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Data-Driven Mitigation of Adversarial Text Perturbation
We propose Continuous Word2Vec (CW2V), our data-driven method to learn word embeddings that ensures that perturbations of words have embeddings similar to those of the original words.
Enumeration of binary trees compatible with a perfect phylogeny
Here, we investigate enumerative properties of the set of binary ranked and unranked tree shapes that are compatible with a perfect phylogeny, and hence, the binary ranked and unranked tree shapes conditioned on an observed pattern of mutations under the in? nitely-many-sites mutation model.
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