Invention Grant
- Patent Title: Runtime estimation for machine learning tasks
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Application No.: US15901430Application Date: 2018-02-21
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Publication No.: US11200512B2Publication Date: 2021-12-14
- Inventor: Parijat Dube , Gauri Joshi , Priya Ashok Nagpurkar , Stefania Costache , Diana Jeanne Arroyo , Zehra Noman Sura
- Applicant: International Business Machines Corporation
- Applicant Address: US NY Armonk
- Assignee: International Business Machines Corporation
- Current Assignee: International Business Machines Corporation
- Current Assignee Address: US NY Armonk
- Agency: Amin, Turocy & Watson, LLP
- Main IPC: G06N20/00
- IPC: G06N20/00 ; G06F16/22

Abstract:
Techniques for estimating runtimes of one or more machine learning tasks are provided. For example, one or more embodiments described herein can regard a system that can comprise a memory that stores computer executable components. The system can also comprise a processor, operably coupled to the memory, and that can execute the computer executable components stored in the memory. The computer executable components can comprise an extraction component that can extract a parameter from a machine learning task. The parameter can define a performance characteristic of the machine learning task. Also, the computer executable components can comprise a model component that can generate a model based on the parameter. Further, the computer executable components can comprise an estimation component that can generate an estimated runtime of the machine learning task based on the model. The estimated runtime can define a period of time beginning at an initiation of the machine learning task and ending at a completion of the machine learning task.
Public/Granted literature
- US20190258964A1 RUNTIME ESTIMATION FOR MACHINE LEARNING TASKS Public/Granted day:2019-08-22
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