Tuning Deep Neural Network’s Hyperparameters Constrained to Deployability on Tiny Systems-Reference-Cited by-同舟云学术

Tuning Deep Neural Network’s Hyperparameters Constrained to Deployability on Tiny Systems

Published:2020 Issue: Volume: Page:92-103
ISSN:0302-9743
Container-title:Artificial Neural Networks and Machine Learning – ICANN 2020
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Author:

Perego Riccardo^ORCID,Candelieri Antonio^ORCID,Archetti Francesco^ORCID,Pau Danilo^ORCID

Publisher

Springer International Publishing

Link

https://link.springer.com/content/pdf/10.1007/978-3-030-61616-8_8

Reference24 articles.

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3. Suganuma, M., Shirakawa, S., Nagao, T.: A genetic programming approach to designing convolutional neural network architectures. In: Genetic and Evolutionary Computation Conference (2017)

4. Bianco, S., Buzzelli, M., Ciocca, G., Schettini, R.: Neural architecture search for image saliency fusion. Inf. Fusion 57, 89–101 (2020)

5. Liu, H., Simonyan, K., Vinyals, O., Fernando, C., Kavukcuoglu, K.: Hierarchical representations for efficient architecture search. In: International Conference on Learning Representations (2018b)

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