Debugging correctness issues in training machine learning models
US12020134B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jan 6, 2023 |
| Grant date | Jun 25, 2024 |
| Priority date | — |
| Expiry date | Jan 6, 2043 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N3/09
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A method includes training, using a first computing system having a first configuration, a first machine learning model having a machine learning model architecture, and training, using a second computing system having a different second configuration, a second machine learning model having the machine learning model architecture. The method also includes determining, for a shared training operation performed by both the first computing system and the second computing system, a similarity measure that represents a similarity between: a first training output generated by the first computing system during performance of the shared training operation during training of the first machine learning model; and a second training output generated by the second computing system during performance of the shared training operation during training of the second machine learning model. The method further includes displaying, to a user, a graphical representation based on the similarity measure determined for the shared training operation.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.