Patents by Inventor Eric Philip TRAUT

Eric Philip TRAUT 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).

  • Training reinforcement machine learning systems
    Patent number: 11663522
    Abstract: A method of training a reinforcement machine learning computer system. The method comprises providing a machine-learning computer programming language including a pre-defined plurality of reinforcement machine learning criterion statements, and receiving a training specification authored in the machine-learning computer programming language. The training specification defines a plurality of training sub-goals with a corresponding plurality of the reinforcement machine learning criterion statements supported by the machine-learning computer programming language. The method further comprises computer translating the plurality of training sub-goals from the training specification into a shaped reward function configured to score a reinforcement machine learning model configuration with regard to the plurality of training sub-goals.
    Type: Grant
    Filed: April 27, 2020
    Date of Patent: May 30, 2023
    Assignee: Microsoft Technology Licensing, LLC
    Inventors: Eric Philip Traut, Marcos de Moura Campos, Xuan Zhao, Ross Ian Story, Victor Shnayder
  • Multi-fidelity simulated data for machine learning
    Patent number: 11562174
    Abstract: A method of training a machine learning system. The method comprises collecting a first simulation dataset derived from a computer simulating a hypothetical scenario with a first simulation configuration having a first degree of fidelity. The method further comprises collecting a second simulation dataset derived from a computer simulating the hypothetical scenario with a second simulation configuration having a second degree of fidelity different than the first degree of fidelity. The method further comprises building a multi-fidelity training dataset including training data from both the first simulation dataset and the second simulation dataset according to an interleaving protocol.
    Type: Grant
    Filed: May 15, 2020
    Date of Patent: January 24, 2023
    Assignee: Microsoft Technology Licensing, LLC
    Inventors: Eric Philip Traut, Marcos de Moura Campos, Ashish Kapoor, Babak Seyed Aghazadeh
  • MULTI-FIDELITY SIMULATED DATA FOR MACHINE LEARNING
    Publication number: 20210357692
    Abstract: A method of training a machine learning system. The method comprises collecting a first simulation dataset derived from a computer simulating a hypothetical scenario with a first simulation configuration having a first degree of fidelity. The method further comprises collecting a second simulation dataset derived from a computer simulating the hypothetical scenario with a second simulation configuration having a second degree of fidelity different than the first degree of fidelity. The method further comprises building a multi-fidelity training dataset including training data from both the first simulation dataset and the second simulation dataset according to an interleaving protocol.
    Type: Application
    Filed: May 15, 2020
    Publication date: November 18, 2021
    Applicant: Microsoft Technology Licensing, LLC
    Inventors: Eric Philip TRAUT, Marcos de Moura CAMPOS, Ashish KAPOOR, Babak SEYED AGHAZADEH
  • TRAINING REINFORCEMENT MACHINE LEARNING SYSTEMS
    Publication number: 20210334696
    Abstract: A method of training a reinforcement machine learning computer system. The method comprises providing a machine-learning computer programming language including a pre-defined plurality of reinforcement machine learning criterion statements, and receiving a training specification authored in the machine-learning computer programming language. The training specification defines a plurality of training sub-goals with a corresponding plurality of the reinforcement machine learning criterion statements supported by the machine-learning computer programming language. The method further comprises computer translating the plurality of training sub-goals from the training specification into a shaped reward function configured to score a reinforcement machine learning model configuration with regard to the plurality of training sub-goals.
    Type: Application
    Filed: April 27, 2020
    Publication date: October 28, 2021
    Applicant: Microsoft Technology Licensing, LLC
    Inventors: Eric Philip TRAUT, Marcos de Moura CAMPOS, Xuan ZHAO, Ross Ian STORY, Victor SHNAYDER