mlsanityData to 7 Oct 2026

FOX-NAS: Fast, On-device and Explainable Neural Architecture Search

arXiv 2108.08189 ↗First posted 14 Aug 2021cs.LG cs.CVcited by 7

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Abstract (arXiv)

Neural architecture search can discover neural networks with good performance, and One-Shot approaches are prevalent. One-Shot approaches typically require a supernet with weight sharing and predictors that predict the performance of architecture. However, the previous methods take much time to generate performance predictors thus are inefficient. To this end, we propose FOX-NAS that consists of fast and explainable predictors based on simulated annealing and multivariate regression. Our method is quantization-friendly and can be efficiently deployed to the edge. The experiments on different hardware show that FOX-NAS models outperform some other popular neural network architectures. For example, FOX-NAS matches MobileNetV2 and EfficientNet-Lite0 accuracy with 240% and 40% less latency on the edge CPU. FOX-NAS is the 3rd place winner of the 2020 Low-Power Computer Vision Challenge (LPCVC), DSP classification track. See all evaluation results at https://lpcv.ai/competitions/2020. Search code and pre-trained models are released at https://github.com/great8nctu/FOX-NAS.

Key facts. Cited by 7 papers in the map (data through 7 Oct 2026). Builds on 28 of its 33 references that are in the map. First posted on arXiv 14 Aug 2021.

Builds on

28 of 33 references.

References · 28

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16 more
  1. 2019Searching for MobileNetV3cited by 1,984
  2. 2018DARTS: Differentiable Architecture Searchcited by 1,782
  3. 2017Quantization and Training of Neural Networks for Efficient Integer-Arithmetic-Only Inferencecited by 1,548
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  13. 2017Progressive Neural Architecture Searchcited by 483
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  16. 2020FBNetV3: Joint Architecture-Recipe Search using Predictor Pretrainingcited by 35

Built on by

Cited by year

Citing papers per year: 2021: 1; 2022: 1; 2023: 4; 2024: 1.

7 papers.

  1. 2023AdaptiveNet: Post-deployment Neural Architecture Adaptation for Diverse Edge Environmentscited by 19
  2. 2021MAPLE: Microprocessor A Priori for Latency Estimationcited by 5
  3. 2023Efficient Automation of Neural Network Design: A Survey on Differentiable Neural Architecture Searchcited by 5
  4. 2022Design Automation for Fast, Lightweight, and Effective Deep Learning Models: A Surveycited by 1
  5. 2023Generative Model for Models: Rapid DNN Customization for Diverse Tasks and Resource Constraintscited by 0
  6. 2023Explainable Graph Neural Architecture Search via Monte-Carlo Tree Search (Full version)cited by 0
  7. 2024Task-Oriented Real-time Visual Inference for IoVT Systems: A Co-design Framework of Neural Networks and Edge Deploymentcited by 0