Patents by Inventor Sunny Sanjiv Ketkar

Sunny Sanjiv Ketkar 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).

  • Framework for testing machine learning workflows
    Patent number: 11392469
    Abstract: The disclosed embodiments provide a system for testing machine learning workflows. During operation, the system obtains a configuration for a staging test of a machine learning model, wherein the configuration includes a model name for the machine learning model, a duration of the staging test, and a use case associated with the machine learning model. Next, the system selects a staging test host for the staging test. The system then deploys the staging test on the staging test host in a staging environment, wherein the deployed staging test executes the machine learning model based on live traffic received from a production environment. After the staging test has completed, the system outputs a set of metrics representing a system impact of the machine learning model on the staging test host.
    Type: Grant
    Filed: June 20, 2019
    Date of Patent: July 19, 2022
    Assignee: Microsoft Technology Licensing, LLC
    Inventors: Ali Sadiq Mohamed, Manish Swaminathan, Shunlin Liang, Prateek Sachdev, Vivek Desai, Adam R. Peck, Sunny Sanjiv Ketkar
  • FRAMEWORK FOR TESTING MACHINE LEARNING WORKFLOWS
    Publication number: 20200401491
    Abstract: The disclosed embodiments provide a system for testing machine learning workflows. During operation, the system obtains a configuration for a staging test of a machine learning model, wherein the configuration includes a model name for the machine learning model, a duration of the staging test, and a use case associated with the machine learning model. Next, the system selects a staging test host for the staging test. The system then deploys the staging test on the staging test host in a staging environment, wherein the deployed staging test executes the machine learning model based on live traffic received from a production environment. After the staging test has completed, the system outputs a set of metrics representing a system impact of the machine learning model on the staging test host.
    Type: Application
    Filed: June 20, 2019
    Publication date: December 24, 2020
    Applicant: Microsoft Technology Licensing, LLC
    Inventors: Ali Sadiq Mohamed, Manish Swaminathan, Shunlin Liang, Prateek Sachdev, Vivek Desai, Adam R. Peck, Sunny Sanjiv Ketkar