Genetic Programming Bibliography entries for Gabriel Kronberger

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GP coauthors/coeditors: Michael Affenzeller, C Fischer, Stephan M Winkler, Stefan Wagner, Stefan Forstenlechner, Michael Kommenda, Herbert Stekel, Bogdan Burlacu, Gerd Bramerdorfer, Guenther Weidenholzer, Siegfried Silber, Wolfgang Amrhein, Lukas Kammerer, J Manuel Colmenar, Esther Maqueda, Marta Botella-Serrano, Jose Ignacio Hidalgo Perez, Christian Haider, Fabricio Olivetti de Franca, Florian Bachinger, Oscar Garnica, J Lanchares, Jose Manuel Velasco Cabo, Hannah Janout, Thomas Paier, Carina Ringelhahn, Michael Heckmann, Andreas Haghofer, David Joedicke, Sergio Contador, Evgeniya Kabliman, Ana Helena Kolody, Johannes Kronsteiner, Leonhard Schickmair, Benjamin Lindner, Christoph Feilmayr, Andreas Beham, Johannes Karder, Thomas Burgler, Stefan Fink, Andreas Scheibenpflug, Heinz Dobler, Andreas Promberger, Falk Nickel, Edwin Lughofer, Susanne Saminger-Platz, Harry Desmond, Deaglan J Bartlett, Patrick E Leser, Geoffrey F Bomarito, James McDermott, Patryk Orzechowski, Leonardo Vanneschi, Luca Manzoni, Roman Tobias Kalkreuth, Mauro Castelli, Laura Millan Garcia, Ricardo Fernandez Serrano, Gaspar Gonzalez Doncel, Ricardo Fernandez, Gizo Bokuchava, Patrice Halodova, Alberto Saez-Maderuelo, Christoph Neumueller, David Piringer, Bernhard Bloder, Stefan Prieschl, Dominic Girardi, Yousef A Radwan, Erik Pitzer, Stefan Vonolfen, Monika Kofler, Viktoria Dorfer, David Robert White, Brian W Goldman, Wojciech Jaskowski, Una-May O'Reilly, Sean Luke, Witold Jacak, Philipp Fleck, Ciprian Zavoianu, Daniela Zaharie,

Genetic Programming Articles by Gabriel Kronberger

  1. Laura Millan and Gabriel Kronberger and Ricardo Fernandez and Gizo Bokuchava and Patrice Halodova and Alberto Saez-Maderuelo and Gaspar Gonzalez-Doncel and J. Ignacio Hidalgo. Prediction of microscopic residual stresses using genetic programming. Applications in Engineering Science, 15:100141, 2023. details

  2. Hannah Janout and Thomas Paier and Carina Ringelhahn and Michael Heckmann and Andreas Haghofer and Gabriel Kronberger and Stephan Winkler. Identification of Surrogate Models for the Prediction of Degrees of Freedom within a Tolerance Chain. Procedia Computer Science, 217:796-805, 2023. 4th International Conference on Industry 4.0 and Smart Manufacturing. details

  3. C. Haider and F. O. de Franca and B. Burlacu and G. Kronberger. Shape-constrained multi-objective genetic programming for symbolic regression. Applied Soft Computing, 132:109855, 2023. details

  4. James McDermott and Gabriel Kronberger and Patryk Orzechowski and Leonardo Vanneschi and Luca Manzoni and Roman Kalkreuth and Mauro Castelli. Genetic Programming Benchmarks: Looking Back and Looking Forward. SIGEVOlution newsletter of the ACM Special Interest Group on Genetic and Evolutionary Computation, 15(3) 2022. details

  5. G. Kronberger and F. O. de Franca and B. Burlacu and C. Haider and M. Kommenda. Shape-constrained Symbolic Regression - Improving Extrapolation with Prior Knowledge. Evolutionary Computation, 30(1):75-98, 2022. details

  6. Gabriel Kronberger and Evgeniya Kabliman and Johannes Kronsteiner and Michael Kommenda. Extending a physics-based constitutive model using genetic programming. Applications in Engineering Science, 9:100080, 2022. details

  7. Evgeniya Kabliman and Ana Helena Kolody and Johannes Kronsteiner and Michael Kommenda and Gabriel Kronberger. Application of symbolic regression for constitutive modeling of plastic deformation. Applications in Engineering Science, 6:100052, 2021. details

  8. Gabriel Kronberger and J. Manuel Colmenar and Stephan M. Winkler and Jose Ignacio Hidalgo. Multilayer analysis of population diversity in grammatical evolution for symbolic regression. Soft Comput, 24(15):11283-11295, 2020. details

  9. Michael Kommenda and Bogdan Burlacu and Gabriel Kronberger and Michael Affenzeller. Parameter identification for symbolic regression using nonlinear least squares. Genetic Programming and Evolvable Machines, 21(3):471-501, 2020. Special Issue on Integrating numerical optimization methods with genetic programming. details

  10. Gabriel Kronberger and Michael Kommenda and Edwin Lughofer and Susanne Saminger-Platz and Andreas Promberger and Falk Nickel and Stephan Winkler and Michael Affenzeller. Using robust generalized fuzzy modeling and enhanced symbolic regression to model tribological systems. Applied Soft Computing, 69:610-624, 2018. details

  11. J. Ignacio Hidalgo and J. Manuel Colmenar and Gabriel Kronberger and Stephan M. Winkler and Oscar Garnica and Juan Lanchares. Data Based Prediction of Blood Glucose Concentrations Using Evolutionary Methods. Journal of Medical Systems, 41(9):142, 2017. Special issue on Patient Facing Systems. details

  12. Gerd Bramerdorfer and Stephan M. Winkler and Michael Kommenda and Guenther Weidenholzer and Siegfried Silber and Gabriel Kronberger and Michael Affenzeller and Wolfgang Amrhein. Using FE Calculations and Data-Based System Identification Techniques to Model the Nonlinear Behavior of PMSMs. IEEE Transactions on Industrial Electronics, 61(11):6454-6462, 2014. details

  13. Stephan M. Winkler and Gabriel K. Kronberger and Michael Affenzeller and Herbert Stekel. Variable Interaction Networks in Medical Data. International Journal of Privacy and Health Information Management (IJPHIM), 1(2):1-16, 2014. details

  14. Stephan M. Winkler and Michael Affenzeller and Gabriel Kronberger and Michael Kommenda and Stefan Wagner and Viktoria Dorfer and Witold Jacak and Herbert Stekel. On the use of estimated tumour marker classifications in tumour diagnosis prediction - a case study for breast cancer. International Journal of Simulation and Process Modelling, 8(1):29-41, 2013. details

  15. David R. White and James McDermott and Mauro Castelli and Luca Manzoni and Brian W. Goldman and Gabriel Kronberger and Wojciech Jaskowski and Una-May O'Reilly and Sean Luke. Better GP benchmarks: community survey results and proposals. Genetic Programming and Evolvable Machines, 14(1):3-29, 2013. details

  16. S. M. Winkler and M. Affenzeller and G. K. Kronberger and M. Kommenda and S. Wagner and W. Jacak and H. Stekel. On the Use of Estimated Tumor Marker Classifications in Tumor Diagnosis Prediction - A Case Study for Breast Cancer. International Journal of Simulation and Process Modelling, 2011. details

Genetic Programming Books by Gabriel Kronberger

Genetic Programming PhD doctoral thesis Gabriel Kronberger

Genetic Programming conference papers by Gabriel Kronberger

  1. Patrick Leser and Geoffrey Bomarito and Gabriel Kronberger and Fabricio Olivetti De Franca. Comparing Methods for Estimating Marginal Likelihood in Symbolic Regression. In William La Cava and Steven Gustafson editors, Symbolic Regression, pages 2058-2066, Melbourne, Australia, 2024. Association for Computing Machinery. details

  2. Gabriel Kronberger and Fabricio Olivetti de Franca and Harry Desmond and Deaglan Bartlett and Lukas Kammerer. The Inefficiency of Genetic Programming for Symbolic Regression. In Heike Trautmann and Tea Tusar and Penousal Machado and Thomas Baeck editors, 18th International Conference on Parallel Problem Solving from Nature, University of Applied Sciences Upper Austria, Hagenberg, Austria, 2024. Springer. details

  3. Fabricio Olivetti de Franca and Gabriel Kronberger. Reducing Overparameterization of Symbolic Regression Models with Equality Saturation. In Sara Silva and Luis Paquete and Leonardo Vanneschi and Nuno Lourenco and Ales Zamuda and Ahmed Kheiri and Arnaud Liefooghe and Bing Xue and Ying Bi and Nelishia Pillay and Irene Moser and Arthur Guijt and Jessica Catarino and Pablo Garcia-Sanchez and Leonardo Trujillo and Carla Silva and Nadarajen Veerapen editors, Proceedings of the 2023 Genetic and Evolutionary Computation Conference, pages 1064-1072, Lisbon, Portugal, 2023. Association for Computing Machinery. details

  4. Christian Haider and Fabricio Olivetti de Franca and Bogdan Burlacu and Florian Bachinger and Gabriel Kronberger and Michael Affenzeller. Shape-constrained Symbolic Regression: Real-World Applications in Magnetization, Extrusion and Data Validation. In Stephan Winkler and Leonardo Trujillo and Charles Ofria and Ting Hu editors, Genetic Programming Theory and Practice XX, pages 225-240, Michigan State University, USA, 2023. Springer. details

  5. Christian Haider and Fabricio De Franca and Gabriel Kronberger and Bogdan Burlacu. Comparing Optimistic and Pessimistic Constraint Evaluation in Shape-constrained Symbolic Regression. In Alma Rahat and Jonathan Fieldsend and Markus Wagner and Sara Tari and Nelishia Pillay and Irene Moser and Aldeida Aleti and Ales Zamuda and Ahmed Kheiri and Erik Hemberg and Christopher Cleghorn and Chao-li Sun and Georgios Yannakakis and Nicolas Bredeche and Gabriela Ochoa and Bilel Derbel and Gisele L. Pappa and Sebastian Risi and Laetitia Jourdan and Hiroyuki Sato and Petr Posik and Ofer Shir and Renato Tinos and John Woodward and Malcolm Heywood and Elizabeth Wanner and Leonardo Trujillo and Domagoj Jakobovic and Risto Miikkulainen and Bing Xue and Aneta Neumann and Richard Allmendinger and Inmaculada Medina-Bulo and Slim Bechikh and Andrew M. Sutton and Pietro Simone Oliveto editors, Proceedings of the 2022 Genetic and Evolutionary Computation Conference, pages 938-945, Boston, USA, 2022. Association for Computing Machinery. details

  6. David Piringer and Bernhard Bloder and Gabriel Kronberger. Steel Phase Kinetics Modeling using Symbolic Regression. In 2022 24th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC), pages 327-330, 2022. details

  7. Gabriel Kronberger. Local Optimization Often is Ill-conditioned in Genetic Programming for Symbolic Regression. In 2022 24th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC), pages 304-310, 2022. details

  8. Lukas Kammerer and Gabriel Kronberger and Michael Kommenda. Symbolic Regression with Fast Function Extraction and Nonlinear Least Squares Optimization. In Roberto Moreno-Diaz and Franz Pichler and Alexis Quesada-Arencibia editors, 18th International Conference on Computer Aided Systems Theory, EUROCAST 2022, volume 13789, pages 139-146, Las Palmas de Gran Canaria, Spain, 2022. Springer. Revised Selected Papers. details

  9. Christian Haider and Gabriel Kronberger. Shape-Constrained Symbolic Regression with NSGA-III. In Roberto Moreno-Diaz and Franz Pichler and Alexis Quesada-Arencibia editors, 18th International Conference on Computer Aided Systems Theory, EUROCAST 2022, volume 13789, pages 164-172, Las Palmas de Gran Canaria, Spain, 2022. Springer. Revised Selected Papers. details

  10. Bogdan Burlacu and Michael Kommenda and Gabriel Kronberger and Stephan M. Winkler and Michael Affenzeller. Symbolic Regression in Materials Science: Discovering Interatomic Potentials from Data. In Leonardo Trujillo and Stephan M. Winkler and Sara Silva and Wolfgang Banzhaf editors, Genetic Programming Theory and Practice XIX, pages 1-30, Ann Arbor, USA, 2022. Springer. details

  11. Laura Millan Garcia and Gabriel Kronberger and Jose Ignacio Hidalgo Perez and Ricardo Fernandez Serrano and Oscar Garnica and Gaspar Gonzalez Doncel. Estimation of Grain-level Residual Stresses in a Quenched Cylindrical Sample of Aluminum Alloy AA5083 using Genetic Programming. In Pedro Castillo and Juanlu Jimenez-Laredo editors, 24th International Conference, EvoApplications 2021, volume 12694, pages 421-436, virtual event, 2021. Springer Verlag. details

  12. Lukas Kammerer and Gabriel Kronberger and Stephan Winkler. Empirical Analysis of Variance for Genetic Programming based Symbolic Regression. In Francisco Chicano and Alberto Tonda and Krzysztof Krawiec and Marde Helbig and Christopher W. Cleghorn and Dennis G. Wilson and Georgios Yannakakis and Luis Paquete and Gabriela Ochoa and Jaume Bacardit and Christian Gagne and Sanaz Mostaghim and Laetitia Jourdan and Oliver Schuetze and Petr Posik and Carlos Segura and Renato Tinos and Carlos Cotta and Malcolm Heywood and Mengjie Zhang and Leonardo Trujillo and Risto Miikkulainen and Bing Xue and Aneta Neumann and Richard Allmendinger and Fuyuki Ishikawa and Inmaculada Medina-Bulo and Frank Neumann and Andrew M. Sutton editors, Proceedings of the 2021 Genetic and Evolutionary Computation Conference Companion, pages 251-252, internet, 2021. Association for Computing Machinery. details

  13. David Joedicke and Gabriel Kronberger and Jose Manuel Colmenar and Stephan M. Winkler and Jose Manuel Velasco and Sergio Contador and Jose Ignacio Hidalgo. Analysis of the performance of Genetic Programming on the Blood Glucose Level Prediction Challenge 2020. In Kerstin Bach and Razvan C. Bunescu and Cindy Marling and Nirmalie Wiratunga editors, Proceedings of the 5th International Workshop on Knowledge Discovery in Healthcare Data co-located with 24th European Conference on Artificial Intelligence, KDH@ECAI 2020, volume 2675, pages 141-145, Santiago de Compostela, Spain and Virtually, 2020. CEUR-WS.org. details

  14. Bogdan Burlacu and Gabriel Kronberger and Michael Kommenda. Operon C++: An Efficient Genetic Programming Framework for Symbolic Regression. In Richard Allmendinger and Hugo Terashima Marin and Efren Mezura Montes and Thomas Bartz-Beielstein and Bogdan Filipic and Ke Tang and David Howard and Emma Hart and Gusz Eiben and Tome Eftimov and William La Cava and Boris Naujoks and Pietro Oliveto and Vanessa Volz and Thomas Weise and Bilel Derbel and Ke Li and Xiaodong Li and Saul Zapotecas and Qingfu Zhang and Rui Wang and Ran Cheng and Guohua Wu and Miqing Li and Hisao Ishibuchi and Jonathan Fieldsend and Ozgur Akman and Khulood Alyahya and Juergen Branke and John R. Woodward and Daniel R. Tauritz and Marco Baioletti and Josu Ceberio Uribe and John McCall and Alfredo Milani and Stefan Wagner and Michael Affenzeller and Bradley Alexander and Alexander (Sandy) Brownlee and Saemundur O. Haraldsson and Markus Wagner and Nayat Sanchez-Pi and Luis Marti and Silvino Fernandez Alzueta and Pablo Valledor Pellicer and Thomas Stuetzle and Matthew Johns and Nick Ross and Ed Keedwell and Herman Mahmoud and David Walker and Anthony Stein and Masaya Nakata and David Paetzel and Neil Vaughan and Stephen Smith and Stefano Cagnoni and Robert M. Patton and Ivanoe De Falco and Antonio Della Cioppa and Umberto Scafuri and Ernesto Tarantino and Akira Oyama and Koji Shimoyama and Hemant Kumar Singh and Kazuhisa Chiba and Pramudita Satria Palar and Alma Rahat and Richard Everson and Handing Wang and Yaochu Jin and Erik Hemberg and Riyad Alshammari and Tokunbo Makanju and Fuijimino-shi and Ivan Zelinka and Swagatam Das and Ponnuthurai Nagaratnam and Roman Senkerik editors, Proceedings of the 2020 Genetic and Evolutionary Computation Conference Companion, pages 1562-1570, internet, 2020. Association for Computing Machinery. details

  15. Evgeniya Kabliman and Ana Helena Kolody and Michael Kommenda and Gabriel Kronberger. Prediction of stress-strain curves for aluminium alloys using symbolic regression. In Proceedings of the 22nd International ESAFORM Conference on Material Forming, volume 2113, page 180009, 2019. AIP. details

  16. Gabriel Kronberger and Lukas Kammerer and Michael Kommenda. Identification of Dynamical Systems Using Symbolic Regression. In Roberto Moreno-Diaz and Franz Pichler and Alexis Quesada-Arencibia editors, International Conference on Computer Aided Systems Theory, EUROCAST 2019, volume 12013, pages 370-377, Las Palmas de Gran Canaria, Spain, 2019. Springer. details

  17. Lukas Kammerer and Gabriel Kronberger and Bogdan Burlacu and Stephan M. Winkler and Michael Kommenda and Michael Affenzeller. Symbolic Regression by Exhaustive Search: Reducing the Search Space Using Syntactical Constraints and Efficient Semantic Structure Deduplication. In Wolfgang Banzhaf and Erik Goodman and Leigh Sheneman and Leonardo Trujillo and Bill Worzel editors, Genetic Programming Theory and Practice XVII, pages 79-99, East Lansing, MI, USA, 2019. Springer. details

  18. Lukas Kammerer and Gabriel Kronberger and Michael Kommenda. Data Aggregation for Reducing Training Data in Symbolic Regression. In Roberto Moreno-Diaz and Franz Pichler and Alexis Quesada-Arencibia editors, International Conference on Computer Aided Systems Theory, EUROCAST 2019, volume 12013, pages 378-386, Las Palmas de Gran Canaria, Spain, 2019. Springer. details

  19. Stefan Prieschl and Dominic Girardi and Gabriel Kronberger. Using Ontologies to Express Prior Knowledge for Genetic Programming. In Andreas Holzinger and Peter Kieseberg and A Min Tjoa and Edgar R. Weippl editors, Machine Learning and Knowledge Extraction - Third IFIP TC 5, TC 12, WG 8.4, WG 8.9, WG 12.9 International Cross-Domain Conference, CD-MAKE 2019, Canterbury, UK, August 26-29, 2019, Proceedings, volume 11713, pages 362-376, 2019. Springer. details

  20. Bogdan Burlacu and Gabriel Kronberger and Michael Kommenda and Michael Affenzeller. Parsimony measures in multi-objective genetic programming for symbolic regression. In Richard Allmendinger and Carlos Cotta and Carola Doerr and Pietro S. Oliveto and Thomas Weise and Ales Zamuda and Anne Auger and Dimo Brockhoff and Nikolaus Hansen and Tea Tusar and Konstantinos Varelas and David Camacho-Fernandez and Massimiliano Vasile and Annalisa Riccardi and Bilel Derbel and Ke Li and Xiaodong Li and Saul Zapotecas and Qingfu Zhang and Ozgur Akman and Khulood Alyahya and Juergen Branke and Jonathan Fieldsend and Tinkle Chugh and Jussi Hakanen and Josu Ceberio Uribe and Valentino Santucci and Marco Baioletti and John McCall and Emma Hart and Daniel R. Tauritz and John R. Woodward and Koichi Nakayama and Chika Oshima and Stefan Wagner and Michael Affenzeller and Eneko Osaba and Javier Del Ser and Pascal Kerschke and Boris Naujoks and Vanessa Volz and Anna I Esparcia-Alcazar and Riyad Alshammari and Erik Hemberg and Tokunbo Makanju and Brad Alexander and Saemundur O. Haraldsson and Markus Wagner and Silvino Fernandez Alzueta and Pablo Valledor Pellicer and Thomas Stuetzle and David Walker and Matt Johns and Nick Ross and Ed Keedwell and Masaya Nakata and Anthony Stein and Takato Tatsumi and Nadarajen Veerapen and Arnaud Liefooghe and Sebastien Verel and Gabriela Ochoa and Stephen Smith and Stefano Cagnoni and Robert M. Patton and William La Cava and Randal Olson and Patryk Orzechowski and Ryan Urbanowicz and Akira Oyama and Koji Shimoyama and Hemant Kumar Singh and Kazuhisa Chiba and Pramudita Satria Palar and Alma Rahat and Richard Everson and Handing Wang and Yaochu Jin and Marcus Gallagher and Mike Preuss and Olivier Teytaud and Fernando Lezama and Joao Soares and Zita Vale editors, GECCO '19: Proceedings of the Genetic and Evolutionary Computation Conference Companion, pages 338-339, Prague, Czech Republic, 2019. ACM. details

  21. Bogdan Burlacu and Lukas Kammerer and Michael Affenzeller and Gabriel Kronberger. Hash-Based Tree Similarity and Simplification in Genetic Programming for Symbolic Regression. In Roberto Moreno-Diaz and Franz Pichler and Alexis Quesada-Arencibia editors, International Conference on Computer Aided Systems Theory, EUROCAST 2019, volume 12013, pages 361-369, Las Palmas de Gran Canaria, Spain, 2019. Springer. details

  22. B. Burlacu and M. Affenzeller and G. Kronberger and M. Kommenda. Online Diversity Control in Symbolic Regression via a Fast Hash-based Tree Similarity Measure. In 2019 IEEE Congress on Evolutionary Computation (CEC), pages 2175-2182, 2019. details

  23. Gabriel Kronberger and Lukas Kammerer and Bogdan Burlacu and Stephan M. Winkler and Michael Kommenda and Michael Affenzeller. Cluster Analysis of a Symbolic Regression Search Space. In Wolfgang Banzhaf and Lee Spector and Leigh Sheneman editors, Genetic Programming Theory and Practice XVI, pages 85-102, Ann Arbor, USA, 2018. Springer. details

  24. Gabriel Kronberger and Michael Kommenda and Andreas Promberger and Falk Nickel. Predicting friction system performance with symbolic regression and genetic programming with factor variables. In Hernan Aguirre and Keiki Takadama and Hisashi Handa and Arnaud Liefooghe and Tomohiro Yoshikawa and Andrew M. Sutton and Satoshi Ono and Francisco Chicano and Shinichi Shirakawa and Zdenek Vasicek and Roderich Gross and Andries Engelbrecht and Emma Hart and Sebastian Risi and Ekart Aniko and Julian Togelius and Sebastien Verel and Christian Blum and Will Browne and Yusuke Nojima and Tea Tusar and Qingfu Zhang and Nikolaus Hansen and Jose Antonio Lozano and Dirk Thierens and Tian-Li Yu and Juergen Branke and Yaochu Jin and Sara Silva and Hitoshi Iba and Anna I Esparcia-Alcazar and Thomas Bartz-Beielstein and Federica Sarro and Giuliano Antoniol and Anne Auger and Per Kristian Lehre editors, GECCO '18: Proceedings of the Genetic and Evolutionary Computation Conference, pages 1278-1285, Kyoto, Japan, 2018. ACM. details

  25. Bogdan Burlacu and Michael Affenzeller and Michael Kommenda and Gabriel Kronberger and Stephan Winkler. Schema Analysis in Tree-Based Genetic Programming. In Wolfgang Banzhaf and Randal S. Olson and William Tozier and Rick Riolo editors, Genetic Programming Theory and Practice XV, pages 17-37, University of Michigan in Ann Arbor, USA, 2017. Springer. details

  26. Jose Ignacio Hidalgo and J. Manuel Colmenar and Gabriel Kronberger and Stephan M. Winkler. Glucose Prognosis by Grammatical Evolution. In Roberto Moreno-Diaz and Franz Pichler and Alexis Quesada-Arencibia editors, 16th International Conference on Computer Aided Systems Theory, EUROCAST 2017, Part I, volume 10671, pages 455-463, Las Palmas de Gran Canaria, Spain, 2017. Springer. Revised Selected Papers. details

  27. Bogdan Burlacu and Michael Affenzeller and Michael Kommenda and Gabriel Kronberger and Stephan M. Winkler. Analysis of Schema Frequencies in Genetic Programming. In Roberto Moreno-Diaz and Franz Pichler and Alexis Quesada-Arencibia editors, 16th International Conference on Computer Aided Systems Theory, EUROCAST 2017, Part I, volume 10671, pages 432-438, Las Palmas de Gran Canaria, Spain, 2017. Springer. Revised Selected Papers. details

  28. Michael Affenzeller and Stephan M. Winkler and Bogdan Burlacu and Gabriel Kronberger and Michael Kommenda and Stefan Wagner. Dynamic Observation of Genotypic and Phenotypic Diversity for Different Symbolic Regression GP Variants. In Proceedings of the Genetic and Evolutionary Computation Conference Companion, pages 1553-1558, Berlin, Germany, 2017. ACM. details

  29. Gabriel K. Kronberger and Bogdan Burlacu and Michael Kommenda and Stephan Winkler and Michael Affenzeller. Measures for the Evaluation and Comparison of Graphical Model Structures. In Roberto Moreno-Diaz and Franz Pichler and Alexis Quesada-Arencibia editors, Computer Aided Systems Theory, EUROCAST 2017, volume 10671, pages 283-290, Las Palmas de Gran Canaria, Spain, 2017. details

  30. Michael Kommenda and Johannes Karder and Andreas Beham and Bogdan Burlacu and Gabriel K. Kronberger and Stefan Wagner and Michael Affenzeller. Optimization Networks for Integrated Machine Learning. In Roberto Moreno-Diaz and Franz Pichler and Alexis Quesada-Arencibia editors, Computer Aided Systems Theory, EUROCAST 2017, volume 10671, pages 392-399, Las Palmas de Gran Canaria, Spain, 2017. details

  31. Michael Affenzeller and Bogdan Burlacu and Stephan M. Winkler and Michael Kommenda and Gabriel K. Kronberger and Stefan Wagner. Offspring Selection Genetic Algorithm Revisited: Improvements in Efficiency by Early Stopping Criteria in the Evaluation of Unsuccessful Individuals. In Roberto Moreno-Diaz and Franz Pichler and Alexis Quesada-Arencibia editors, 16th International Conference on Computer Aided Systems Theory, EUROCAST 2017, volume 10671, pages 424-431, Las Palmas de Gran Canaria, Spain, 2017. Springer. details

  32. Stephan M. Winkler and Michael Affenzeller and Bogdan Burlacu and Gabriel Kronberger and Michael Kommenda and Philipp Fleck. Similarity-based Analysis of Population Dynamics in Genetic Programming Performing Symbolic Regression. In Rick Riolo and Bill Worzel and Brian Goldman and Bill Tozier editors, Genetic Programming Theory and Practice XIV, pages 1-17, Ann Arbor, USA, 2016. Springer. details

  33. J. Manuel Colmenar and Stephan M. Winkler and Gabriel Kronberger and Esther Maqueda and Marta Botella and J. Ignacio Hidalgo. Predicting Glycemia in Diabetic Patients By Evolutionary Computation and Continuous Glucose Monitoring. In Tobias Friedrich and Frank Neumann and Andrew M. Sutton and Martin Middendorf and Xiaodong Li and Emma Hart and Mengjie Zhang and Youhei Akimoto and Peter A. N. Bosman and Terry Soule and Risto Miikkulainen and Daniele Loiacono and Julian Togelius and Manuel Lopez-Ibanez and Holger Hoos and Julia Handl and Faustino Gomez and Carlos M. Fonseca and Heike Trautmann and Alberto Moraglio and William F. Punch and Krzysztof Krawiec and Zdenek Vasicek and Thomas Jansen and Jim Smith and Simone Ludwig and JJ Merelo and Boris Naujoks and Enrique Alba and Gabriela Ochoa and Simon Poulding and Dirk Sudholt and Timo Koetzing editors, GECCO '16 Companion: Proceedings of the Companion Publication of the 2016 Annual Conference on Genetic and Evolutionary Computation, pages 1393-1400, Denver, Colorado, USA, 2016. ACM. details

  34. Michael Kommenda and Gabriel Kronberger and Michael Affenzeller and Stephan Winkler and Bogdan Burlacu. Evolving Simple Symbolic Regression Models by Multi-objective Genetic Programming. In Rick Riolo and William P. Worzel and M. Kotanchek and A. Kordon editors, Genetic Programming Theory and Practice XIII, pages 1-19, Ann Arbor, USA, 2015. Springer. details

  35. Gabriel Kronberger and Michael Kommenda and Stephan M. Winkler and Michael Affenzeller. Using Contextual Information in Sequential Search for Grammatical Optimization Problems. In Roberto Moreno-Diaz and Franz Pichler and Alexis Quesada-Arencibia editors, 15th International Conference Computer Aided Systems Theory, EUROCAST 2015, volume 9520, pages 417-424, Las Palmas de Gran Canaria, Spain, 2015. Springer. Revised Selected Papers. details

  36. Stephan M. Winkler and Gabriel K. Kronberger and Michael Kommenda and Stefan Fink and Michael Affenzeller. Dynamics of Predictability and Variable Influences Identified in Financial Data Using Sliding Window Machine Learning. In Roberto Moreno-Diaz and Franz Pichler and Alexis Quesada-Arencibia editors, Computer Aided Systems Theory, EUROCAST 2015, volume 9520, pages 326-333, Las Palmas, Gran Canaria, Spain, 2015. Springer. details

  37. Michael Kommenda and Andreas Beham and Michael Affenzeller and Gabriel K. Kronberger. Complexity Measures for Multi-Objective Symbolic Regression. In Roberto Moreno-Diaz and Franz Pichler and Alexis Quesada-Arencibia editors, Computer Aided Systems Theory, EUROCAST 2015, volume 9520, pages 409-416, Las Palmas, Gran Canaria, Spain, 2015. Springer. details

  38. Stephan M. Winkler and Michael Affenzeller and Gabriel Kronberger and Michael Kommenda and Bogdan Burlacu and Stefan Wagner. Sliding Window Symbolic Regression for Detecting Changes of System Dynamics. In Rick Riolo and William P. Worzel and Mark Kotanchek editors, Genetic Programming Theory and Practice XII, pages 91-107, Ann Arbor, USA, 2014. Springer. details

  39. Michael Kommenda and Michael Affenzeller and Bogdan Burlacu and Gabriel Kronberger and Stephan M. Winkler. Genetic programming with data migration for symbolic regression. In Steven Gustafson and Ekaterina Vladislavleva editors, GECCO 2014 Workshop on Symbolic Regression and Modelling, pages 1361-1366, Vancouver, BC, Canada, 2014. ACM. details

  40. Gabriel Kronberger and Michael Kommenda and Stefan Wagner and Heinz Dobler. GPDL: a framework-independent problem definition language for grammar-guided genetic programming. In Christian Blum and Enrique Alba and Thomas Bartz-Beielstein and Daniele Loiacono and Francisco Luna and Joern Mehnen and Gabriela Ochoa and Mike Preuss and Emilia Tantar and Leonardo Vanneschi and Kent McClymont and Ed Keedwell and Emma Hart and Kevin Sim and Steven Gustafson and Ekaterina Vladislavleva and Anne Auger and Bernd Bischl and Dimo Brockhoff and Nikolaus Hansen and Olaf Mersmann and Petr Posik and Heike Trautmann and Muhammad Iqbal and Kamran Shafi and Ryan Urbanowicz and Stefan Wagner and Michael Affenzeller and David Walker and Richard Everson and Jonathan Fieldsend and Forrest Stonedahl and William Rand and Stephen L. Smith and Stefano Cagnoni and Robert M. Patton and Gisele L. Pappa and John Woodward and Jerry Swan and Krzysztof Krawiec and Alexandru-Adrian Tantar and Peter A. N. Bosman and Miguel Vega-Rodriguez and Jose M. Chaves-Gonzalez and David L. Gonzalez-Alvarez and Sergio Santander-Jimenez and Lee Spector and Maarten Keijzer and Kenneth Holladay and Tea Tusar and Boris Naujoks editors, GECCO '13 Companion: Proceeding of the fifteenth annual conference companion on Genetic and evolutionary computation conference companion, pages 1333-1340, Amsterdam, The Netherlands, 2013. ACM. details

  41. Gabriel Kronberger and Michael Kommenda. Evolution of Covariance Functions for Gaussian Process Regression using Genetic Programming. In EuroCAST 2013, Las Palmas, Canary Islands, Spain, 2013. Springer. details

  42. Michael Kommenda and Gabriel Kronberger and Stephan Winkler and Michael Affenzeller and Stefan Wagner. Effects of constant optimization by nonlinear least squares minimization in symbolic regression. In Christian Blum and Enrique Alba and Thomas Bartz-Beielstein and Daniele Loiacono and Francisco Luna and Joern Mehnen and Gabriela Ochoa and Mike Preuss and Emilia Tantar and Leonardo Vanneschi and Kent McClymont and Ed Keedwell and Emma Hart and Kevin Sim and Steven Gustafson and Ekaterina Vladislavleva and Anne Auger and Bernd Bischl and Dimo Brockhoff and Nikolaus Hansen and Olaf Mersmann and Petr Posik and Heike Trautmann and Muhammad Iqbal and Kamran Shafi and Ryan Urbanowicz and Stefan Wagner and Michael Affenzeller and David Walker and Richard Everson and Jonathan Fieldsend and Forrest Stonedahl and William Rand and Stephen L. Smith and Stefano Cagnoni and Robert M. Patton and Gisele L. Pappa and John Woodward and Jerry Swan and Krzysztof Krawiec and Alexandru-Adrian Tantar and Peter A. N. Bosman and Miguel Vega-Rodriguez and Jose M. Chaves-Gonzalez and David L. Gonzalez-Alvarez and Sergio Santander-Jimenez and Lee Spector and Maarten Keijzer and Kenneth Holladay and Tea Tusar and Boris Naujoks editors, GECCO '13 Companion: Proceeding of the fifteenth annual conference companion on Genetic and evolutionary computation conference companion, pages 1121-1128, Amsterdam, The Netherlands, 2013. ACM. details

  43. Bogdan Burlacu and Michael Affenzeller and Michael Kommenda and Stephan Winkler and Gabriel Kronberger. Visualization of genetic lineages and inheritance information in genetic programming. In Christian Blum and Enrique Alba and Thomas Bartz-Beielstein and Daniele Loiacono and Francisco Luna and Joern Mehnen and Gabriela Ochoa and Mike Preuss and Emilia Tantar and Leonardo Vanneschi and Kent McClymont and Ed Keedwell and Emma Hart and Kevin Sim and Steven Gustafson and Ekaterina Vladislavleva and Anne Auger and Bernd Bischl and Dimo Brockhoff and Nikolaus Hansen and Olaf Mersmann and Petr Posik and Heike Trautmann and Muhammad Iqbal and Kamran Shafi and Ryan Urbanowicz and Stefan Wagner and Michael Affenzeller and David Walker and Richard Everson and Jonathan Fieldsend and Forrest Stonedahl and William Rand and Stephen L. Smith and Stefano Cagnoni and Robert M. Patton and Gisele L. Pappa and John Woodward and Jerry Swan and Krzysztof Krawiec and Alexandru-Adrian Tantar and Peter A. N. Bosman and Miguel Vega-Rodriguez and Jose M. Chaves-Gonzalez and David L. Gonzalez-Alvarez and Sergio Santander-Jimenez and Lee Spector and Maarten Keijzer and Kenneth Holladay and Tea Tusar and Boris Naujoks editors, GECCO '13 Companion: Proceeding of the fifteenth annual conference companion on Genetic and evolutionary computation conference companion, pages 1351-1358, Amsterdam, The Netherlands, 2013. ACM. details

  44. Michael Kommenda and Michael Affenzeller and Gabriel K. Kronberger and Stephan M. Winkler. Nonlinear Least Squares Optimization of Constants in Symbolic Regression. In Roberto Moreno-Diaz and Franz Pichler and Alexis Quesada-Arencibia editors, Computer Aided Systems Theory, EUROCAST 2013, volume 8111, pages 420-427, Las Palmas de Gran Canaria, Spain, 2013. Springer. details

  45. S. Wagner and G. Kronberger and A. Beham and M. Kommenda and A. Scheibenpflug and E. Pitzer and S. Vonolfen and M. Kofler and S. Winkler and V. Dorfer and M. Affenzeller. Architecture and Design of the HeuristicLab Optimization Environment. In Robin Braun and Zenon Chaczko and Franz Pichler editors, First Australian Conference on the Applications of Systems Engineering, ACASE, volume 6, pages 197-261, Sydney, Australia, 2012. Springer International Publishing. Selected and updated papers. details

  46. Gabriel Kronberger and Stefan Wagner and Michael Kommenda and Andreas Beham and Andreas Scheibenpflug and Michael Affenzeller. Knowledge Discovery through Symbolic Regression with HeuristicLab. In Bettina Berendt and Myra Spiliopoulou editors, Conference booklet ECML-PKDD 2012, volume 7524, pages 824-827, Bristol UK, 2012. Springer. Demo Spotlights. details

  47. Michael Kommenda and Gabriel Kronberger and Stefan Wagner and Stephan Winkler and Michael Affenzeller. On the architecture and implementation of tree-based genetic programming in HeuristicLab. In Stefan Wagner and Michael Affenzeller editors, GECCO 2012 Evolutionary Computation Software Systems (EvoSoft), pages 101-108, Philadelphia, Pennsylvania, USA, 2012. ACM. details

  48. Bogdan Burlacu and Michael Affenzeller and Michael Kommenda and Stephan M. Winkler and Gabriel Kronberger. Evolution Tracking in Genetic Programming. In Emilio Jimenez and Boris Sokolov editors, The 24th European Modeling and Simulation Symposium, EMSS 2012, Vienna, Austria, 2012. details

  49. Michael Affenzeller and Stephan M. Winkler and Stefan Forstenlechner and Gabriel Kronberger and Michael Kommenda and Stefan Wagner and Herbert Stekel. Enhanced Confidence Interpretations of GP Based Ensemble Modeling Results. In Emilio Jimenez and Boris Sokolov editors, The 24th European Modeling and Simulation Symposium, EMSS 2012, pages 340-345, Vienna, Austria, 2012. details

  50. S. M. Winkler and M. Affenzeller and G. K. Kronberger and M. Kommenda and S. Wagner and W. Jacak and H. Stekel. Variable Interaction Networks in Medical Data. In Proceedings of the 24th European Modeling and Simulation Symposium EMSS 2012, pages 265-270, Vienna, Austria, 2012. details

  51. Andreas Scheibenpflug and Stefan Wagner and Gabriel K. Kronberger and Michael Affenzeller. HeuristicLab Hive - An Open Source Environment for Parallel and Distributed Execution of Heuristic Optimization Algorithms. In Robin Braun and Zenon Chaczko editors, 1st Australian Conference on the Applications of Systems Engineering ACASE'12, pages 63-65, Sydney, Australia, 2012. details

  52. Stephan M. Winkler and Michael Affenzeller and Gabriel K. Kronberger and Michael Kommenda and Stefan Wagner and Witold Jacak and Herbert Stekel. Analysis of Selected Evolutionary Algorithms in Feature Selection and Parameter Optimization for Data Based Tumor Marker Modeling. In Roberto Moreno-Diaz and Franz Pichler and Alexis Quesada-Arencibia editors, Computer Aided Systems Theory, EUROCAST 2011, volume 6927, pages 335-342, 2012. Springer. details

  53. Alexandru-Ciprian Zavoianu and Gabriel Kronberger and Michael Kommenda and Daniela Zaharie and Michael Affenzeller. Improving the Parsimony of Regression Models for an Enhanced Genetic Programming Process. In Roberto Moreno-Diaz and Franz Pichler and Alexis Quesada-Arencibia editors, 13th International Conference on Computer Aided Systems Theory, EUROCAST 2011, volume 6927, pages 264-271, Las Palmas de Gran Canaria, Spain, 2011. Springer. details

  54. Stefan Wagner and Gabriel Kronberger. Algorithm and experiment design with heuristiclab: an open source optimization environment for research and education. In Darrell Whitley editor, GECCO 2011 Tutorials, pages 1411-1438, Dublin, Ireland, 2011. ACM. details

  55. Gabriel Kronberger and Stefan Fink and Michael Kommenda and Michael Affenzeller. Macro-economic Time Series Modeling and Interaction Networks. In Cecilia Di Chio and Anthony Brabazon and Gianni Di Caro and Rolf Drechsler and Marc Ebner and Muddassar Farooq and Joern Grahl and Gary Greenfield and Christian Prins and Juan Romero and Giovanni Squillero and Ernesto Tarantino and Andrea G. B. Tettamanzi and Neil Urquhart and A. Sima Uyar editors, Applications of Evolutionary Computing, EvoApplications 2011: EvoCOMNET, EvoFIN, EvoHOT, EvoMUSART, EvoSTIM, EvoTRANSLOG, volume 6625, pages 101-110, Turin, Italy, 2011. Springer Verlag. details

  56. Gabriel Kronberger and Michael Kommenda and Michael Affenzeller. Overfitting detection and adaptive covariant parsimony pressure for symbolic regression. In Steven Gustafson and Ekaterina Vladislavleva editors, 3rd symbolic regression and modeling workshop for GECCO 2011, pages 631-638, Dublin, Ireland, 2011. ACM. details

  57. Michael Kommenda and Gabriel Kronberger and Christoph Feilmayr and Michael Affenzeller. Data Mining Using Unguided Symbolic Regression on a Blast Furnace Dataset. In Cecilia Di Chio and Stefano Cagnoni and Carlos Cotta and Marc Ebner and Aniko Ekart and Anna I Esparcia-Alcazar and Juan J. Merelo and Ferrante Neri and Mike Preuss and Hendrik Richter and Julian Togelius and Georgios N. Yannakakis editors, Applications of Evolutionary Computing, EvoApplications 2011: EvoCOMPLEX, EvoGAMES, EvoIASP, EvoINTELLIGENCE, EvoNUM, EvoSTOC, volume 6624, pages 274-283, Turin, Italy, 2011. Springer Verlag. details

  58. Christoph Neumueller and Stefan Wagner and Gabriel K. Kronberger and Michael Affenzeller. Parameter Meta-optimization of Metaheuristic Optimization Algorithms. In Roberto Moreno-Diaz and Franz Pichler and Alexis Quesada-Arencibia editors, Computer Aided Systems Theory, EUROCAST 2011, volume 6927, pages 367-374, Las Palmas de Gran Canaria, Spain, 2011. Revised Selected Papers, Part I. details

  59. M. Affenzeller and C. Fischer and G. K. Kronberger and S. M. Winkler and S. Wagner. New Genetic Programming Hypothesis Search Strategies for Improving the Interpretability in Medical Data Mining Applications. In Proccedings of 23rd IEEE European Modeling \& Simulation Symposium EMSS 2011, Roma, Italy, 2011. details

  60. Stephan M. Winkler and Michael Affenzeller and Gabriel K. Kronberger and Michael Kommenda and Stefan Wagner and Witold Jacak and Herbert Stekel. Analysis of Selected Evolutionary Algorithms in Feature Selection and Parameter Optimization for Data Based Tumor Marker Modeling. In Roberto Moreno-Diaz and Franz Pichler and Alexis Quesada-Arencibia editors, Proceedings of International Conference on Computer Aided Systems Theory, EUROCAST 2011, volume 6927, pages 335-342, Las Palmas, Spain, 2011. Springer. details

  61. Gabriel K. Kronberger and Stephan M. Winkler and Michael Affenzeller and Michael Kommenda and Stefan Wagner. Effects of Mutation before and after offspring selection in genetic programming for symbolic regression. In Agostino Bruzzone and Claudia Frydman editors, 22nd European Modeling \& Simulation Symposium (Simulation in Industry), EMSS 2010, Fes, Morocco, 2010. details

  62. Gabriel Kronberger and Stephan M. Winkler and Michael Affenzeller and Andreas Beham and Stefan Wagner. On the Success Rate of Crossover Operators for Genetic Programming with Offspring Selection. In 12th International Conference on Computer Aided Systems Theory, EUROCAST 2009, volume 5717, pages 793-800, Las Palmas de Gran Canaria, Spain, 2009. Springer. Revised Selected Papers. details

  63. Gabriel Kronberger and Stephan Winkler and Michael Affenzeller and Stefan Wagner. On Crossover Success Rate in Genetic Programming with Offspring Selection. In Leonardo Vanneschi and Steven Gustafson and Alberto Moraglio and Ivanoe De Falco and Marc Ebner editors, Proceedings of the 12th European Conference on Genetic Programming, EuroGP 2009, volume 5481, pages 232-243, Tuebingen, 2009. Springer. details

  64. Gabriel Kronberger and Christoph Feilmayr and Michael Kommenda and Stephan Winkler and Michael Affenzeller and Thomas Burgler. System Identification of Blast Furnace Processes with Genetic Programming. In 2nd International Symposium on Logistics and Industrial Informatics, LINDI 2009, pages 1-6, Linz, Austria, 2009. details

  65. Michael Kommenda and Gabriel Kronberger and Stephan Winkler and Michael Affenzeller and Stefan Wagner and Leonhard Schickmair and Benjamin Lindner. Application of Genetic Programming on Temper Mill Datasets. In 2nd International Conference on Logistics and Industrial Informatics, LINDI 2009, pages 1-5, 2009. details

Genetic Programming book chapters by Gabriel Kronberger

  1. J. Ignacio Hidalgo and J. Manuel Colmenar and J. Manuel Velasco and Gabriel Kronberger and Stephan M. Winkler and Oscar Garnica and Juan Lanchares. Identification of Models for Glucose Blood Values in Diabetics by Grammatical Evolution. In Conor Ryan and Michael O'Neill and J. J. Collins editors, Handbook of Grammatical Evolution, chapter 15, pages 367-393. Springer, 2018. details

  2. Gabriel Kronberger and Michael Kommenda. Search Strategies for Grammatical Optimization Problems - Alternatives to Grammar-Guided Genetic Programming. In Grzegorz Borowik and Zenon Chaczko and Witold Jacak and Tadeusz Luba editors, Computational Intelligence and Efficiency in Engineering Systems, volume 595 of Studies in Computational Intelligence, pages 89-102. Springer, 2015. details

  3. Michael Kommenda and Michael Affenzeller and Gabriel Kronberger and Bogdan Burlacu and Stephan M. Winkler. Multi-Population Genetic Programming with Data Migration for Symbolic Regression. In Grzegorz Borowik and Zenon Chaczko and Witold Jacak and Tadeusz Luba editors, Computational Intelligence and Efficiency in Engineering Systems, volume 595 of Studies in Computational Intelligence, pages 75-87. Springer, 2015. details

  4. Bogdan Burlacu and Michael Affenzeller and Stephan M. Winkler and Michael Kommenda and Gabriel Kronberger. Methods for Genealogy and Building Block Analysis in Genetic Programming. In Grzegorz Borowik and Zenon Chaczko and Witold Jacak and Tadeusz Luba editors, Computational Intelligence and Efficiency in Engineering Systems, volume 595 of Studies in Computational Intelligence, pages 61-74. Springer, 2015. details

  5. S. M. Winkler and M. Affenzeller and G. K. Kronberger and M. Kommenda and S. Wagner and W. Jacak and H. Stekel. On the Identification of Virtual Tumor Markers and Tumor Diagnosis Predictors Using Evolutionary Algorithms. In R. Klempous and J. Nikodem and W. Jacak and Z. Chaczko editors, Advanced Methods and Applications in Computational Intelligence, pages 95-122. Springer, 2014. details

  6. Michael Affenzeller and Stephan M. Winkler and Gabriel Kronberger and Michael Kommenda and Bogdan Burlacu and Stefan Wagner. Gaining Deeper Insights in Symbolic Regression. In Rick Riolo and Jason H. Moore and Mark Kotanchek editors, Genetic Programming Theory and Practice XI, chapter 10, pages 175-190. Springer, Ann Arbor, USA, 2013. details

  7. Gabriel K. Kronberger and Michael Affenzeller and Stefan Fink. Genetic programming: Current trends and applications in computational finance. In Nikolaos S. Thomaidis and Gordon H. Dash editors, Recent advances in computational finance, chapter 6, pages 99-115. Nova Science Publishers, Inc., 2013. details

  8. Stephan M. Winkler and Michael Affenzeller and Stefan Wagner and Gabriel K. Kronberger and Michael Kommenda. Using Genetic Programming in Nonlinear Model Identification. In Daniel Alberer and Hakan Hjalmarsson and Luigi del Re editors, Workshop on Identification in Automotive 2010, volume 418 of Lecture Notes in Control and Information Sciences, chapter 6, pages 89-109. Springer, Linz, Austria, 2010. details

Genetic Programming other entries for Gabriel Kronberger