Patent · US Active

Training machine learning models using task selection policies to increase learning progress

US10936949B2 · kind B2 · utility

0Cited by
1References
22Claims
0Family size

Assignee

Inventors

Key dates

Filing dateJul 10, 2019
Grant dateMar 2, 2021
Priority date
Expiry dateJul 10, 2039

Classification

  • Technology area (CPC G)Physics
  • CPC primaryG06N3/0985
  • WIPO fieldComputer technology
  • WIPO sectorElectrical engineering

Abstract

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for training a machine learning model. In one aspect, a method includes receiving training data for training the machine learning model on a plurality of tasks, where each task includes multiple batches of training data. A task is selected in accordance with a current task selection policy. A batch of training data is selected from the selected task. The machine learning model is trained on the selected batch of training data to determine updated values of the model parameters. A learning progress measure that represents a progress of the training of the machine learning model as a result of training the machine learning model on the selected batch of training data is determined. The current task selection policy is updated using the learning progress measure.

Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.