Patents by Inventor Jeffrey Todd Miller, JR.

Jeffrey Todd Miller, JR. 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).

  • Advanced detection of rare events and corresponding interactive graphical user interface
    Patent number: 11157837
    Abstract: A system can obtain observations from a dataset. The system can generate a set of training partitions based on the observations and generate an ensemble of machine-learning models based on the set of training partitions. The system can then receive new data and detect whether the new data is indicative of the event using the ensemble. In some cases, the system can update the ensemble by providing the new data as input to an unsupervised machine-learning model that is separate from the ensemble of machine-learning models; receiving an output from the unsupervised machine-learning model indicating whether or not the new data is indicative of the event; incorporating a new observation into the dataset indicating whether or not the new data is indicative of the event based on the output from the unsupervised machine-learning model; and updating the ensemble based on the dataset with the new observation.
    Type: Grant
    Filed: August 2, 2019
    Date of Patent: October 26, 2021
    Assignee: SAS INSTITUTE INC.
    Inventors: Yue Qi, Jeffrey Todd Miller, Jr., Thomas Francis Mutdosch, Rory David Ness MacKenzie, Iain Douglas Jackson, Peter Rowland Eastwood, Ryan Gillespie, Adam Michael Ames, Andrew John Knotts, Robert Wayne Thompson
  • ADVANCED DETECTION OF RARE EVENTS AND CORRESPONDING INTERACTIVE GRAPHICAL USER INTERFACE
    Publication number: 20200042904
    Abstract: A system can obtain observations from a dataset. The system can generate a set of training partitions based on the observations and generate an ensemble of machine-learning models based on the set of training partitions. The system can then receive new data and detect whether the new data is indicative of the event using the ensemble. In some cases, the system can update the ensemble by providing the new data as input to an unsupervised machine-learning model that is separate from the ensemble of machine-learning models; receiving an output from the unsupervised machine-learning model indicating whether or not the new data is indicative of the event; incorporating a new observation into the dataset indicating whether or not the new data is indicative of the event based on the output from the unsupervised machine-learning model; and updating the ensemble based on the dataset with the new observation.
    Type: Application
    Filed: August 2, 2019
    Publication date: February 6, 2020
    Applicant: SAS Institute Inc.
    Inventors: Yue Qi, Jeffrey Todd Miller, JR., Thomas Francis Mutdosch, Rory David Ness MacKenzie, Iain Douglas Jackson, Peter Rowland Eastwood, Ryan Gillespie, Adam Michael Ames, Andrew John Knotts, Robert Wayne Thompson