Patents by Inventor Michael Canny

Michael Canny 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 FOR TRAINING MACHINE LEARNING CLASSIFICATION MODELS TO GENERATE INVESTMENT DATA PREDICTIONS
    Publication number: 20230325929
    Abstract: Systems and methods for scoring investment data using machine learning-based model training. The method includes receiving historical data over a time period. The method further includes determining positive investment data and negative investment data based on the historical data and investment preference data. The positive investment data including characteristics associated with positive assets that align with the investment preference data. The negative investment data including characteristics associated with negative assets that misalign with the investment data. The method further includes calculating machine learning model parameters based on the positive and negative investment data. The method also includes calculating a score corresponding to a new asset based on the machine learning model parameters and new investment data. The method further includes determining whether the new investment data aligns with the investment preference data based on the score and a threshold investment score.
    Type: Application
    Filed: June 15, 2023
    Publication date: October 12, 2023
    Inventors: John Dance, Amit Shavit, Vineel Gujjar, Michael Canny, John Avery
  • Systems and Methods for an Augmented Stock and Investment Screener
    Publication number: 20200320634
    Abstract: Systems and methods for scoring investment data using machine learning-based model training. The method includes receiving historical data over a time period. The method further includes determining positive investment data and negative investment data based on the historical data and investment preference data. The positive investment data including characteristics associated with positive assets that align with the investment preference data. The negative investment data including characteristics associated with negative assets that misalign with the investment data. The method further includes calculating machine learning model parameters based on the positive and negative investment data. The method also includes calculating a score corresponding to a new asset based on the machine learning model parameters and new investment data. The method further includes determining whether the new investment data aligns with the investment preference data based on the score and a threshold investment score.
    Type: Application
    Filed: April 3, 2020
    Publication date: October 8, 2020
    Inventors: John Dance, Amit Shavit, Vineel Gujjar, Michael Canny, John Avery