Neural architecture search promises to speed up the process of finding neural network architectures that will yield good models for a given dataset. Neural architecture search is the task of ...

Deep neural networks have a huge advantage: They replace “feature engineering”—a difficult and arduous part of the classic machine learning cycle—with an end-to-end process that automatically learns ...

Neural architecture search (NAS) and machine learning optimisation represent rapidly advancing fields that are reshaping the way modern systems are designed and deployed. By automating the process of ...

NAS methods can generally be classified based on tailored designs from the following aspects: search space, search strategy, and evaluation strategy. In particular, search space can be further ...