Patents by Inventor Daniel David Kirsche

Daniel David Kirsche 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 product for machine learning model lifecycle management
    Patent number: 11710076
    Abstract: Computing systems, computing apparatuses, computing methods, and computer program products are disclosed for machine learning model lifecycle management. An example computing method includes receiving a machine learning model selection, a machine learning model experiment creation input, a machine learning model experiment run type, and a machine learning model input data path. The example method further includes determining a machine learning model execution engine based on the machine learning model experiment creation input and the machine learning model experiment run type. The example method further includes retrieving input data based on the machine learning model input data path. The example method further includes executing a machine learning model experiment based on the machine learning model execution engine, machine learning model experiment creation input, and the input data.
    Type: Grant
    Filed: October 21, 2021
    Date of Patent: July 25, 2023
    Assignee: GROUPON, INC.
    Inventors: Daniel David Kirsche, Derrick C. Spell, Bahador Nooraei Beidokht, Xiaohan Zeng, Lingyong Wang, Jae Young Chung, Andrew Lisy
  • METHOD, APPARATUS, AND COMPUTER PROGRAM PRODUCT FOR MACHINE LEARNING MODEL LIFECYCLE MANAGEMENT
    Publication number: 20220180248
    Abstract: Computing systems, computing apparatuses, computing methods, and computer program products are disclosed for machine learning model lifecycle management. An example computing method includes receiving a machine learning model selection, a machine learning model experiment creation input, a machine learning model experiment run type, and a machine learning model input data path. The example method further includes determining a machine learning model execution engine based on the machine learning model experiment creation input and the machine learning model experiment run type. The example method further includes retrieving input data based on the machine learning model input data path. The example method further includes executing a machine learning model experiment based on the machine learning model execution engine, machine learning model experiment creation input, and the input data.
    Type: Application
    Filed: October 21, 2021
    Publication date: June 9, 2022
    Inventors: Daniel David Kirsche, Derrick C. Spell, Bahador Nooraei Beidokht, Xiaohan Zeng, Lingyong Wang, Jae Young Chung, Andrew Lisy
  • Method, apparatus, and computer program product for machine learning model lifecycle management
    Patent number: 11182695
    Abstract: Computing systems, computing apparatuses, computing methods, and computer program products are disclosed for machine learning model lifecycle management. An example computing method includes receiving a machine learning model selection, a machine learning model experiment creation input, a machine learning model experiment run type, and a machine learning model input data path. The example method further includes determining a machine learning model execution engine based on the machine learning model experiment creation input and the machine learning model experiment run type. The example method further includes retrieving input data based on the machine learning model input data path. The example method further includes executing a machine learning model experiment based on the machine learning model execution engine, machine learning model experiment creation input, and the input data.
    Type: Grant
    Filed: August 20, 2018
    Date of Patent: November 23, 2021
    Assignee: GROUPON, INC.
    Inventors: Daniel David Kirsche, Derrick C. Spell, Bahador Nooraei Beidokht, Xiaohan Zeng, Lingyong Wang, Jae Young Chung, Andrew Lisy