Accepted to ICANN 2019

The following paper has been accepted to the 28th International Conference on Artificial Neural Networks (ICANN 2019) as an oral presentation. In this paper, we propose a method to control the architecture complexity by adding the penalty term in the dynamic optimization method of neural network structures [Shirakawa et al. 2018].

Shota Saito and Shinichi Shirakawa: Controlling Model Complexity in Probabilistic Model-Based Dynamic Optimization of Neural Network Structures, 28th International Conference on Artificial Neural Networks (ICANN 2019) (Accepted as oral presentation) [arXiv]