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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. Serrano, A.; Micó, L.;Oncina, J.
    "Impact of the Initialization in Tree-Based Fast Similarity Search Techniques"
    SIMBAD'11 Proceedings of the First international conference on Similarity-based pattern recognition , ISBN: 978-3-642-24470-4, pp. 163-176, Venecia, Italia (2011)
    : bibtex : pdf
    Abstract:

    Many fast similarity search techniques relies on the use of pivots (specially selected points in the data set). Using these points, specific structures (indexes) are built speeding up the search when queering. Usually, pivot selection techniques are incremental, being the first one randomly chosen. This article explores several techniques to choose the first pivot in a tree-based fast similarity search technique. We provide experimental results showing that an adequate choice of this pivot leads to significant reductions in distance computations and time complexity. Moreover, most pivot tree-based indexes emphasizes in building balanced trees.We provide experimentally and theoretical support that very unbalanced trees can be a better choice than balanced ones.

@inproceedings {
 author = "Serrano, A.; Micó, L.;Oncina, J.",
 title  = "Impact of the Initialization in Tree-Based Fast Similarity Search Techniques",
 address = "Venecia, Italia",
 booktitle = "SIMBAD'11 Proceedings of the First international conference on Similarity-based pattern recognition ",
 editor = "Pelillo, M.; Hancock, E.R.",
 isbn = "978-3-642-24470-4",
 pages = "163-176",
 publisher = "Springer",
 year = "2011"
}
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