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PRAIg '16 / +pics

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AERFAI Summer School on Deep Learning

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Alicante July 5-6, 2017

10th international workshop on Machine Learning and Music

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Barcelona: 16th October 2017

Publications:

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  1. Rico-Juan, J. R.; Calera-Rubio, J.; Carrasco, R. C.
    "Smoothing and compression with stochastic k-testable tree languages"
    Pattern Recognition, vol. 38, pp. 1420--1430 (2005)
    : bibtex
    Abstract:

    In this paper, we describe a generalization for tree stochastic languages of k-gram models. These models are based on the k-testable class,a subclass of the languages recognizable by ascending tree auntomata. One of the advantages of this approchis that the probabilistic model can be updated in an incremental fashion. Another feature is that backing-off schemes can be defined. As an illustration of their applicability, they have been used to compress tree data files at a better rate than string-based methods.

@article {
 author = "Rico-Juan, J. R.; Calera-Rubio, J.; Carrasco, R. C.",
 title  = "Smoothing and compression with stochastic k-testable tree languages",
 journal = "Pattern Recognition",
 number = "9",
 pages = "1420--1430",
 volume = "38",
 year = "2005"
}
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