Learning Policies for Neural Network Architecture Optimization Using Reinforcement Learning

Learning Policies for Neural Network Architecture Optimization Using Reinforcement Learning

Deep learning systems tend to be very sensitive to the specific network architecture both in terms of learning ability and performance of the learned solution. This, together with the difficulty of tuning neural network architectures leads to a need for automatic network optimization. Previous work...

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Bibliographic Details
Main Authors:	Raghav Vadhera, Manfred Huber
Format:	Article
Language:	English
Published:	LibraryPress@UF 2023-05-01
Series:	Proceedings of the International Florida Artificial Intelligence Research Society Conference
Online Access:	https://journals.flvc.org/FLAIRS/article/view/133380
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