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Call for Papers: Workshop on Experimental Methods at PPSN 2010

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  • mike_preuss
    Call for Papers Workshop on Experimental Methods for the Assessment of Computational Systems (WEMACS) on September 11, 2010 in Krakow, Poland, as part of the
    Message 1 of 1 , Jun 17, 2010
      Call for Papers

      Workshop on Experimental Methods for the Assessment of Computational Systems (WEMACS)
      on September 11, 2010 in Krakow, Poland, as part of the PPSN 2010 workshop program

      Organizers: Thomas Bartz-Beielstein, Marco Chiarandini, Luis Paquete, Mike Preuss
      Advisory board: Mauro Birattari, Juergen Branke, Dimo Brockhoff, Carlos Fonseca, David Ginsbourger, Yuri Goegebeur, Gusz Eiben, Wolfgang Konen, Joern Mehnen, Boris Naujoks, Ruxandra Stoean, Heike Trautmann

      Submission: abstracts (<=4pages) or papers (<=10pages), LNCS formatted PDF, via
      mail to Mike Preuss (mike.preuss@...), --deadline-- July 15

      Accepted papers must be presented at the workshop and will be considered for a special issue of the Evolutionary Computation Journal, MIT Press.

      Scope of the Workshop
      The experimental analysis of computational systems inspired by nature can be made more sound and effective by the use of appropriate experimental methods. More severe requirements have been transmitted to draw objective conclusions from computational experiments, while at the same time the design and configuration of the computational systems can be improved by profitable ways of looking into the data collected. The quest for these methods is spawning a considerable amount of interdisciplinary research, mainly between the fields of computer science, artificial intelligence, optimization, statistics and machine learning.

      The aim of this workshop is to collect works in this interdisciplinary area. On the one side, we look for submissions advancing the quality of experimental methods. Some types of analysis still remain peculiar to the field of computer science and require ad hoc methods. Examples are modeling algorithm behavior over time, dealing with censored data, multiobjective and dynamic environments. On the other side, we look for works that possibly reinvestigate previously published computational systems and algorithms and extend the characterization of their empirical performances, producing novel results.

      Relevant topics for this workshop are:
      + Tuning and configuration: new methods and comparison of existing ones
      + Modeling algorithm behavior over time and applications of survival analysis
      + Learning methods for algorithm analysis and design
      + Methods for algorithm selection in algorithm portfolios
      + Generation of data sets for benchmarking
      + Novel results on empirical assessment and comparisons of known methods in old or new settings
      + Setting up and maintenance of data repositories
      + Assessment of analysis methods in terms of errors and predictive power
      + Performance assessment methods in multiobjective and dynamic environments
      + Novel ways to visualize results
      + Simulation techniques and meta-models for algorithm analysis
      + Assessment methods for competitions
      + Experiments to validate/substantiate recent advances in the theory of heuristic computations
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