Patents by Inventor Thomas Stearns

Thomas Stearns 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).

  • Publication number: 20230052225
    Abstract: A computer system includes a memory configured to store instructions, and one or more processors configured to execute the instructions to cause the computer system to perform a method for event detection. The method includes obtaining a user profile and a persona category associated with the user profile corresponding to a user; receiving first data associated with the user and second data associated with one or more environmental or situational factors; detecting an event based on the first data or the second data; and querying a database in response to the detected event to determine one or more recommended actions for the user based on the user profile and the persona category of the user.
    Type: Application
    Filed: August 12, 2022
    Publication date: February 16, 2023
    Inventors: Scott EDINGTON, Jiri NOVAK, Theodore HARRIS, Simon NILSSON, Thomas STEARNS, Keith TAYLOR
  • Patent number: 11514369
    Abstract: Systems and methods are described for interpreting machine learning model predictions. An example method includes: providing a machine learning model configured to receive a plurality of features as input and provide a prediction as output, wherein the plurality of features includes an engineered feature including a combination of two or more parent features; calculating a Shapley value for each feature in the plurality of features; and allocating a respective portion of the Shapley value for the engineered feature to each of the two or more parent features.
    Type: Grant
    Filed: June 11, 2021
    Date of Patent: November 29, 2022
    Assignee: DataRobot, Inc.
    Inventors: Mark Benjamin Romanowsky, Jared Bowns, Thomas Whitehead, Thomas Stearns, Xavier Conort, Anastasiia Tamazlykar, Mohak Saxena
  • Publication number: 20210390457
    Abstract: Systems and methods are described for interpreting machine learning model predictions. An example method includes: providing a machine learning model configured to receive a plurality of features as input and provide a prediction as output, wherein the plurality of features includes an engineered feature including a combination of two or more parent features; calculating a Shapley value for each feature in the plurality of features; and allocating a respective portion of the Shapley value for the engineered feature to each of the two or more parent features.
    Type: Application
    Filed: June 11, 2021
    Publication date: December 16, 2021
    Inventors: Mark Benjamin Romanowsky, Jared Bowns, Thomas Whitehead, Thomas Stearns, Xavier Conort, Anastasiia Tamazlykar, Mohak Saxena