RBFleX-NAS : Training-Free Neural Architecture Search Using Radial Basis Function Kernel and Hyperparameter Detection

Training-Free Neural Architecture Search (NAS) Using Radial Basis Function (RBF) Kernel

Demo

Creator Info

Tomomasa Yamasaki

Singapore University of Technology and Design (Sep 2021 intake)

  

Download the paper

RBFleX-NAS: Training-Free Neural Architecture Search Using Radial Basis Function Kernel and Hyperparameter Detection
Tomomasa Yamasaki; Zhehui Wang; Tao Luo; Niangjun Chen; Bo Wang
IEEE Transactions on Neural Networks and Learning Systems (TNNLS)

How to run RBFleX-NAS

Jump to https://github.com/tomomasayamasaki/RBFleX-NAS.git

Citing RBFleX-NAS

If you use RBFleX, please cite the following paper:

@ARTICLE{10959729,
  author={Yamasaki, Tomomasa and Wang, Zhehui and Luo, Tao and Chen, Niangjun and Wang, Bo},
  journal={IEEE Transactions on Neural Networks and Learning Systems}, 
  title={RBFleX-NAS: Training-Free Neural Architecture Search Using Radial Basis Function Kernel and Hyperparameter Detection}, 
  year={2025},
  volume={36},
  number={6},
  pages={10057-10071},
  keywords={Accuracy;Training;Vectors;Kernel;Feature extraction;Correlation;Computer architecture;Benchmark testing;Predictive models;Neural architecture search;Activation;neural architecture search (NAS);radial basis function (RBF);training-free},
  doi={10.1109/TNNLS.2025.3552693}}

Licence

MIT Licence