Patents by Inventor Simon Howey

Simon Howey 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: 20220114450
    Abstract: A system and method for tuning hyperparameters and training a model includes implementing a hyperparameter tuning service that tunes hyperparameters of a model that includes receiving, via an API, a tuning request that includes: (i) a first part comprising tuning parameters for generating tuned hyperparameter values for hyperparameters of the model; and (ii) a second part comprising model training control parameters for monitoring and controlling a training of the model, wherein the model training control parameters include criteria for generating instructions for curtailing a training run of the model; monitoring the training run for training the model based on the second part of the tuning request, wherein the monitoring of the training run includes periodically collecting training run data; and computing an advanced training curtailment instruction based on the training run data that automatically curtails the training run prior to a predefined maximum training schedule of the training run.
    Type: Application
    Filed: October 22, 2021
    Publication date: April 14, 2022
    Inventors: Michael McCourt, Taylor Jackie Springs, Ben Hsu, Simon Howey, Halley Nicki Vance, James Blomo, Patrick Hayes, Scott Clark
  • Patent number: 11157812
    Abstract: A system and method for tuning hyperparameters and training a model includes implementing a hyperparameter tuning service that tunes hyperparameters of a model that includes receiving, via an API, a tuning request that includes: (i) a first part comprising tuning parameters for generating tuned hyperparameter values for hyperparameters of the model; and (ii) a second part comprising model training control parameters for monitoring and controlling a training of the model, wherein the model training control parameters include criteria for generating instructions for curtailing a training run of the model; monitoring the training run for training the model based on the second part of the tuning request, wherein the monitoring of the training run includes periodically collecting training run data; and computing an advanced training curtailment instruction based on the training run data that automatically curtails the training run prior to a predefined maximum training schedule of the training run.
    Type: Grant
    Filed: April 15, 2020
    Date of Patent: October 26, 2021
    Assignee: Intel Corporation
    Inventors: Michael McCourt, Taylor Jackie Springs, Ben Hsu, Simon Howey, Halley Nicki Vance, James Blomo, Patrick Hayes, Scott Clark
  • Publication number: 20200327412
    Abstract: A system and method for tuning hyperparameters and training a model includes implementing a hyperparameter tuning service that tunes hyperparameters of a model that includes receiving, via an API, a tuning request that includes: (i) a first part comprising tuning parameters for generating tuned hyperparameter values for hyperparameters of the model; and (ii) a second part comprising model training control parameters for monitoring and controlling a training of the model, wherein the model training control parameters include criteria for generating instructions for curtailing a training run of the model; monitoring the training run for training the model based on the second part of the tuning request, wherein the monitoring of the training run includes periodically collecting training run data; and computing an advanced training curtailment instruction based on the training run data that automatically curtails the training run prior to a predefined maximum training schedule of the training run.
    Type: Application
    Filed: April 15, 2020
    Publication date: October 15, 2020
    Inventors: Michael McCourt, Taylor Jackie Springs, Ben Hsu, Simon Howey, Halley Nicki Vance, James Blomo, Patrick Hayes, Scott Clark