I have read a lot about NAS, but I still do not understand one concept: When setting up a neural network, hyperparameters (such as the learning rate, dropout rate, batch size, filter size, etc.) need to be set up.
In NAS, only the best architecture is decided, e.g. how many layers and neurons. But what about the hyperparameters? Are they randomly chosen?