Patent · US Active

Resource scheduling using machine learning

US11734066B2 · kind B2 · utility

0Cited by
2References
15Claims
0Family size

Assignee

Inventors

Key dates

Filing dateJan 8, 2020
Grant dateAug 22, 2023
Priority date
Expiry dateJan 8, 2040

Classification

  • Technology area (CPC G)Physics
  • CPC primaryG06F2209/5019
  • WIPO fieldComputer technology
  • WIPO sectorElectrical engineering

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.

Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.