2018
A Boo(n) for Evaluating Architecture Performance
ICML 2018oral
We point out important problems with the common practice of using the best single model performance for comparing deep learning architectures, and we propose a method that corrects these flaws. Each time a model is trained, one gets a different result due to random factors in the training process, w…