Snapshot Ensembles: Train 1, get M for freeEnsembles of neural networks are known to be much more robust and accurate than individual networks. However, training multiple deep networks for model averaging is computationally expensive. In this paper, we propose a method to obtain the seemingly contradictory goal of ensembling multiple neural networks at no additional training cost. We achieve this goal by training a single neural network, c
https://kaigi.org/jsai/webprogram/2017/paper-445.html
