Correctness preserving optimization of deep neural networks
US11455538B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Dec 20, 2018 |
| Grant date | Sep 27, 2022 |
| Priority date | — |
| Expiry date | Jul 28, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06V20/58
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A method for reducing the number of neurons in a trained deep neural network (DNN) includes classifying layer types in a plurality of hidden layers; evaluating the accuracy of the DNN using a validation set of data; and generating a layer specific ranking of neurons, wherein the generating includes: analyzing, using the validation set of data for one or more of the plurality of hidden layers, the activation function for each neuron in the analyzed layers to determine an activation score for each neuron; and ranking, on a layer type basis, each neuron in the analyzed layers based on the neuron's activation score to generate a layer specific ranking of neurons. The method further includes removing a number of lower ranked neurons from the DNN that does not result in the DNN after the removal of selected lower ranked neurons to fall outside of an accuracy threshold limit.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.