Designing MacPherson Suspension Architectures Using Bayesian Optimization

Sinnu Susan Thomas, Jacopo Palandri, Mohsen Lakehal-Ayat, Punarjay Chakravarty, Friedrich Wolf-Monheim, Matthew B. Blaschko. Designing MacPherson Suspension Architectures Using Bayesian Optimization. In Katrien Beuls, Bart Bogaerts 0001, Gianluca Bontempi, Pierre Geurts, Nick Harley, Bertrand Lebichot, Tom Lenaerts, Gilles Louppe, Paul Van Eecke, editors, Proceedings of the 31st Benelux Conference on Artificial Intelligence (BNAIC 2019) and the 28th Belgian Dutch Conference on Machine Learning (Benelearn 2019), Brussels, Belgium, November 6-8, 2019. Volume 2491 of CEUR Workshop Proceedings, CEUR-WS.org, 2019. [doi]

@inproceedings{ThomasPLCWB19,
  title = {Designing MacPherson Suspension Architectures Using Bayesian Optimization},
  author = {Sinnu Susan Thomas and Jacopo Palandri and Mohsen Lakehal-Ayat and Punarjay Chakravarty and Friedrich Wolf-Monheim and Matthew B. Blaschko},
  year = {2019},
  url = {http://ceur-ws.org/Vol-2491/paper104.pdf},
  researchr = {https://researchr.org/publication/ThomasPLCWB19},
  cites = {0},
  citedby = {0},
  booktitle = {Proceedings of the 31st Benelux Conference on Artificial Intelligence (BNAIC 2019) and the 28th Belgian Dutch Conference on Machine Learning (Benelearn 2019), Brussels, Belgium, November 6-8, 2019},
  editor = {Katrien Beuls and Bart Bogaerts 0001 and Gianluca Bontempi and Pierre Geurts and Nick Harley and Bertrand Lebichot and Tom Lenaerts and Gilles Louppe and Paul Van Eecke},
  volume = {2491},
  series = {CEUR Workshop Proceedings},
  publisher = {CEUR-WS.org},
}