Anytime Neural Architecture Search on Tabular Data

arXiv:2403.10318v1 Announce Type: new
Abstract: The increasing demand for tabular data analysis calls for transitioning from manual architecture design to Neural Architecture Search (NAS). This transition demands an efficient and responsive anytime NAS approach that is capable of returning current optimal architectures within any given time budget while progressively enhancing architecture quality with increased budget allocation. However, the area of research on Anytime NAS for tabular data remains unexplored. To this end, we introduce ATLAS, the first anytime NAS approach …

abstract analysis architecture architectures arxiv budget cs.lg current data data analysis demand design nas neural architecture search quality responsive search tabular tabular data transition type