The cross-entropy loss function is widely used and generally considered the default loss function for text classification.
We introduce HoVer (HOppy VERification), a dataset for many-hop evidence extraction and fact verification.
The exploding cost and time needed for data labeling and model training are bottlenecks for training DNN models on large datasets.
Ranked #2 on Text Classification on Amazon-5
First, we prove that for any estimator, increasing the number of bagged estimators $N$ in the average can only reduce the MSE.