Accepted to ICANN 2022

Our paper has been accepted to the 31st International Conference on Artificial Neural Networks (ICANN 2022). This paper proposes an efficient search method for multiple neural architectures with different complexities by using importance sampling.

  • Yuhei Noda, Shota Saito, and Shinichi Shirakawa: Efficient Search of Multiple Neural Architectures with Different Complexities via Importance Sampling, 31st International Conference on Artificial Neural Networks (ICANN 2022), September 6-9 2022 (Accepted). [arXiv]