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courses:rg:2011:deciphering_foreign_language [2012/01/07 14:05] tran |
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If we use traditional EM, every time we update < | If we use traditional EM, every time we update < | ||
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+ | __**Practical questions: | ||
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+ | **Some other notes related to this paper:** | ||
+ | - Generative story: The generative process that generates data given some hidden variables. | ||
+ | - [[http:// | ||
+ | - Gibbs sampling: | ||
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+ | Why did they experiment with Temporal expression corpus? This corpus has relatively small word types, it makes easier to compare Iterative EM with full EM. | ||
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+ | ==== Section 3 ==== | ||
+ | Not many details of this section was presented, however, there are few discussion around this. | ||
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+ | How to choose the best translation? | ||
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+ | Given another text (which is not in training data), how to translate it? Use MLE to find the best translation from the model. | ||
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+ | ==== Conclusion ==== | ||
+ | This is an interesting paper, however, there is a lot of maths behind. | ||
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