Target Conditioned Sampling: Optimizing Data Selection for Multilingual Neural Machine Translation (P19-1)
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| Challenge: | Existing studies show that training on a single related language is more effective than using all data. |
| Approach: | They propose an efficient algorithm that first samples a target sentence, and then conditionally samples its source sentence. |
| Outcome: | The proposed algorithm brings significant gains on three of four languages with minimal training overhead. |
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