doi:10.1109/CEC.2010.5585956",
notes = "WCCI 2010. Also known as \cite{5585956}",
}
Created by W.Langdon from gp-bibliography.bib Revision:1.2031
@InProceedings{Kattan:2010:cec,
author = "Ahmed Kattan and Riccardo Poli",
title = "Evolutionary synthesis of lossless compression
algorithms with {GP-zip3}",
booktitle = "IEEE Congress on Evolutionary Computation (CEC 2010)",
year = "2010",
address = "Barcelona, Spain",
month = "18-23 " # jul,
publisher = "IEEE Press",
keywords = "genetic algorithms, genetic programming",
isbn13 = "978-1-4244-6910-9",
abstract = "Here we propose GP-zip3, a system which uses Genetic
Programming to find optimal ways to combine standard
compression algorithms for the purpose of compressing
files and archives. GP-zip3 evolves programs with
multiple components. One component analyses statistical
features extracted from the raw data to be compressed
(seen as a sequence of 8-bit integers) to divide the
data into blocks. These blocks are then projected onto
a two-dimensional Euclidean space via two further
(evolved) program components. K-means clustering is
applied to group similar data blocks. Each cluster is
then labelled with the optimal compression algorithm
for its member blocks. Once a program that achieves
good compression is evolved, it can be used on unseen
data without the requirement for any further evolution.
GP-zip3 is similar to its predecessor, GP-zip2. Both
systems outperform a variety of standard compression
algorithms and are faster than other evolutionary
compression techniques. However, GP-zip2 was still
substantially slower than off-the-shelf algorithms.
GP-zip3 alleviates this problem by using a novel
fitness evaluation strategy. More specifically, GP-zip3
evolves and then uses decision trees to predict the
performance of GP individuals without requiring them to
be used to compress the training data. As shown in a
variety of experiments, this speeds up evolution in
GP-zip3 considerably over GP-zip2 while achieving
similar compression results, thereby significantly
broadening the scope of application of the approach.",
doi = "doi:10.1109/CEC.2010.5585956",
notes = "WCCI 2010. Also known as \cite{5585956}",
}
Genetic Programming entries for Ahmed Kattan Riccardo Poli