Generating sets of training programs for machine learning models

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United States of America Patent

PATENT NO 10949741
APP PUB NO 20180025270A1
SERIAL NO

15631682

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Abstract

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A method, system and computer program product for generating sets of training programs for machine learning models. Fixed values of one or more workload metrics are received from a user, where the workload metrics correspond to low-level program features which define particular low-level application behavior. A profile using the fixed values of the workload metrics is then created. A suite of synthetic applications is generated using the created profile to form a set of training programs which target particular aspects of program behavior. A machine learning model is then trained using the set of training programs. Since the generated synthetic applications provide a broader coverage of the program state-space, the formed set of training programs more accurately targets performance behavior thereby improving the prediction accuracy of the machine learning based predictive models.

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Patent Owner(s)

  • 501 BOARD OF REGENTS THE UNIVERSITY OF TEXAS SYSTEM

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Inventor(s)

Inventor Name Address # of filed Patents Total Citations
Gerstlauer, Andreas Austin, US 2 12
John, Lizy Kurian Austin, US 11 133
Panda, Reena Austin, US 3 37
Zheng, Xinnian Austin, US 1 7

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