March 10, 2022, 2:11 a.m. | Zimian Wei, Hengyue Pan, Xin Niu, Peijie Dong, Dongsheng Li

cs.LG updates on arXiv.org arxiv.org

Neural architecture search (NAS) has gained significant attention for
automatic network design in recent years. Previous NAS methods suffer from
limited search spaces, which may lead to sub-optimal results. In this paper, we
propose UENAS, an evolution-based NAS framework with a broader search space
that supports optimizing network architectures, pruning strategies, and
hyperparameters simultaneously. To alleviate the huge search cost caused by the
expanded search space, three strategies are adopted: First, an adaptive pruning
strategy that iteratively trims the average …

arxiv evolution framework nas

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