Questions tagged [neural-architecture-search]

For questions related to the concept of neural (network) architecture search (NAS), which is a way of automating the design (that is, the hyper-parameters) of a neural network. NAS is related to neuroevolution, given that neuroevolution can be used to perform NAS, but neuroevolution is not the only way of performing NAS. For example, reinforcement learning can also be used to perform NAS.

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Which hyper-parameters are considered in neural architecture search?

I want to understand automatic Neural Architecture Search (NAS). I read already multiple papers, but I cannot figure out what the actual search space of NAS is / how are classical hyper-parameters ...
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Can operations like convolution and pooling be discovered with a neural architecture search approach?

From Neural Architecture Search: A Survey, first published in 2018: Moreover, common search spaces are also based on predefined building blocks, such as different kinds of convolutions and ...
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How do I determine the best neural network architecture for a problem with 3 inputs and 12 outputs?

This post continues the topic in the following post: Is it possible to train a neural network with 3 inputs and 12 outputs?. I conducted several experiments in MATLAB and selected those neural ...
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Regional specialization in neural networks (especially for language processing)?

What is the status of the research on regional specialization of the artificial neural networks? Biology knows that such specialization exists in the brain and it is very important for the functioning ...
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Need to determine a ML solution for the given graphical problem

I need to generate a 3D plane given a set of feature inputs. Most inputs are a range of values between 0 and 1 (sigmoidial), except a few. For example a rectangle: ...
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Autoencoder symmetry

I'm building Autoencoder. In the encoding part I use several strided and diluted convolutions per stage of encoding but I'm wondering if I have to construct the decoding part in a symmetric way. My ...