MixMAS: A Framework for Sampling-Based Mixer Architecture Search for Multimodal Fusion and Learning

Bibliografski detalji

Izdano u:	arXiv.org (Dec 24, 2024), p. n/a
Glavni autor:	Chergui, Abdelmadjid
Daljnji autori:	Bezirganyan, Grigor, Sellami, Sana, Berti-Équille, Laure, Fournier, Sébastien
Izdano:	Cornell University Library, arXiv.org
Teme:	Performance measurement Data integration Deep learning Machine learning Data search Sampling
Online pristup:	Citation/Abstract Full text outside of ProQuest
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