AME: Attention and Memory Enhancement in Hyper-Parameter Optimization

Training Deep Neural Networks (DNNs) is inherently subject to sensitive hyper-parameters and untimely feedbacks of performance evaluation. To solve these two difficulties, an efficient parallel hyper-parameter optimization model is proposed under the framework of Deep Reinforcement Learning (DRL). T...

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Veröffentlicht in:	Proceedings (IEEE Computer Society Conference on Computer Vision and Pattern Recognition. Online) S. 480 - 489
Hauptverfasser:	Xu, Nuo, Chang, Jianlong, Nie, Xing, Huo, Chunlei, Xiang, Shiming, Pan, Chunhong
Format:	Tagungsbericht
Sprache:	Englisch
Veröffentlicht:	IEEE 01.06.2022
Schlagworte:	categorization grouping and shape analysis Optimization methods; Recognition: detection Performance evaluation Reinforcement learning retrieval; Segmentation Search problems Semantics Training Transformers Visualization
ISSN:	1063-6919
Online-Zugang:	Volltext
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