Patents by Inventor Ryan TINE

Ryan TINE 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).

  • System and method for facilitating a machine learning model rebuild
    Patent number: 12541705
    Abstract: Some embodiments of the present application include obtaining a trained machine learning model that was trained using training data. Production data may be obtained from a data feed selected based on the trained machine learning model. In some embodiments, feature sets and observed results may be extracted from data output from the data feed, and one or more features or results may be masked to generate the production data. Predicted results data may be generated with the trained machine learning model based on the production data and an accuracy score for the trained machine learning model may be determined based on the predicted results data. If the accuracy score satisfies a threshold accuracy condition, the trained machine learning model may be caused to be rebuilt or the training data may be caused to be updated.
    Type: Grant
    Filed: November 4, 2020
    Date of Patent: February 3, 2026
    Assignee: Capital One Services, LLC
    Inventors: Aditya Patil, Chase Hudson, Ryan Tine
  • SYSTEM AND METHOD FOR FACILITATING A MACHINE LEARNING MODEL REBUILD
    Publication number: 20220138621
    Abstract: Some embodiments of the present application include obtaining a trained machine learning model that was trained using training data. Production data may be obtained from a data feed selected based on the trained machine learning model. In some embodiments, feature sets and observed results may be extracted from data output from the data feed, and one or more features or results may be masked to generate the production data. Predicted results data may be generated with the trained machine learning model based on the production data and an accuracy score for the trained machine learning model may be determined based on the predicted results data. If the accuracy score satisfies a threshold accuracy condition, the trained machine learning model may be caused to be rebuilt or the training data may be caused to be updated.
    Type: Application
    Filed: November 4, 2020
    Publication date: May 5, 2022
    Applicant: Capital One Services, LLC
    Inventors: Aditya PATIL, Chase HUDSON, Ryan TINE