mlsanityData to 7 Oct 2026

Trends in Neural Architecture Search: Towards the Acceleration of Search

arXiv 2108.08474 ↗First posted 19 Aug 2021cs.LGcited by 3

Not on the map. Why?

Abstract (arXiv)

In modern deep learning research, finding optimal (or near optimal) neural network models is one of major research directions and it is widely studied in many applications. In this paper, the main research trends of neural architecture search (NAS) are classified as neuro-evolutionary algorithms, reinforcement learning based algorithms, and one-shot architecture search approaches. Furthermore, each research trend is introduced and finally all the major three trends are compared. Lastly, the future research directions of NAS research trends are discussed.

Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). Builds on 12 of its 14 references that are in the map. First posted on arXiv 19 Aug 2021.

Builds on

12 of 14 references.

References · 12

  1. 2015U-Net: Convolutional Networks for Biomedical Image Segmentationcited by 19,604
  2. 2018DARTS: Differentiable Architecture Searchcited by 1,782
  3. 2016Neural Architecture Search with Reinforcement Learningcited by 1,489
  4. 2017Learning Transferable Architectures for Scalable Image Recognitioncited by 1,097
  5. 2016HyperNetworkscited by 1,003
  6. 2018Regularized Evolution for Image Classifier Architecture Searchcited by 902
  7. 2018Efficient Neural Architecture Search via Parameter Sharingcited by 831
  8. 2016Designing Neural Network Architectures using Reinforcement Learningcited by 277
  9. 2017SMASH: One-Shot Model Architecture Search through HyperNetworkscited by 200
  10. 2018Graph HyperNetworks for Neural Architecture Searchcited by 131
  11. 2020Communication-Efficient and Distributed Learning Over Wireless Networks: Principles and Applicationscited by 62
  12. 2020Auction-based Charging Scheduling with Deep Learning Framework for Multi-Drone Networkscited by 12

Built on by

Cited by year

Citing papers per year: 2022: 2; 2023: 0; 2024: 0; 2025: 1.

3 papers.

  1. 2022Two-stage architectural fine-tuning with neural architecture search using early-stopping in image classificationcited by 2
  2. 2022Search Space Adaptation for Differentiable Neural Architecture Search in Image Classificationcited by 0
  3. 2025Quantum Circuit Structure Optimization for Quantum Reinforcement Learningcited by 0