Building Optimal Neural Architectures using Interpretable Knowledge

arXiv:2403.13293v1 Announce Type: cross
Abstract: Neural Architecture Search is a costly practice. The fact that a search space can span a vast number of design choices with each architecture evaluation taking nontrivial overhead makes it hard for an algorithm to sufficiently explore candidate networks. In this paper, we propose AutoBuild, a scheme which learns to align the latent embeddings of operations and architecture modules with the ground-truth performance of the architectures they appear in. By doing so, AutoBuild is capable …

architectures arxiv building cs.ai cs.cv cs.lg knowledge neural architectures type