E2E-FS: An End-to-End Feature Selection Method for Neural Networks

Medientyp: E-Artikel
Titel: E2E-FS: An End-to-End Feature Selection Method for Neural Networks
Beteiligte: Cancela, Brais; Bolon-Canedo, Veronica; Alonso-Betanzos, Amparo
Erschienen: Institute of Electrical and Electronics Engineers (IEEE), 2022
Erschienen in: IEEE Transactions on Pattern Analysis and Machine Intelligence
Sprache: Nicht zu entscheiden
DOI: 10.1109/tpami.2022.3228824
ISSN: 0162-8828; 2160-9292; 1939-3539
Schlagwörter: Applied Mathematics ; Artificial Intelligence ; Computational Theory and Mathematics ; Computer Vision and Pattern Recognition ; Software
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