Computationally efficient neural network architecture search
US10997503B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jun 20, 2019 |
| Grant date | May 4, 2021 |
| Priority date | — |
| Expiry date | Jul 1, 2039 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N3/09
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A method for receiving training data for training a neural network to perform a machine learning task and for searching for, using the training data, an optimized neural network architecture for performing the machine learning task is described. Searching for the optimized neural network architecture includes: maintaining population data; maintaining threshold data; and repeatedly performing the following operations: selecting one or more candidate architectures from the population data; generating a new architecture from the one or more selected candidate architectures; for the new architecture: training a neural network having the new architecture until termination criteria for the training are satisfied; and determining a final measure of fitness of the neural network having the new architecture after the training; and adding data defining the new architecture and the final measure of fitness for the neural network having the new architecture to the population data.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.