Patents by Inventor Sarth Frey

Sarth Frey 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).

  • Systems and methods for implementing an intelligent tuning of multiple hyperparameter criteria of a model constrained with metric thresholds
    Patent number: 12033036
    Abstract: Systems and methods for tuning hyperparameters of a model include receiving a tuning request for tuning hyperparameters, the tuning request includes a first and a second objective function for the machine learning model. The first and second objective functions may output metric values that do not improve uniformly. Systems and methods additionally include defining a joint tuning function that is based on a combination of the first and second objective functions; executing a tuning operation; identifying a Pareto efficient frontier curve defined by a plurality of distinct hyperparameter values; applying metric thresholds to the Pareto efficient frontier curve; demarcating the Pareto efficient frontier curve into at least a first infeasible section and a second feasible section; searching the second feasible section of the Pareto efficient frontier curve for one or more proposed hyperparameter values; and identifying at least a first set of proposed hyperparameter values based on the search.
    Type: Grant
    Filed: July 30, 2020
    Date of Patent: July 9, 2024
    Assignee: Intel Corporation
    Inventors: Michael McCourt, Bolong Cheng, Taylor Jackie Spriggs, Halley Vance, Olivia Kim, Ben Hsu, Sarth Frey, Patrick Hayes, Scott Clark
  • SYSTEMS AND METHODS FOR IMPLEMENTING AN INTELLIGENT TUNING OF MULTIPLE HYPERPARAMETER CRITERIA OF A MODEL CONSTRAINED WITH METRIC THRESHOLDS
    Publication number: 20210034924
    Abstract: Systems and methods for tuning hyperparameters of a model include receiving a tuning request for tuning hyperparameters, the tuning request includes a first and a second objective function for the machine learning model. The first and second objective functions may output metric values that do not improve uniformly. Systems and methods additionally include defining a joint tuning function that is based on a combination of the first and second objective functions; executing a tuning operation; identifying a Pareto efficient frontier curve defined by a plurality of distinct hyperparameter values; applying metric thresholds to the Pareto efficient frontier curve; demarcating the Pareto efficient frontier curve into at least a first infeasible section and a second feasible section; searching the second feasible section of the Pareto efficient frontier curve for one or more proposed hyperparameter values; and identifying at least a first set of proposed hyperparameter values based on the search.
    Type: Application
    Filed: July 30, 2020
    Publication date: February 4, 2021
    Inventors: Michael McCourt, Bolong Cheng, Taylor Jackle Spriggs, Halley Vance, Olivia Kim, Ben Hsu, Sarth Frey, Patrick Hayes, Scott Clark