Invention Grant
- Patent Title: Resource scheduling using machine learning
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Application No.: US15943206Application Date: 2018-04-02
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Publication No.: US10579423B2Publication Date: 2020-03-03
- Inventor: Jinchao Li , Yu Wang , Karan Srivastava , Jianfeng Gao , Prabhdeep Singh , Haiyuan Cao , Xinying Song , Hui Su , Jaideep Sarkar
- Applicant: Microsoft Technology Licensing, LLC
- Applicant Address: US WA Redmond
- Assignee: Microsoft Technology Licensing, LLC
- Current Assignee: Microsoft Technology Licensing, LLC
- Current Assignee Address: US WA Redmond
- Agency: Schwegman Lundberg & Woessner, P.A.
- Main IPC: G06F9/46
- IPC: G06F9/46 ; G06F9/48 ; G06K9/62 ; G06F9/50 ; G06N20/00

Abstract:
Generally discussed herein are devices, systems, and methods for scheduling tasks to be completed by resources. A method can include identifying features of the task, the features including a time-dependent feature and a time-independent feature, the time-dependent feature indicating a time the task is more likely to be successfully completed by the resource, converting the features to feature values based on a predefined mapping of features to feature values in a first memory device, determining, by a gradient boost tree model and based on a first current time and the feature values, a likelihood the resource will successfully complete the task, and scheduling the task to be performed by the resource based on the determined likelihood.
Public/Granted literature
- US20190303197A1 RESOURCE SCHEDULING USING MACHINE LEARNING Public/Granted day:2019-10-03
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