论文标题
分享或不共享：对体重分享的全面评估
To Share or Not To Share: A Comprehensive Appraisal of Weight-Sharing
论文作者
论文摘要
重量共享（WS）最近成为一种范式，以加速自动搜索有效的神经体系结构，这是一种称为神经体系结构搜索（NAS）的过程。尽管非常吸引人，但这个框架并非没有缺点，并且已经开始在小型手工制作的基准测试中质疑其功能。在本文中，我们利用\ nasbench数据集来挑战WS在代表性搜索空间上的效率。通过将SOTA WS方法与普通的随机搜索进行比较，我们表明，尽管使用权重分担和独立的评估之间的评估之间存在良好的相关性，但WS很少对NAS显着有助于NAS。特别是我们强调了搜索空间本身对收益的影响。
Weight-sharing (WS) has recently emerged as a paradigm to accelerate the automated search for efficient neural architectures, a process dubbed Neural Architecture Search (NAS). Although very appealing, this framework is not without drawbacks and several works have started to question its capabilities on small hand-crafted benchmarks. In this paper, we take advantage of the \nasbench dataset to challenge the efficiency of WS on a representative search space. By comparing a SOTA WS approach to a plain random search we show that, despite decent correlations between evaluations using weight-sharing and standalone ones, WS is only rarely significantly helpful to NAS. In particular we highlight the impact of the search space itself on the benefits.
