Please find below a Call for Contributions for the following GECCO 2020
WORKshop.
*Note that GECCO 2020 will be an electronic-only conference due to
COVID-19. * *It will be required that the presentation of all accepted
papers is provided in the form of a pre-recorded talk. More details about
this will be provided soon (together with how workshop discussions will
occur).*
Extended Submission deadline: April 17, 2020
Good Benchmarking Practices for Evolutionary Computation
BENCHMARK @ GECCO
https://sites.google.com/view/benchmarking-network/home/activities/GECCO20
<https://sites.google.com/view/benchmarking-network/home/activities/%0DGECCO20>
(Please copy and paste the above link in your browser if it does not work)
see also http://iao.hfuu.edu.cn/benchmark-gecco20
PDF Flyer:
http://www.gm.fh-koeln.de/~naujoks/gecco/benchmark_gecco20_cfp.pdf
Exteneded Submission Deadline: April 17th, 2020
to be held as part of the Genetic and Evolutionary Computation Conference
(GECCO 2020) July 8-12, 2020, Cancún, Quintana Roo, Mexico, organized by
ACM SIGEVO https://gecco-2020.sigevo.org
SCOPE AND OBJECTIVES
Benchmarking aims to illuminate the strengths and weaknesses of algorithms
regarding different problem characteristics. To this end, several
benchmarking suites have been designed which target different types of
characteristics.
Gaining insight into the behavior of algorithms on a wide array of problems
has benefits for different stakeholders. It helps engineers new to the
field of optimization find an algorithm suitable for their problem. It also
allows experts in optimization to develop new algorithms and improve
existing ones.
Even though benchmarking is a highly-researched topic within the
evolutionary computation community, there are still a number of open
questions and challenges that should be explored:
1.
(i) most commonly-used benchmarks are small and do not cover the space
of meaningful problems,
2.
(ii) benchmarking suites lack the complexity of real-world problems,
3.
(iii) proper statistical analysis techniques that can easily be applied
depending on the nature of the data are lacking or seldom used, and
4.
(iv) user-friendly, openly accessible benchmarking techniques and
software need to be developed and spread.
We wish to enable a culture of sharing to ensure direct access to resources
as well as reproducibility. This helps to avoid common pitfalls in
benchmarking such as overfitting to specific test cases. We aim to
establish new standards for benchmarking in evolutionary computation
research so we can objectively compare novel algorithms and fully
demonstrate where they excel and where they can be improved.
WORKSHOP DESCRIPTION
As the goal of the workshop is to discuss, develop and improve benchmarking
practices in evolutionary computation, we particularly welcome informal
position statements addressing or identifying open challenges in
benchmarking, as well as all other suggestions and contributions for a
discussion. Possible contributions include, but are not limited to:
-
- lists of open questions/issues in benchmarking
-
- examples of good benchmarking
-
- descriptions of common pitfalls in benchmarking and how to avoid them.
For all other information about the workshop, please contact Thomas Weise
at tweise@ustc.edu.cn with CC to p.oliveto@sheffield.ac.uk, lacava@upenn.edu
, boris.naujoks@th-koeln.de, and vanessa@modl.ai.
We also welcome the submission of workshop papers to be published in the
GECCO companion proceedings. The Workshop Call for Papers (CfP) can be
downloaded in PDF format or as plain text file here:
https://sites.google.com/view/benchmarking-network/home/activities/GECCO20
Our goal for the WORKshop is to collaboratively produce output that
improves the state-of-the-art of benchmarking in evolutionary computation,
not to organize yet another mini-conference!
TOPICS
The topics of interest for this workshop include, but are not limited to:
- the selection of meaningful (real-world) benchmark problems,
- performance measures for comparing algorithm behavior,
- novel statistical approaches for analyzing empirical data,
- landscape analysis,
- data mining approaches for understanding algorithm behavior,
- transfer learning from benchmark experiences to real-world problems, and
- benchmarking tools for executing experiments and analysis of experimental
results.
IMPORTANT DATES
Paper Submission Opening: 27 February 2020
Extended Submission Deadline: 17 April 2020
Decisions Due: 1 May 2020
Camera-Ready Material Due: 8 May 2020
Author Registration Deadline: 27 April 2020 (TBC)
Conference Presentation: 8-9 July 2020
*Submission Instructions*
All relevant instructions regarding paper submission are available at
https://gecco-2020.sigevo.org/index.html/tiki-index.php?page=Workshops.
RELATED EVENT
A similar benchmarking best practices workshop will be held at PPSN 2020,
which takes place from September 5-9, 2020, in Leiden, The
Netherlands: https://sites.google.com/view/benchmarking-
network/home/activities/PPSN20
<https://sites.google.com/view/benchmarking-%0Dnetwork/home/activities/PPSN20>
. Contributions to this workshop are welcome in any format until June 8,
2020.
LIST OF ORGANIZERS (alphabetical order)
Thomas Bäck, Leiden University, Leiden, The Netherlands
Carola Doerr, CNRS and Sorbonne University, Paris, France
Tome Eftimov, Jožef Stefan Institute, Ljubljana, Slovenia
Pascal Kerschke, University of Münster, Münster, Germany
William La Cava, University of Pennsylvania, Philadelphia, PA, USA
Manuel López-Ibáñez, University of Manchester, Manchester, UK
Boris Naujoks, Technical University of Cologne, Köln (Cologne), Germany
Pietro S. Oliveto, University of Sheffield, Sheffield, UK
Patryk Orzechowski, University of Pennsylvania, Philadelphia, PA, USA
Mike Preuss, LIACS, Leiden University, Leiden, The Netherlands
Jérémy Rapin, Facebook AI Research, Paris, France
Ofer M. Shir, Tel-Hai College and Migal Institute, Israel
Olivier Teytaud, Facebook AI Research, Paris, France
Heike Trautmann, University of Münster, Münster, Germany
Ryan J. Urbanowicz, University of Pennsylvania, Philadelphia, PA, USA
Vanessa Volz, modl.ai, Copenhagen, Denmark
Markus Wagner, The University of Adelaide, Adelaide, Australia
Hao Wang, Sorbonne University, Paris, France
Thomas Weise, Institute of Applied Optimization, Hefei University, Hefei,
China Borys Wróbel, Adam Mickiewicz University, Poland
Aleš Zamuda, University of Maribor, Maribor, Slovenia
HOSTING EVENT
The Genetic and Evolutionary Computation Conference (GECCO 2020) July 8-12,
2020, Cancún, Quintana Roo, Mexicohttp://gecco-2020.sigevo.org
The Genetic and Evolutionary Computation Conference (GECCO 2020) will
present the latest high- quality results in genetic and evolutionary
computation. Topics include genetic algorithms, genetic programming,
evolution strategies, evolutionary programming, memetic algorithms,
hyper-heuristics, real-world applications, evolutionary machine learning,
evolvable hardware, artificial life, adaptive behavior, ant colony
optimization, swarm intelligence, biological applications, evolutionary
robotics, coevolution, artificial immune systems, and more. The full list
of tracks is available at: https://gecco-
2020.sigevo.org/index.html/Program+Tracks
This workshop is organized as part of ImAppNIO Cost Action 15140.
--
Pietro S. Oliveto
Senior Lecturer,
EPSRC Early Career Fellow,
Department of Computer Science,
The University of Sheffield, Sheffield, UK.
*www.dcs.shef.ac.uk/people/P.Oliveto/rig/
<http://www.dcs.shef.ac.uk/people/P.Oliveto/rig/>*
*Fully funded PhD studentships available now* in time complexity analysis
of bio-inspired computation. Enquiries by excellent candidates can be sent
to me by email. Applications will be accepted until the posts are filled.
Further details are here
<http://staffwww.dcs.shef.ac.uk/people/P.Oliveto/PhDStudentships.html>.
Applicants should apply using the online application form here
<http://www.shef.ac.uk/postgraduate/online>
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