FR-NAS: Forward-and-Reverse Graph Predictor for Efficient Neural Architecture Search

arXiv:2404.15622v1 Announce Type: new
Abstract: Neural Architecture Search (NAS) has emerged as a key tool in identifying optimal configurations of deep neural networks tailored to specific tasks. However, training and assessing numerous architectures introduces considerable computational overhead. One method to mitigating this is through performance predictors, which offer a means to estimate the potential of an architecture without exhaustive training. Given that neural architectures fundamentally resemble Directed Acyclic Graphs (DAGs), Graph Neural Networks (GNNs) become an apparent choice for such …

architecture arxiv cs.lg graph nas neural architecture search search type