Evaluating Neural Architecture Search Methods on Diverse and Unseen Datasets

Neural Architecture Search (NAS) methods should be able to find optimal neural network architectures for diverse datasets, not just common benchmarks. This work introduces eight new datasets to challenge NAS approaches and evaluate their generalization capabilities.