Scientific Publications

A list of relevant peer-reviewed scientific papers and book chapters co-authored by us since 2005

[2015]

[2014]

[2013]

[2012]

  • Mark E. Kotanchek, Ekaterina Vladislavleva, and Guido F. Smits – Symbolic Regression in Not Enough: It takes a village to raise a model invited chapter for the Tenth anniversary GPTP workshop, May 2012, Ann Arbor, MI, U.S.A. To appear in Genetic Programming in Theory and Practice X book
  • Kalyan Veeramachaneni, Ekaterina Vladislavleva, Una-May O’Reilly – Knowledge mining sensory evaluation data: genetic programming, statistical techniques, and swarm optimization Journal on Genetic Programming and Evolvable Machines, March 2012, Volume 13, Issue 1, p.103-133
  • Martina Friese, Thomas Bartz-Beielstein, Katya Vladislavleva, Oliver Flasch, Olaf Mersmann, Boris Naujoks, Martin Zaefferer, Jörg Stork – Ensemble-based Model Selection for Smart-Metering Data. In Proceedings 22. Workshop Computational Intelligence, 2012, Germany, p. 215–228

[2011]

  • Rick Riolo, Ekaterina Vladislavleva, Jason H. Moore (Editors) – Genetic Programming Theory and Practice IX. Series: Genetic and Evolutionary Computation, 2011, ISBN 978-1-4614-1769-9, Hardcover. Springer.
  • Sean Stijven, Wouter Minnebo, Katya Vladislavleva. – Separating the wheat from the chaff: on feature selection and feature importance in regression random forests and symbolic regression. In Steven Gustafson and Ekaterina Vladislavleva editors, 3rd symbolic regression and modeling workshop for GECCO 2011, pages 623-630, Dublin, Ireland, 2011. ACM.
  • Smits G.F., Vladislavleva E., Kotanchek M. – Scalable Symbolic Regression by Continuous Evolution with Very Small Populations. In Genetic Programming Theory and Practice VIII, Genetic and Evolutionary Computation Vol.8, Rick Riolo,Trent McConaghy, and Ekaterina Vladislavleva (Editors), Chapter 9, Published: 2011, Springer, ISBN: 978-1-4419-7746-5
  • Kalyan K. Veeramachaneni, Ekaterina Vladislavleva and Una-May O’Reilly – Feature extraction from optimization samples via ensemble based symbolic regression. In Annals of Mathematics and Artificial Intelligence Journal, 2011, Springer Netherlands, ISSN: 1012-2443
  • Riolo, Rick; McConaghy, Trent; Vladislavleva, Ekaterina (Editors) – Genetic Programming Theory and Practice VIII , Springer Series: Genetic and Evolutionary Computation, Vol. 8, 2011, ISBN 978-1-4419-7746-5, Hardcover

[2010]

  • M. Kotanchek – Real World Data Modeling. In Juergen Branke etal. (Editors), GECCO'2010: Proceedings of the 12th annual conference on Genetic and evolutionary computation, pages 2863-2896, Portland, Oregon, USA, 2010, ISBN: 978-1-4503-0073-5 download
  • E. Vladislavleva, G. Smits, D. den Hertog. – On the Importance of Data Balancing for Symbolic Regression.. In IEEE Transactions On Evolutionary Computation, Volume 14, Issue: 2, Pages: 252-277, Published: 2010, ISSN: 1089-778X, DOI: 10.1109/TEVC.2009.2029697
  • Kotanchek M.E., Vladislavleva E.Y., Smits G.S. – Symbolic Regression as a Discovery Engine: Insights on Outliers and Prototypes. In Genetic Programming in Theory and Practice VII, Riolo Rick, O'Reilly Una-May and McConaghy Trent (Editors), Chapter 4, Published: 2010, ISBN:Â 978-1-4419-1625-9
  • Katya Vladislavleva, Kalyan Veeramachaneni, Matt Burland, Jason Parcon, Una-May O'Reilly, – Knowledge mining with genetic programming methods for variable selection in flavor design. In Juergen Branke et al. (Editors),GECCO'2010: Proceedings of the 12th annual conference on Genetic and evolutionary computation, pages 941-948, Portland, Oregon, USA, 2010, ISBN13:978-1-4503-0072-8
  • Kalyan Veeramachaneni, Katya Vladislavleva, Matt Burland, Jason Parcon, Una-May O'Reilly. – Evolutionary Optimization of Flavors. In Juergen Branke et al. (Editors), GECCO'2010: Proceedings of the 12th annual conference on Genetic and evolutionary computation, pages 1291-1298, Portland, Oregon, USA, 2010, ISBN13: 978-1-4503-0072-8
  • Katya Vladislavleva, Kalyan Veeramachaneni, Una-May O'Reilly – Learning a Lot from Only a Little: Genetic Programming for PanelSegmentation on Sparce Sensory Evaluation Data. In A.I.Esparcia-Alcazar et al. (Editors), Proceedings of the 13th European Conference on Genetic Programming, EuroGP2010, Lecture Notes on Computer Science, Volume 6021, pages 244-255, Istanbul, 2010, Springer, ISBN13: 978-3-642-12147-0
  • Kalyan Veeramachaneni, Katya Vladislavleva, Una-May O’Reilly – Feature Extraction from Optimization Data via DataModeler’s Ensemble Symbolic Regression, LION, Lecture Notes in Computer Science, Vol. 6073, pp. 251-265, Springer, 2010

[2009]

  • Mark Kotanchek and Guido Smits and Ekaterina Vladislavleva. – Exploiting Trustable Models via Pareto GP for Targeted Data Collection. In Rick L. Riolo, Terence Soule and Bill Worzel (Editors), Genetic Programming Theory and Practice VI, chapter 10, Published 2009, ISBN: 978-0-387-87622-1
  • E. Vladislavleva, G. Smits, D. den Hertog – Order of Nonlinearity as a Complexity Measure for Models Generated by Symbolic Regression via Pareto Genetic Programming.. In IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION, Volume 13, Issue: 2, Pages: 333-349, Published: 2009, ISSN: 1089-778X, DOI:10.1109/TEVC.2008.926486

[2008]

[2007]

[2006]

  • Guido Smits, Ekaterina Vladislavleva – Ordinal Pareto Genetic Programming. In Gary G. Yen etal. (Editors), Proceedings of the 2006 IEEE Congress on Evolutionary Computation, pages 3114-3120, Vancouver, BC, Canada, IEEE Press, Published 2006, ISBN: 0-7803-9487-9
  • Guido Smits, Arthur Kordon, Katherine Vladislavleva, Elsa Jordaan and Mark Kotanchek. – Variable Selection in Industrial Datasets using Pareto Genetic Programming. In Tina Yu, Rick Riolo and Bill Worzel (Editors), Genetic Programming Theory and Practice III (2005), chapter 6, Published 2006, ISBN: 978-0-387-28110-0

[2005]

  • Vladislavleva E. J. – Symbolic Regression via Genetic Programming. Thesis for Dow Benelux NV, Eindhoven, the Netherlands, Technische Universiteit Eindhoven, 02/2005