Neural network training from private data
US11551083B2 · kind B2 · utility
1Cited by
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14Claims
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Key dates
| Filing date | Dec 17, 2019 |
| Grant date | Jan 10, 2023 |
| Priority date | — |
| Expiry date | Nov 22, 2040 |
Classification
- Technology area (CPC H)Electricity
- CPC primaryH04L67/10
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Training and enhancement of neural network models, such as from private data, are described. A slave device receives a version of a neural network model from a master. The slave accesses a local and/or private data source and uses the data to perform optimization of the neural network model. This can be done such as by computing gradients or performing knowledge distillation to locally train an enhanced second version of the model. The slave sends the gradients or enhanced neural network model to a master. The master may use the gradient or second version of the model to improve a master model.
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