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If you are interested in our recent article Self-adjusting parameter control for surrogate-assisted constrained optimization under limited budgets  which appeared in the journal Applied Soft Computing (ASOC), please take the opportunity to follow this link: https://authors.elsevier.com/a/1Vj555aecSVnxb. For a period until November, 02, 2017, this link will provide the free download of the final journal article. (After this period, the link is still

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Due to a major release change in SPOT, the newest package version SPOT 2.0 on CRAN is currently not compatible with TDMR 1.4 (Tuned Data Mining in R). Therefore TDMR 1.4 is currently archived on CRAN. We are working on an update. For the time being:

You can download TDMR 1.4 together with the last compatible SPOT 1.1.0 from the CIOP web site. Please follow the installation instructions here on our download page.

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l.t.r. Prof. Andreas Stafylopatis, Samineh Bagheri, Prof. Stefanos Kollias from National Technical University of Athens (NTUA) (Image: Themis Zervou / NTUA)

It was a big and nice surprise for us at "IEEE Symposium Series on Computational Intelligence" (IEEE SSCI 2016), a conference held in Athens, Greece, from 6th to 9th of December, 2016: After presenting her recent research work related to online model selection for constrained optimization, Samineh Bagheri won the Best Student Paper Award for it. The paper was selected from over 400 contributions from international researchers presented at this conference. This means Mehr »

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We are delighted to announce that our recent research work related to online model selection for constrained optimization has been accepted for publication and it will be presented at  "IEEE Symposium Series on Computational Intelligence" (IEEE SSCI 2016).  The SSCI 2016 conference will be held in Athens, Greece, from 6th to 9th of December, 2016. Many plenary and keynote talks are planned in the wide field of computational intelligence. 

Our article "Online Selection of Surrogate Models for Constrained Black-Box Optimization" received many positive

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