Removing nodes from machine-trained network based on introduction of probabilistic noise during training
US11900238B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Feb 3, 2020 |
| Grant date | Feb 13, 2024 |
| Priority date | — |
| Expiry date | Jan 22, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N7/01
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Some embodiments provide a method for reducing complexity of a machine-trained (MT) network that receives input data and computes output data for each input data. The MT network includes multiple computation nodes that (i) generate output values and (ii) use output values of other computation nodes as input values. During training of the MT network, the method introduces probabilistic noise to the output values of a set of the computation nodes. the method determines a subset of the computation nodes for which the introduction of the probabilistic noise to the output value does not affect the computed output data for the network. The method removes the subset of computation nodes from the trained MT network.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.