Patents by Inventor Frank R. Schmidt

Frank R. Schmidt 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).

  • Method, apparatus and computer program for generating robust automatic learning systems and testing trained automatic learning systems
    Patent number: 11676025
    Abstract: A method for training an automated learning system includes processing training input with a first neural network and processing the output of the first neural network with a second neural network. The input layer of the second neural network corresponding to the output layer of the first neural network. The output layer of the second neural network corresponding to the input layer of the first neural network. An objective function is determined using the output of the second neural network and a predetermined modification magnitude. The objective function is approximated using random Cauchy projections which are propagated through the second neural network.
    Type: Grant
    Filed: October 29, 2018
    Date of Patent: June 13, 2023
    Assignees: Robert Bosch GmbH, Carnegie Mellon University
    Inventors: Jeremy Zico Kolter, Eric Wong, Frank R. Schmidt, Jan Hendrik Metzen
  • Method, Apparatus and Computer Program for generating robust automatic learning systems and testing trained automatic learning systems
    Publication number: 20200026996
    Abstract: A method for training an automated learning system includes processing training input with a first neural network and processing the output of the first neural network with a second neural network. The input layer of the second neural network corresponding to the output layer of the first neural network. The output layer of the second neural network corresponding to the input layer of the first neural network. An objective function is determined using the output of the second neural network and a predetermined modification magnitude. The objective function is approximated using random Cauchy projections which are propagated through the second neural network.
    Type: Application
    Filed: October 29, 2018
    Publication date: January 23, 2020
    Inventors: Jeremy Zico Kolter, Eric Wong, Frank R. Schmidt, Jan Hendrik Metzen