Patents by Inventor Colin Towers

Colin Towers 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).

  • METHODS FOR DEVELOPMENT OF A MACHINE LEARNING SYSTEM THROUGH LAYERED GRADIENT BOOSTING
    Publication number: 20240119315
    Abstract: A layered machine learning system for processing data. The machine learning system comprises decision trees with different depths. An iterative training process is performed on the layered machine learning system to determine the structures of the decision trees based on prior predictions. The fitted decision trees are further configured to update leaf values with a gradient boosting method. By cumulating the predictions of decisions trees in prior iterations, interaction effects are modeled among different depths within the layered machine learning system.
    Type: Application
    Filed: December 6, 2023
    Publication date: April 11, 2024
    Inventors: Rachael MCNAUGHTON, Richard BLAND, Colin TOWERS, William JAMES
  • METHODS FOR DEVELOPMENT OF A MACHINE LEARNING SYSTEM THROUGH LAYERED GRADIENT BOOSTING
    Publication number: 20230419128
    Abstract: A layered machine learning system for processing data. The machine learning system comprises decision trees with different depths. An iterative training process is performed on the layered machine learning system to determine the structures of the decision trees based on prior predictions. The fitted decision trees are further configured to update leaf values with a gradient boosting method. By cumulating the predictions of decisions trees in prior iterations, interaction effects are modeled among different depths within the layered machine learning system.
    Type: Application
    Filed: April 17, 2023
    Publication date: December 28, 2023
    Inventors: Rachael MCNAUGHTON, Richard BLAND, Colin TOWERS, William JAMES
  • Methods for development of a machine learning system through layered gradient boosting
    Patent number: 11853906
    Abstract: A layered machine learning system for processing data. The machine learning system comprises decision trees with different depths. An iterative training process is performed on the layered machine learning system to determine the structures of the decision trees based on prior predictions. The fitted decision trees are further configured to update leaf values with a gradient boosting method. By cumulating the predictions of decisions trees in prior iterations, interaction effects are modeled among different depths within the layered machine learning system.
    Type: Grant
    Filed: April 17, 2023
    Date of Patent: December 26, 2023
    Assignee: Towers Watson Software Limited
    Inventors: Rachael McNaughton, Richard Bland, Colin Towers, William James