Efficient Hyperparameter Optimization Using Deep Q-Network and BRKGA-Reference-Cited by-同舟云学术

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Efficient Hyperparameter Optimization Using Deep Q-Network and BRKGA

Published:2024-06-30 Issue: Volume:13 Page:1-8
ISSN:
Container-title:2024 IEEE Congress on Evolutionary Computation (CEC)
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Author:

Kobayashi Kosei¹,Aritsugi Masayoshi²,González Pedro Henrique³,Mendonça Israel¹

Affiliation:

1. Graduate School of Science and Technology, Kumamoto University,Kumamoto,Japan

2. Faculty of Advanced Science and Technology, Kumamoto University,Kumamoto,Japan

3. System Engineering and Computer Science Program, Federal University of Rio de Janeiro,Rio de Janeiro,Brazil

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10609966/10611750/10612117.pdf?arnumber=10612117

Reference30 articles.

1. Grid Search-Based Hyperparameter Tuning and Classification of Microarray Cancer Data

2. K-Nearest Neighbors and Grid Search CV Based Real Time Fault Monitoring System for Industries

3. Random search for hyper-parameter optimization;Bergstra;Journal of Machine Learning Research,2012

4. Practical bayesian optimization of machine learning algorithms;Snoek,2012

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