Patents by Inventor Olivia Kim

Olivia Kim 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).

  • 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
  • Publication number: 20200302342
    Abstract: Systems and methods for tuning hyperparameters of a model includes: receiving a multi-criteria tuning work request for tuning hyperparameters of the model of the subscriber to the remote tuning service, wherein the multi-criteria tuning work request includes: a first objective function of the model to be optimized by the remote tuning service; a second objective function to be optimized by the remote tuning service, the second objective function being distinct from the first objective function; computing a joint tuning function based on a combination of the first objective function and the second objective function; executing a tuning operation of the hyperparameters for the model based on a tuning of the joint function; and identifying one or more proposed hyperparameter values based on one or more hyperparameter-based points along a convex Pareto optimal curve.
    Type: Application
    Filed: June 8, 2020
    Publication date: September 24, 2020
    Inventors: Bolong Cheng, Olivia Kim, Michael McCourt, Patrick Hayes, Scott Clark
  • Patent number: 10740695
    Abstract: Systems and methods for tuning hyperparameters of a model includes: receiving a multi-criteria tuning work request for tuning hyperparameters of the model of the subscriber to the remote tuning service, wherein the multi-criteria tuning work request includes: a first objective function of the model to be optimized by the remote tuning service; a second objective function to be optimized by the remote tuning service, the second objective function being distinct from the first objective function; computing a joint tuning function based on a combination of the first objective function and the second objective function; executing a tuning operation of the hyperparameters for the model based on a tuning of the joint function; and identifying one or more proposed hyperparameter values based on one or more hyperparameter-based points along a convex Pareto optimal curve.
    Type: Grant
    Filed: November 26, 2019
    Date of Patent: August 11, 2020
    Assignee: SigOpt, Inc.
    Inventors: Bolong Cheng, Olivia Kim, Michael McCourt, Patrick Hayes, Scott Clark
  • Patent number: 10621514
    Abstract: Systems and methods for tuning hyperparameters of a model includes: receiving at a remote tuning service a multi-criteria tuning work request for tuning hyperparameters of the model of a subscriber, wherein the multi-criteria tuning work request includes: a first objective function of the model to be optimized by the remote tuning service; a second objective function to be optimized by the remote tuning service, the second objective function being distinct from the first objective function; computing a first conditionally constrained joint function for the model based on subjecting the first objective function to the second objective function; a second conditionally constrained joint function for the model based on subjecting the second objective function to the first objective function of the model; executing a tuning operation of the hyperparameters for the model; and identifying proposed hyperparameter values based on one or more hyperparameter-based points along a non-convex Pareto optimal curve.
    Type: Grant
    Filed: November 26, 2019
    Date of Patent: April 14, 2020
    Assignee: SigOpt, Inc.
    Inventors: Bolong Cheng, Olivia Kim, Michael McCourt, Patrick Hayes, Scott Clark
  • Publication number: 20200097855
    Abstract: Systems and methods for tuning hyperparameters of a model includes: receiving a multi-criteria tuning work request for tuning hyperparameters of the model of the subscriber to the remote tuning service, wherein the multi-criteria tuning work request includes: a first objective function of the model to be optimized by the remote tuning service; a second objective function to be optimized by the remote tuning service, the second objective function being distinct from the first objective function; computing a joint tuning function based on a combination of the first objective function and the second objective function; executing a tuning operation of the hyperparameters for the model based on a tuning of the joint function; and identifying one or more proposed hyperparameter values based on one or more hyperparameter-based points along a convex Pareto optimal curve.
    Type: Application
    Filed: November 26, 2019
    Publication date: March 26, 2020
    Inventors: Bolong Cheng, Olivia Kim, Michael McCourt, Patrick Hayes, Scott Clark
  • Publication number: 20200097856
    Abstract: Systems and methods for tuning hyperparameters of a model includes: receiving at a remote tuning service a multi-criteria tuning work request for tuning hyperparameters of the model of a subscriber, wherein the multi-criteria tuning work request includes: a first objective function of the model to be optimized by the remote tuning service; a second objective function to be optimized by the remote tuning service, the second objective function being distinct from the first objective function; computing a first conditionally constrained joint function for the model based on subjecting the first objective function to the second objective function; a second conditionally constrained joint function for the model based on subjecting the second objective function to the first objective function of the model; executing a tuning operation of the hyperparameters for the model; and identifying proposed hyperparameter values based on one or more hyperparameter-based points along a non-convex Pareto optimal curve.
    Type: Application
    Filed: November 26, 2019
    Publication date: March 26, 2020
    Inventors: Bolong Cheng, Olivia Kim, Michael McCourt, Patrick Hayes, Scott Clark
  • Publication number: 20200065705
    Abstract: Systems and methods for tuning hyperparameters of a model includes: receiving at a remote tuning service a multi-criteria tuning work request for tuning hyperparameters of the model of a subscriber, wherein the multi-criteria tuning work request includes: a first objective function of the model to be optimized by the remote tuning service; a second objective function to be optimized by the remote tuning service, the second objective function being distinct from the first objective function; computing a first conditionally constrained joint function for the model based on subjecting the first objective function to the second objective function; a second conditionally constrained joint function for the model based on subjecting the second objective function to the first objective function of the model; executing a tuning operation of the hyperparameters for the model; and identifying proposed hyperparameter values based on one or more hyperparameter-based points along a non-convex Pareto optimal curve.
    Type: Application
    Filed: July 31, 2019
    Publication date: February 27, 2020
    Inventors: Bolong Cheng, Olivia Kim, Michael McCourt, Patrick Hayes, Scott Clark
  • Patent number: 10558934
    Abstract: Systems and methods for tuning hyperparameters of a model includes: receiving at a remote tuning service a multi-criteria tuning work request for tuning hyperparameters of the model of a subscriber, wherein the multi-criteria tuning work request includes: a first objective function of the model to be optimized by the remote tuning service; a second objective function to be optimized by the remote tuning service, the second objective function being distinct from the first objective function; computing a first conditionally constrained joint function for the model based on subjecting the first objective function to the second objective function; a second conditionally constrained joint function for the model based on subjecting the second objective function to the first objective function of the model; executing a tuning operation of the hyperparameters for the model; and identifying proposed hyperparameter values based on one or more hyperparameter-based points along a non-convex Pareto optimal curve.
    Type: Grant
    Filed: July 31, 2019
    Date of Patent: February 11, 2020
    Assignee: SigOpt, Inc.
    Inventors: Bolong Cheng, Olivia Kim, Michael McCourt, Patrick Hayes, Scott Clark
  • Patent number: 10528891
    Abstract: Systems and methods for tuning hyperparameters of a model includes: receiving a multi-criteria tuning work request for tuning hyperparameters of the model of the subscriber to the remote tuning service, wherein the multi-criteria tuning work request includes: a first objective function of the model to be optimized by the remote tuning service; a second objective function to be optimized by the remote tuning service, the second objective function being distinct from the first objective function; computing a joint tuning function based on a combination of the first objective function and the second objective function; executing a tuning operation of the hyperparameters for the model based on a tuning of the joint function; and identifying one or more proposed hyperparameter values based on one or more hyperparameter-based points along a convex Pareto optimal curve.
    Type: Grant
    Filed: July 31, 2019
    Date of Patent: January 7, 2020
    Assignee: SigOpt, Inc.
    Inventors: Bolong Cheng, Olivia Kim, Michael McCourt, Patrick Hayes, Scott Clark