Multiagent Reinforcement Learning for Hyperparameter Optimization of Convolutional Neural Networks

Nowadays, deep convolutional neural networks (DCNNs) play a significant role in many application domains, such as computer vision, medical imaging, and image processing. Nonetheless, designing a DCNN, able to defeat the state of the art, is a manual, challenging, and time-consuming task, due to the...

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Bibliographic Details
Published in:	IEEE transactions on computer-aided design of integrated circuits and systems Vol. 41; no. 4; pp. 1034 - 1047
Main Authors:	Iranfar, Arman, Zapater, Marina, Atienza, David
Format:	Journal Article
Language:	English
Published:	New York IEEE 01.04.2022 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Accuracy Artificial neural networks Computer architecture Computer vision Convolution Convolutional neural network (CNN) hyperparameter optimization Image classification Image processing Image segmentation Kernel Learning Medical imaging Multiagent systems neural architecture search (NAS) Neural networks Optimization Reinforcement learning reinforcement Learning (RL) Search problems Subspaces Training
ISSN:	0278-0070, 1937-4151
Online Access:	Get full text
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