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 displayed 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

Software

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

Files (2)