An experimental analysis of Noise-Contrastive Estimation: the noise distribution matters

EACL 2017 Matthieu LabeauAlex Allauzenre

Noise Contrastive Estimation (NCE) is a learning procedure that is regularly used to train neural language models, since it avoids the computational bottleneck caused by the output softmax. In this paper, we attempt to explain some of the weaknesses of this objective function, and to draw directions for further developments... (read more)

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