System and method for training neural networks with errors
US11574194B2 · kind B2 · utility
Assignee
Inventor
Key dates
| Filing date | Mar 27, 2019 |
| Grant date | Feb 7, 2023 |
| Priority date | — |
| Expiry date | Dec 8, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG11C11/1675
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A computing device includes one or more processors, random access memory (RAM), and a non-transitory computer-readable storage medium storing instructions for execution by the one or more processors. The computing device receives first data on which to train a neural network comprising at least one quantized layer and performs a set of training iterations to train weights for the neural network. Each training iteration of the set of training iterations includes stochastically writing values to the random access memory for a set of activations of the at least one quantized layer of the neural network using first write parameters corresponding to a first write error rate. The computing device stores trained values for the weights of the neural network. The trained neural network is configured to classify second data based on the stored values.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.