Neural Architecture Search
Neural Architecture Search
**Neural Architecture Search (NAS)** learns a modular architecture which can be transferred from a small dataset to a large dataset. The method does this by reducing the problem of learning best convolutional architectures to the problem of learning a small convolutional cell. The cell can then be stacked in series to handle larger images and more complex datasets.

Note that this refers to the original method referred to as NAS - there is also a broader category of methods called "neural architecture search".
Learning Transferable Architectures for Scalable Image Recognition
https://paperswithcode.com/paper/learning-transferable-architectures-for
Learning Transferable Architectures for Scalable Image Recognition