Deep Neural network Hyper-parameter Tuning with Genetic Algorithm

Hello there. I’m thinking of using Genetic Algorithm to tune Hyper-parameters of Neural Networks.

Apart form this paper and this blog blog, I don’t find anything that relates with the topic. However there are many GA libraries such as PyGAD etc, but they only apply GA onto weights to fine tune the model instead of finding the best hyper-parameters.

By any chance, anyone here tried anything like this before, as in using GA to find the best hyperparameter in a Tensorflow/Keras Model? Mind share your thoughts?


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