Maximum Relevance Minimum Redundancy Dropout with Informative Kernel Determinantal Point Process.

Saffari, Mohsen; Khodayar, Mahdi; Ebrahimi Saadabadi, Mohammad Saeed; Sequeira, Ana F; Cardoso, Jaime S

Saffari, Mohsen; Khodayar, Mahdi; Ebrahimi Saadabadi, Mohammad Saeed; Sequeira, Ana F; Cardoso, Jaime S.

Afiliación

Saffari M; INESC TEC and Faculty of Engineering, University of Porto, 4200-465 Porto, Portugal.
Khodayar M; Department of Computer Science, University of Tulsa, Tulsa, OK 74104, USA.
Ebrahimi Saadabadi MS; Faculty of Electrical Engineering, K. N. Toosi University of Technology, Tehran 16315-1355, Iran.
Sequeira AF; INESC TEC, 4200-465 Porto, Portugal.
Cardoso JS; INESC TEC and Faculty of Engineering, University of Porto, 4200-465 Porto, Portugal.

Sensors (Basel) ; 21(5)2021 Mar 06.

Article en En | MEDLINE | ID: mdl-33800810

Palabras clave

deep learning; determinantal point process; dropout; image classification; information theory; regularization methods

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Sensors (Basel) Año: 2021 Tipo del documento: Article País de afiliación: Portugal Pais de publicación: Suiza

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