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Improving Neural Language Models with Weight Norm Initialization and Regularization
AbstractEmbedding and projection matrices are commonly used in neural language models (NLM) as well as in other sequence processing networks that operate on large vocabularies. We examine such matrices in …...
Experimenting with Power Divergences for Language Modeling
AbstractNeural language models are usually trained using Maximum-Likelihood Estimation (MLE). The corresponding objective function for MLE is derived from the Kullback-Leibler (KL) divergence between the empirical probability distribution representing the …...