Massive Exploration of Neural Machine Translation Architectures Massive Exploration of Neural Machine Translation Architectures
Paper summary Investigates different parameter choices for encoder-decoder NMT models. They find that LSTM is better than GRU, 2 bidirectional layers is enough, additive attention is the best, and a well-tuned beam search is important. They achieve good results on the WMT15 English->German task and release the code. https://i.imgur.com/GaAsTvE.png
arxiv.org
scholar.google.com
Massive Exploration of Neural Machine Translation Architectures
Britz, Denny and Goldie, Anna and Luong, Minh-Thang and Le, Quoc V.
arXiv e-Print archive - 2017 via Local Bibsonomy
Keywords: dblp


Summary by Marek Rei 2 months ago
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