Data compression techniques for machine learning models
US12061671B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Oct 7, 2021 |
| Grant date | Aug 13, 2024 |
| Priority date | — |
| Expiry date | Sep 30, 2042 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N5/01
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
In some aspects, techniques for creating representative and informative training datasets for the training of machine-learning models are provided. For example, a risk assessment system can receive a risk assessment query for a target entity. The risk assessment system can compute an output risk indicator for the target entity by applying a machine learning model to values of informative attributes associated with the target entity. The machine learning model may be trained using training samples selected from a representative and informative (RAI) dataset. The RAI dataset can be created by determining the informative attributes based on attributes used by a set of models and further extracting representative data records from an initial training dataset based on the determined informative attributes. The risk assessment system can transmit a responsive message including the output risk indicator for use in controlling access of the target entity to an interactive computing environment.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.