|
| | | | |
| | | |
| Stat |
Members: 3645
Articles: 2'500'096
Articles rated: 2609
19 April 2024 |
|
| | | | |
|
Article overview
| |
|
|
Neural Machine Translation with Gumbel-Greedy Decoding | | Jiatao Gu
; Daniel Jiwoong Im
; Victor O.K. Li
; | | Date: |
23 Jun 2017 | | Abstract: | Previous neural machine translation models used some heuristic search
algorithms (e.g., beam search) in order to avoid solving the maximum a
posteriori problem over translation sentences at test time. In this paper, we
propose the Gumbel-Greedy Decoding which trains a generative network to predict
translation under a trained model. We solve such a problem using the
Gumbel-Softmax reparameterization, which makes our generative network
differentiable and trainable through standard stochastic gradient methods. We
empirically demonstrate that our proposed model is effective for generating
sequences of discrete words. | | Source: | arXiv, 1706.7518 | | Services: | Forum | Review | PDF | Favorites | |
|
|
No review found.
Did you like this article?
Note: answers to reviews or questions about the article must be posted in the forum section.
Authors are not allowed to review their own article. They can use the forum section.
browser Mozilla/5.0 AppleWebKit/537.36 (KHTML, like Gecko; compatible; ClaudeBot/1.0; +claudebot@anthropic.com)
|
| |
|
|
|
|
News, job offers and information for researchers and scientists:
| |
REGISTER