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Resilience Under Attack: Benchmarking Optimizers Against Poisoning in Federated Learning for Image Classification Using Cnn

AuthID
P-01A-70A

Author(s)

Biadgligne, Y

Baghoussi, Y

Li, K

Jorge, A

Editor(es)

Rojas,I;Joya,G;Català,A

Tipo de Documento

Proceedings Paper

Year published

2025

Publicado

in Advances in Computational Intelligence - 18th International Work-Conference on Artificial Neural Networks, IWANN 2025, A Coruña, Spain, June 16-18, 2025, Proceedings, Part I in Lecture Notes in Computer Science, ISSN: 16113349; 03029743

Volume: 16008, Páginas: 27-40

Conference

18Th International Work-Conference on Artificial Neural Networks, Iwann 2025, Location: A Coruña

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Scopus^®

Dblp^®/pt/publications/view/1383434

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Fontes

Publication Identifiers

DOI: 10.1007/978-3-032-02725-2_3

DBLP: conf/iwann/BiadgligneBLJ25

SCOPUS: 2-s2.0-105019643013

Source Identifiers

ISSN: 16113349; 03029743

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Resilience Under Attack: Benchmarking Optimizers Against Poisoning in Federated Learning for Image Classification Using Cnn

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