Implementing a computer system task involving nonstationary streaming time-series data by removing biased gradients from memory
US11410077B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Feb 5, 2019 |
| Grant date | Aug 9, 2022 |
| Priority date | — |
| Expiry date | Jun 11, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N3/084
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A computer-implemented method for implementing a computer system task involving streaming data by removing biased gradients from memory includes generating a parameter sequence including a plurality of parameters corresponding to respective iteration counts. Generating the parameter sequence includes obtaining a first parameter value corresponding to a given iteration count by updating memory corresponding to the given iteration count based on a second parameter value corresponding to a prior iteration count, adapting a size of the updated memory to remove biased gradients, and obtaining the first parameter value by performing a step of a gradient descent method based on the adaptation and the second parameter value. The method further includes learning a time-series model based on the parameter sequence, and implementing a computer system task using the time-series model.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.