Inductive Transfer

• Tipo: Capítulo ou Parte de Livro
• Data: 2017

Autores

Ricardo Vilalta (Autor) Outra; Christophe Giraud-Carrier (Autor) Outra; Pavel Brazdil (Autor) FEP; Carlos Soares (Autor) FEUP

Livro

Título: Encyclopedia of Machine Learning and Data Mining

Páginas: 666-671

ISBN: 978-1-4899-7685-7

ISBN Eletrónico: 978-1-4899-7685-7

Outras Informações

ID Authenticus: P-00M-NW6

DOI: 10.1007/978-1-4899-7687-1_138

Abstract (EN): We describe different scenarios where a learning mechanism is capable of acquiring experience on a source task, and subsequently exploit such experience on a target task. The core ideas behind this ability to transfer knowledge from one task to another have been studied in the machine learning literature under different titles and perspectives. Here we describe some of them under the names of inductive transfer, transfer learning, multitask learning, meta-searching, meta-generalization, and domain adaptation.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 7