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          <dc:title>Estimation-of-Distribution Algorithms: Theory and Applications (Dagstuhl Seminar 22182)</dc:title>
          <dc:creator>Uribe, Josu Ceberio</dc:creator>
          <dc:creator>Doerr, Benjamin</dc:creator>
          <dc:creator>Witt, Carsten</dc:creator>
          <dc:creator>Soloviev, Vicente P.</dc:creator>
          <dc:subject>estimation-of-distribution algorithms</dc:subject>
          <dc:subject>heuristic search and optimization</dc:subject>
          <dc:subject>machine learning</dc:subject>
          <dc:subject>probabilistic model building</dc:subject>
          <dc:description>The Dagstuhl seminar 22182 Estimation-of-Distribution Algorithms: Theory and Practice on May 2-6, 2022 brought together 19 international experts in estimation-of-distribution algorithms (EDAs). Their research ranged from a theoretical perspective, e.g., runtime analysis on synthetic problems, to an applied perspective, e.g., solutions of industrial optimization problems with EDAs. This report documents the program and the outcomes of the seminar.</dc:description>
          <dc:publisher>Schloss Dagstuhl – Leibniz-Zentrum für Informatik</dc:publisher>
          <dc:contributor>Josu Ceberio Uribe and Benjamin Doerr and Carsten Witt and Vicente P. Soloviev</dc:contributor>
          <dc:date>2022</dc:date>
          <dc:relation>Is Part Of Dagstuhl Reports, Volume 12, Issue 5 (2022)</dc:relation>
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          <dc:language>eng</dc:language>
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