 2025
    Inventors: Douglas HAMILTON, Michael O'ROURKE, Xuyang LIN, Hyunsoo JEONG, William DAGUE, Tudor MOROSAN
  • Systems and methods of generating datasets from heterogeneous sources for machine learning
    Patent number: 12159236
    Abstract: A computer system is provided that is programmed to select feature sets from a large number of features. Features for a set are selected based on metagradient information returned from a machine learning process that has been performed on an earlier selected feature set. The process can iterate until a selected feature set converges or otherwise meets or exceeds a given threshold.
    Type: Grant
    Filed: November 20, 2023
    Date of Patent: December 3, 2024
    Assignee: NASDAQ, INC.
    Inventors: Douglas Hamilton, Michael O'Rourke, Xuyang Lin, Hyunsoo Jeong, William Dague, Tudor Morosan
  • SYSTEMS AND METHODS OF GENERATING DATASETS FROM HETEROGENEOUS SOURCES FOR MACHINE LEARNING
    Publication number: 20240086737
    Abstract: A computer system is provided that is programmed to select feature sets from a large number of features. Features for a set are selected based on metagradient information returned from a machine learning process that has been performed on an earlier selected feature set. The process can iterate until a selected feature set converges or otherwise meets or exceeds a given threshold.
    Type: Application
    Filed: November 20, 2023
    Publication date: March 14, 2024
    Inventors: Douglas HAMILTON, Michael O'ROURKE, Xuyang LIN, Hyunsoo JEONG, William DAGUE, Tudor MOROSAN
  • Systems and methods of generating datasets from heterogeneous sources for machine learning
    Patent number: 11861510
    Abstract: A computer system is provided that is programmed to select feature sets from a large number of features. Features for a set are selected based on metagradient information returned from a machine learning process that has been performed on an earlier selected feature set. The process can iterate until a selected feature set converges or otherwise meets or exceeds a given threshold.
    Type: Grant
    Filed: January 6, 2023
    Date of Patent: January 2, 2024
    Assignee: NASDAQ, INC.
    Inventors: Douglas Hamilton, Michael O'Rourke, Xuyang Lin, Hyunsoo Jeong, William Dague, Tudor Morosan
  • SYSTEMS AND METHODS OF GENERATING DATASETS FROM HETEROGENEOUS SOURCES FOR MACHINE LEARNING
    Publication number: 20230142808
    Abstract: A computer system is provided that is programmed to select feature sets from a large number of features. Features for a set are selected based on metagradient information returned from a machine learning process that has been performed on an earlier selected feature set. The process can iterate until a selected feature set converges or otherwise meets or exceeds a given threshold.
    Type: Application
    Filed: January 6, 2023
    Publication date: May 11, 2023
    Inventors: Douglas HAMILTON, Michael O'ROURKE, Xuyang LIN, Hyunsoo JEONG, William DAGUE, Tudor MOROSAN
  • Systems and methods of generating datasets from heterogeneous sources for machine learning
    Patent number: 11568170
    Abstract: A computer system is provided that is programmed to select feature sets from a large number of features. Features for a set are selected based on metagradient information returned from a machine learning process that has been performed on an earlier selected feature set. The process can iterate until a selected feature set converges or otherwise meets or exceeds a given threshold.
    Type: Grant
    Filed: March 28, 2019
    Date of Patent: January 31, 2023
    Assignee: NASDAQ, INC.
    Inventors: Douglas Hamilton, Michael O'Rourke, Xuyang Lin, Hyunsoo Jeong, William Dague, Tudor Morosan
  • SYSTEMS AND METHODS OF GENERATING DATASETS FROM HETEROGENEOUS SOURCES FOR MACHINE LEARNING
    Publication number: 20190303719
    Abstract: A computer system is provided that is programmed to select feature sets from a large number of features. Features for a set are selected based on metagradient information returned from a machine learning process that has been performed on an earlier selected feature set. The process can iterate until a selected feature set converges or otherwise meets or exceeds a given threshold.
    Type: Application
    Filed: March 28, 2019
    Publication date: October 3, 2019
    Inventors: Douglas HAMILTON, Michael O'ROURKE, Xuyang LIN, Hyunsoo JEONG, William DAGUE, Tudor MOROSAN