Mathilde Pellerin

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Learning the parameters of the edit distance has been increasingly studied during the past few years to improve the assessment of similarities between struc-tured data, such as strings, trees or graphs. Often based on the optimization of the likelihood of pairs of data, the learned models usually take the form of prob-abilistic state machines, such as(More)
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