Gabriele Barbieri

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Many systems use Markov models to generate finite-length sequences that imitate a given style. These systems often need to enforce specific control constraints on the sequences to generate. Unfortunately , control constraints are not compatible with Markov models, as they induce long-range dependencies that violate the Markov hypothesis of limited memory.(More)
We address the issue of generating texts in the style of an existing author, that also satisfy structural constraints imposed by the genre of the text. We focus on song lyrics, for which structural constraints are well-defined: rhyme and meter. Although Markov processes are known to be suitable for representing style, they are difficult to control in order(More)
Feature generation has been proposed recently to generate feature sets automatically, as opposed to human-designed feature sets. This technique has shown promising results in many areas of supervised classification, in particular in the audio domain. However, feature generation is usually performed blindly, with genetic algorithms. As a result search(More)
It seems necessary to detect a broken bike rooted at a station in near realtime as the number of bikes within bikeshare systems has reached more than a million in 2015. Indeed, a bike that cannot be moved is not cost effective in terms of number of trips. This brings frustration to users who were expecting to find a bike at that station without knowing that(More)
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