Self Normalization

Several techniques have recently been pro- posed for training “self-normalized” discrimi- native models. These attempt to find parameter settings for which unnormalized model scores approximate the true label probability. How- …...

Training neural network language mod- els over large vocabularies is computa- tionally costly compared to count-based models such as Kneser-Ney. We present a systematic comparison of neural strate- gies to …...