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The Inside-Outside Algorithm is a dynamic programming approach used primarily for training probabilistic context-free grammars, allowing for the computation of the probabilities of subtrees in a parse tree. It is essential for tasks in natural language processing such as syntactic parsing and is a specific instance of the Expectation-Maximization algorithm for hidden variables in probabilistic models.
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