The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Oct. 26, 2021

Filed:

Apr. 15, 2020
Applicant:

Intel Corporation, Santa Clara, CA (US);

Inventors:

Michael McCourt, San Francisco, CA (US);

Taylor Jackie Springs, San Francisco, CA (US);

Ben Hsu, San Francisco, CA (US);

Simon Howey, San Francisco, CA (US);

Halley Nicki Vance, San Francisco, CA (US);

James Blomo, San Francisco, CA (US);

Patrick Hayes, San Francisco, CA (US);

Scott Clark, San Francisco, CA (US);

Assignee:

Intel Corporation, Santa Clara, CA (US);

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G06N 3/08 (2006.01);
U.S. Cl.
CPC ...
G06N 3/08 (2013.01);
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.


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