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Marc Huber

Address:
Marc Huber
Technische Universität Wien
Institute of Logic and Computation
Favoritenstraße 9–11, E192-01
1040 Wien
Austria

Room: HA0410
Phone: +43(1)58801–192144
Email: mhuber@ac.tuwien.ac.at
Web: http://www.ac.tuwien.ac.at/people/mhuber/

 

 

Publications

6 results
2023
[6]A Policy-Based Learning Beam Search for Combinatorial Optimization
Rupert Ettrich, Marc Huber, Günther Raidl
Evolutionary Computation in Combinatorial Optimization – 23nd European Conference, EvoCOP 2023 (Leslie Pérez Cáceres, Thomas Stützle, eds.), 2023, Springer.
Note: to appear
[bibtex] [pdf]
2022
[5]A Relative Value Function Based Learning Beam Search for Longest Common Subsequence Problems
M. Huber, G. R. Raidl
Chapter in Extended Abstracts of the 18th International Conference on Computer Aided Systems Theory – EUROCAST 2022 (Alexis Quesada-Arencibia, others, eds.), pages 22–23, 2022.
[bibtex] [pdf]
[4]A Learning Large Neighborhood Search for the Staff Rerostering Problem
Fabio F. Oberweger, Günther R. Raidl, Elina Rönnberg, Marc Huber
Integration of Constraint Programming, Artificial Intelligence, and Operations Research – CPAIOR 2022 (Pierre Schaus, ed.), volume 13292 of LNCS, pages 300–317, 2022, Springer.
[bibtex] [pdf] [doi]
[3]A Beam Search for the Shortest Common Supersequence Problem Guided by an Approximate Expected Length Calculation
Jonas Mayerhofer, Markus Kirchweger, Marc Huber, Günther Raidl
Evolutionary Computation in Combinatorial Optimization – EvoCOP 2022 (Leslie Pérez Cáceres, Sébastien Verel, eds.), volume 13222 of LNCS, pages 127–142, 2022, Springer.
[bibtex] [pdf] [doi]
[2]A Relative Value Function Based Learning Beam Search for the Longest Common Subsequence Problem
M. Huber, G. R. Raidl
Computer Aided Systems Theory – EUROCAST 2022 (Roberto Moreno-Díaz, Franz Pichler, Alexis Quesada-Arencibia, eds.), 2022, Springer.
Note: to appear
[bibtex] [pdf]
[1]Learning Beam Search: Utilizing Machine Learning to Guide Beam Search for Solving Combinatorial Optimization Problems
M. Huber, Günther R. Raidl
Machine Learning, Optimization, and Data Science, LOD 2021 (Giuseppe Nicosia, Varun Ojha, Emanuele La Malfa, Gabriele La Malfa, Giorgio Jansen, Panos M. Pardalos, Giovanni Giuffrida, Renato Umeton, eds.), volume 13164 of LNCS, pages 283–298, 2022, Springer.
[bibtex] [pdf] [doi]

Technical Reports

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  • Alexander Dobler
  • Jan Dreier
  • Herbert Fleischner
  • Nikolaus Frohner
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  • Christian Hatschka
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  • Enrico Iurlano
  • Thomas Jatschka
  • Liana Khazaliya
  • Markus Kirchweger
  • Viktoria Korchemna
  • Martin Kronegger
  • Andreas Müller
  • Martin Nöllenburg
  • Daniel Obszelka
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  • Sofia Simola
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