wir bieten...
Dekobild im Seitenkopf ISMLL
 
Personen: Daniela Thyssens
Sprechstunde:
C139 b Spl, n. V.
Telefon, E-Mail:
Phone: 05121 / 883-40378
E-Mail:
Postanschrift:
Wirtschaftsinformatik und Maschinelles Lernen
Universitätsplatz 1
Universität Hildesheim
31141 Hildesheim
Besuchsadresse:
Wirtschaftsinformatik und Maschinelles Lernen
Samelsonplatz 1
Universität Hildesheim
31141 Hildesheim

Publikationen:

  • Tim Dernedde, Daniela Thyssens, Sören Dittrich, Maximilian Stubbemann, Lars Schmidt-Thieme (2024):
    Moco: A Learnable Meta Optimizer for Combinatorial Optimization, in arXiv:2402.04915. PDF
  • Jonas K. Falkner, Daniela Thyssens, Ahmad Bdeir, Lars Schmidt-Thieme (2022):
    Learning to Control Local Search for Combinatorial Optimization., in arXiv preprint arXiv:2206.13181 (accepted at ECML 2022). PDF
  • Jonas K. Falkner, Daniela Thyssens, Lars Schmidt-Thieme (2022):
    Large Neighborhood Search based on Neural Construction Heuristics., in arXiv preprint arXiv:2205.00772. PDF
  • Daniela Thyssens, Jonas K. Falkner, Lars Schmidt-Thieme (2022):
    Supervised Permutation Invariant Networks for Solving the CVRP with Bounded Fleet Size., in arXiv preprint arXiv:2201.01529. PDF
  • Shereen Elsayed, Daniela Thyssens, Ahmed Rashed, Lars Schmidt-Thieme, Hadi S Jomaa (2021):
    Do We Really Need Deep Learning Models for Time Series Forecasting?, in arXiv preprint arXiv:2101.02118 (2021).
  • Shereen Elsayed, Daniela Thyssens, Shabanaz Chamurally, Arslan Tariq, Hadi S. Jomaa (2020):
    Exploring the influence of data aggregation in parking prediction, in International Conference on Database and Expert Systems Applications (DEXA workshop 2020).