Generating and utilizing pruned neural networks
US11983632B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Apr 28, 2023 |
| Grant date | May 14, 2024 |
| Priority date | — |
| Expiry date | Apr 28, 2043 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N3/084
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
The disclosure describes one or more implementations of a neural network architecture pruning system that automatically and progressively prunes neural networks. For instance, the neural network architecture pruning system can automatically reduce the size of an untrained or previously-trained neural network without reducing the accuracy of the neural network. For example, the neural network architecture pruning system jointly trains portions of a neural network while progressively pruning redundant subsets of the neural network at each training iteration. In many instances, the neural network architecture pruning system increases the accuracy of the neural network by progressively removing excess or redundant portions (e.g., channels or layers) of the neural network. Further, by removing portions of a neural network, the neural network architecture pruning system can increase the efficiency of the neural network.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.