Holistic optimization for accelerating iterative machine learning
US11620574B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Dec 4, 2019 |
| Grant date | Apr 4, 2023 |
| Priority date | — |
| Expiry date | Jul 24, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N5/02
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A great deal of time and computational resources may be used when developing a machine learning or other data processing workflow. This can be related to the need to re-compute the workflow in response to adjustments to the workflow parameters, in order to assess the benefit of such adjustments so as to develop a workflow that satisfies accuracy or other constraints. Embodiments herein provide time and computational savings by selectively storing and re-loading intermediate results of steps of a data processing workflow. For each step of the workflow, during execution, a decision is made whether to store the intermediate results of the step. Thus, these embodiments can offer storage savings as well as processing speedups when repeatedly re-executing machine learning or other data processing workflows during workflow development.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.