A Modern Take on the Bias-Variance Tradeoff in Neural Networks
arXiv: Learning, Volume abs/1810.08591, 2018.
We revisit the bias-variance tradeoff for neural networks in light of modern empirical findings. The traditional bias-variance tradeoff in machine learning suggests that as model complexity grows, variance increases. Classical bounds in statistical learning theory point to the number of parameters in a model as a measure of model complexi...More