Entropy-Based Filter Selection in CNNs Applied to Text Classification

Registro completo de metadados
MetadadosDescriçãoIdioma
Autor(es): dc.contributorUniversidade Estadual Paulista (Unesp)-
Autor(es): dc.creatorBezerra de Menezes Rodrigues, Rafael [UNESP]-
Autor(es): dc.creatorMarcílio Júnior, Wilson Estécio [UNESP]-
Autor(es): dc.creatorEler, Danilo Medeiros [UNESP]-
Data de aceite: dc.date.accessioned2022-02-22T00:52:22Z-
Data de disponibilização: dc.date.available2022-02-22T00:52:22Z-
Data de envio: dc.date.issued2021-06-25-
Data de envio: dc.date.issued2021-06-25-
Data de envio: dc.date.issued2019-12-31-
Fonte completa do material: dc.identifierhttp://dx.doi.org/10.1007/978-3-030-61377-8_34-
Fonte completa do material: dc.identifierhttp://hdl.handle.net/11449/208080-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/208080-
Descrição: dc.descriptionFilter selection in convolutional neural networks aims at finding the most important filters in a convolutional layer, with the goal of reducing computational costs and needed storage, as well as understanding the networks’ inner workings. In this paper we propose an entropy-based filter selection method that ranks filters based on the mutual information between their activations and the output classes using validation data. Our proposed method outperforms using filters’ absolute weights sum by a large margin, allowing to regain better performance with fewer filters.-
Descrição: dc.descriptionFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)-
Descrição: dc.descriptionSão Paulo State University-UNESP-
Descrição: dc.descriptionSão Paulo State University-UNESP-
Descrição: dc.descriptionFAPESP: #2018/17881-3-
Descrição: dc.descriptionFAPESP: #2018/25755-8-
Formato: dc.format497-510-
Idioma: dc.languageen-
Relação: dc.relationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)-
???dc.source???: dc.sourceScopus-
Palavras-chave: dc.subjectConvolutional neural networks-
Palavras-chave: dc.subjectFilter pruning-
Palavras-chave: dc.subjectMutual information-
Título: dc.titleEntropy-Based Filter Selection in CNNs Applied to Text Classification-
Aparece nas coleções:Repositório Institucional - Unesp

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