Imitation learning model and datasets: "A Study of Learning Search Approximation in Mixed Integer Branch and Bound: Node Selection in SCIP"

doi: 10.4121/14054330.v1
The doi above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
doi: 10.4121/14054330
Datacite citation style:
Yilmaz, Kaan; Yorke-Smith, Neil (2021): Imitation learning model and datasets: "A Study of Learning Search Approximation in Mixed Integer Branch and Bound: Node Selection in SCIP". Version 1. 4TU.ResearchData. software. https://doi.org/10.4121/14054330.v1
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite
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Imitation learning model and datasets corresponding to the AI article "A Study of Learning Search Approximation in Mixed Integer Branch and Bound: Node Selection in SCIP".
history
  • 2021-05-18 first online, published, posted
publisher
4TU.ResearchData
funding
  • Foundations of Trustworthy AI - Integrating Reasoning, Learning and Optimization (grant code 952215) [more info...] European Commission
  • Dutch Research Council Groot project OPTIMAL
organizations
TU Delft, Faculty of Electrical Engineering, Mathematics and Computer Science

DATA

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