EMAA - Workshop on Empirical Methods for the Analysis of Algorithms
September 9, 2006
Reykjavik, Iceland
Held in conjunction
with the International Conference on
Parallel Problem Solving From Nature (PPSN IX)
Proceedings -
Workshop Description -
Submission -
Dates -
Organising Committee -
Program Committee
Proceedings Luís Paquete,
Marco Chiarandini, Dario Basso (Eds.): Workshop on Empirical Methods for
the Analysis of Algorithms, EMAA 2006, Proceedings. Reykjavik, Iceland,
September 9, 2006. Content
(inclusive of the slides of the four invited talks). BibTeX.
Workshop Description It is
currently acknowledged that randomised decisions in search algorithms,
such as evolutionary algorithms and other metaheuristics, improve the
capability of solving decision and optimization problems. The assessment
of these algorithms through analytical studies is not trivial and often
yields results of scarce importance for practical
applications. Researchers tend therefore to report tables with results
of empirical tests carried out on different problem instances and to
comment on those results.
However, empirical analyses of algorithms require standard methods
to guide in the design of the experiments and to determine whether the
data collected are enough to draw any conclusions. The use of these
empirical methods is not yet widely spread in the field and it is not
yet fully understood which methods are appropriate for different
scenarios of analysis, such as comparison, prediction and generalisation
of algorithm performances.
This workshop aims at intensifying the discussion on empirical
methods for the analysis of search algorithms, ultimately, contributing
to the definition of a standard practice in experimental algorithmics.
Some of the topics are the following:
- application of Experimental Design techniques, such as full or
fractional factorial designs, response-surface methods, etc.;
- statistical inference from computational results through
parametric or non-parametric tests;
- exploratory data analysis;
- generalisation of algorithm complexity from empirical data;
- analysis of run-time/solution-quality distributions;
- definition of instance classes and benchmark problems and analysis
of their representativeness;
- tuning and sensitivity analysis of algorithm parameters;
- impact of different performance measures on the characterisation of
algorithm performance;
- analysis of algorithm performance on stochastic and multiobjective problems;
- influence of confounding factors such as hardware, compilers, data
structures and implementation.
The focus will be on the methodologies, not on the performance of the
algorithms themselves.
Submissions
Authors should prepare their papers in the PPSN format by
following the instructions of LNCS series of Springer. The length of the
paper should not exceed 8 pages. Extended abstracts of post-deadline
important results should be no longer than two pages, including figures
and references.
Accepted works will be presented at the Workshop.
Submissions should be made
electronically, by sending papers or post-deadline abstracts in PDF
format to: Luís Paquete
lpaquete@ualg.pt or to Marco Chiarandini marco@imada.sdu.dk.
Important Dates
- Deadline for paper submissions: 5th June, 2006
- Notifications to authors: 25th June, 2006
- Revised Manuscripts: 30 July, 2006
- Post-deadline abstract submissions: 15th August, 2006
- Post-deadline notifications: 31st August, 2006
- EMAA workshop: 9th September, 2006
Organising Committee
Luís Paquete
Faculty of Economics and Centre for Intelligent Systems, University of Algarve
lpaquete@ualg.pt
Marco Chiarandini
Department of Mathematics and Computer Science, University of Southern Denmark
marco@imada.sdu.dk
Dario Basso
Department of Statistics, University of Padova
dario@stat.unipd.it
Program Committee
- Thomas
Bartz-Beielstein, Department of Computer Science, University of Dortmund
- Mauro Birattari, IRIDIA, Université Libre de Bruxelles
- Carlos M. Fonseca, Centre for Intelligent Systems, Faculty of
Science and Technology, University of Algarve
- Viviane Grunert da Fonseca, Instituto Superior D. Afonso III and Centre for
Intelligent Systems, University of Algarve
- Jürg Hüsler,
Institute of Mathematical Statistics
and Actuarial Science, University of Bern
- Catherine C. McGeoch,
Department of Mathematics and Computer Science, Amherst College
- Fortunato Pesarin, Department of Statistics,
University of Padova
- Rubén Ruiz, Department of Applied Statistics and Operations Research
and Quality, Valencia University of Technology
- Luigi Salmaso,
Faculty of Engineering, University of Padova
- Thomas
Stützle, IRIDIA, Université Libre de Bruxelles
Last modified: Wed Sep 27 09:00:03 CEST 2006
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