Sequence Tutor: Conservative Fine-Tuning of Sequence Generation Models with KL-control

ICML, pp. 1645-1654, 2017.

Cited by: 70|Bibtex|Views139
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Other Links: dblp.uni-trier.de|academic.microsoft.com|arxiv.org

Abstract:

This paper proposes a general method for improving the structure and quality of sequences generated by a recurrent neural network (RNN), while maintaining information originally learned from data, as well as sample diversity. An RNN is first pre-trained on data using maximum likelihood estimation (MLE), and the probability distribution ov...More

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