Multi-task learning
id:
multi-task-learning-187-13679058
title:
Multi-task learning
text:
Multi-task learning (MTL) is a subfield of machine learning in which multiple learning tasks are solved at the same time, while exploiting commonalities and differences across tasks. This can result in improved learning efficiency and prediction accuracy for the task-specific models, when compared to training the models separately. Inherently, Multi-task learning is a multi-objective optimization problem having trade-offs between different tasks.
Early versions of MTL were called "hints". In a w
brand slug:
wiki
category slug:
encyclopedia
description:
Solving multiple machine learning tasks at the same time
original url:
https://en.wikipedia.org/wiki/Multi-task_learning
date created:
2004-08-28T23:51:36Z
date modified:
2024-09-08T15:02:46Z
main entity:
{"identifier":"Q6934509","url":"https://www.wikidata.org/entity/Q6934509"}
image:
fields total:
13
integrity:
15