An Investigation With TuNAS. Efficient Neural Architecture Search methods based on weight sharing have shown good promise in democratizing Neural Architecture Search for computer vision models. There is, however, an ongoing debate whether these efficient methods are significantly better than random search.
Aug 13, 2020 · Here we perform a thorough comparison between efficient and random search methods on a family of progressively larger and more challenging search spaces.
TuNAS uses a reinforcement learning algorithm with weight sharing to perform architecture searches. Our al- gorithm is similar to ProxylessNAS [5] and ENAS [28 ...
A thorough comparison between efficient and random search methods on a family of progressively larger and more challenging search spaces for image ...
Despite recent advances such as TuNAS Bender et al. [2020] and DARTS Liu et al. [2018], these techniques can be an order of magnitude slower and less accurate ...
Can Weight Sharing Outperform Random Architecture Search? An ...
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We find that (i) TuNAS continues to find high-quality architectures, and (ii) the gap between TuNAS and random search increases sig- nificantly on these new ...
Aug 15, 2020 · Can Weight Sharing Outperform Random Architecture Search? An Investigation with TuNAS" "We demonstrate that when weight sharing is ...
The study reveals that, for some spaces, NAS can benefit from weight sharing to find a good-performing architecture, while for others, it hardly works. We then ...
Can weight sharing outperform random architecture search¿ an investigation with tunas. In Proceedings of the IEEE/CVF Conference on Computer Vision and ...
Aug 13, 2020 · TuNAS uses a reinforcement learning algorithm with weight sharing to perform architecture searches. Our al- gorithm is similar to ProxylessNAS ...