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Lossy compression of unordered rooted trees

Romain Azaïs 1, 2 Jean-Baptiste Durand 3 Christophe Godin 4, 5
1 BIGS - Biology, genetics and statistics
Inria Nancy - Grand Est, IECL - Institut Élie Cartan de Lorraine
3 MISTIS - Modelling and Inference of Complex and Structured Stochastic Systems
Grenoble INP - Institut polytechnique de Grenoble - Grenoble Institute of Technology, LJK - Laboratoire Jean Kuntzmann, Inria Grenoble - Rhône-Alpes
4 VIRTUAL PLANTS - Modeling plant morphogenesis at different scales, from genes to phenotype
CRISAM - Inria Sophia Antipolis - Méditerranée , INRA - Institut National de la Recherche Agronomique, UMR AGAP - Amélioration génétique et adaptation des plantes méditerranéennes et tropicales
Abstract : A classical compression method for trees is to represent them by directed acyclic graphs. This approach exploits subtree repeats in the structure and is ecient only for trees with a high level of redundancy. The class of self-nested trees presents remarkable compression properties because of the systematic repetition of subtrees. In this paper, we introduce a lossy compression method that consists in computing the reduction of a self-nested structure that closely approximates the initial data. We compare two versions of our algorithm and a competitive approach of the literature on a simulated dataset.
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Preprints, Working Papers, ...
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Contributor : Romain Azaïs <>
Submitted on : Tuesday, December 1, 2015 - 11:32:55 AM
Last modification on : Wednesday, March 24, 2021 - 11:52:02 AM


  • HAL Id : hal-01236088, version 1


Romain Azaïs, Jean-Baptiste Durand, Christophe Godin. Lossy compression of unordered rooted trees. 2015. ⟨hal-01236088⟩



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