Genetic Programming Bibliography entries for Michael Kommenda
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GP coauthors/coeditors:
Michael Affenzeller,
Stephan M Winkler,
Stefan Forstenlechner,
Gabriel Kronberger,
Stefan Wagner,
Herbert Stekel,
Bogdan Burlacu,
Viktoria Dorfer,
Sebastian Dorl,
Gerhard Halmerbauer,
Tilman Koenigswieser,
Julia Vetter,
Gerd Bramerdorfer,
Guenther Weidenholzer,
Siegfried Silber,
Wolfgang Amrhein,
Fabricio Olivetti de Franca,
Marco Virgolin,
Maimuna Majumder,
Miles Cranmer,
Guilherme Jorge Nunes Monteiro Espada,
Leon Ingelse,
Alcides Fonseca,
Mikel Landajuela,
Brenden Kyle Petersen,
Ruben Glatt,
T Nathan Mundhenk,
Chak Shing Lee,
Jacob Dean Hochhalter,
David L Randall,
Pierre-Alexandre Kamienny,
Hengzhe Zhang,
Grant Dick,
Alessandro Simon,
Jaan Kasak,
Meera Machado,
Casper Wilstrup,
William La Cava,
Philipp Fleck,
Sara Silva,
Leonardo Vanneschi,
Evgeniya Kabliman,
Ana Helena Kolody,
Johannes Kronsteiner,
Lukas Kammerer,
Leonhard Schickmair,
Benjamin Lindner,
Christoph Feilmayr,
Andreas Beham,
Reinhard Holecek,
Andreas Gebeshuber,
Johannes Karder,
Thomas Burgler,
Stefan Fink,
Andreas Scheibenpflug,
Heinz Dobler,
Andreas Promberger,
Falk Nickel,
Edwin Lughofer,
Susanne Saminger-Platz,
Christian Haider,
Patryk Orzechowski,
Ying Jin,
Jason H Moore,
Wolfgang Roland,
Gerald Roman Berger-Weber,
Erik Pitzer,
Stefan Vonolfen,
Monika Kofler,
Witold Jacak,
Ciprian Zavoianu,
Daniela Zaharie,
Genetic Programming Articles by Michael Kommenda
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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F. O. de Franca and M. Virgolin and M. Kommenda and M. S. Majumder and M. Cranmer and G. Espada and L. Ingelse and A. Fonseca and M. Landajuela and B. Petersen and R. Glatt and N. Mundhenk and C. S. Lee and J. D. Hochhalter and D. L. Randall and P. Kamienny and H. Zhang and G. Dick and A. Simon and B. Burlacu and Jaan Kasak and Meera Machado and Casper Wilstrup and W. G. La Cava.
SRBench++: Principled Benchmarking of Symbolic Regression With Domain-Expert Interpretation.
IEEE Transactions on Evolutionary Computation.
Early Access.
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Genetic Programming Books by Michael Kommenda
Genetic Programming conference papers by Michael Kommenda
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Philipp Fleck and Stephan Winkler and Michael Kommenda and Sara Silva and Leonardo Vanneschi and Michael Affenzeller.
Evolutionary Algorithms for Segment Optimization in Vectorial GP. 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 439-442, Lisbon, Portugal, 2023. Association for Computing Machinery.
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Wolfgang Roland and Michael Kommenda and Gerald R. Berger-Weber.
Application of Symbolic Regression in Polymer Processing. In
Bruno Buchberger and Mircea Marin and Viorel Negru and Daniela Zaharie editors,
24th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing, SYNASC 2022, pages 311-318, Hagenberg / Linz, Austria, 2022. IEEE.
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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.
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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.
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William La Cava and Patryk Orzechowski and Bogdan Burlacu and Fabricio de Franca and Marco Virgolin and Ying Jin and Michael Kommenda and Jason Moore.
Contemporary Symbolic Regression Methods and their Relative Performance. In
Joaquin Vanschoren and Sai-Kit Yeung editors,
Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks, volume 1, 2021. Curran.
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Philipp Fleck and Stephan Winkler and Michael Kommenda and Michael Affenzeller.
Grammar-based Vectorial Genetic Programming for Symbolic Regression. In
Wolfgang Banzhaf and Leonardo Trujillo and Stephan Winkler and Bill Worzel editors,
Genetic Programming Theory and Practice XVIII, pages 21-43, East Lansing, USA, 2021. Springer.
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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.
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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.
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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.
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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.
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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.
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Michael Affenzeller and Bogdan Burlacu and Viktoria Dorfer and Sebastian Dorl and Gerhard Halmerbauer and Tilman Koenigswieser and Michael Kommenda and Julia Vetter and Stephan M. Winkler.
White Box vs. Black Box Modeling: On the Performance of Deep Learning, Random Forests, and Symbolic Regression in Solving Regression Problems. In
Roberto Moreno-Diaz and Franz Pichler and Alexis Quesada-Arencibia editors,
17th International Conference, Computer Aided Systems Theory - EUROCAST 2019, volume 12013, pages 288-295, Las Palmas de Gran Canaria, Spain, 2019. Springer.
Revised Selected Papers, Part I.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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Bogdan Burlacu and Michael Affenzeller and Michael Kommenda.
On the Effectiveness of Genetic Operations in Symbolic Regression. In
Roberto Moreno-Diaz and Franz Pichler and Alexis Quesada-Arencibia editors,
15th International Conference Computer Aided Systems Theory, EUROCAST 2015, volume 9520, pages 367-374, Las Palmas de Gran Canaria, Spain, 2015. Springer.
Revised Selected Papers.
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Bogdan Burlacu and Michael Kommenda and Michael Affenzeller.
Building Blocks Identification Based on Subtree Sample Counts for Genetic Programming. In
2015 Asia-Pacific Conference on Computer Aided System Engineering (APCASE), pages 152-157, 2015.
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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.
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Michael Kommenda and Bogdan Burlacu and Reinhard Holecek and Andreas Gebeshuber and Michael Affenzeller.
Heat Treatment Process Parameter Estimation using Heuristic Optimization Algorithms. In
Proceedings of the 27th European Modeling and Simulation Symposium EMSS 2015, pages 222-228, Bergeggi, Italy, 2015.
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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.
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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.
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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.
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Bogdan Burlacu and Michael Affenzeller and Michael Kommenda.
On the Evolutionary Behavior of Genetic Programming with Constants Optimization. In
Roberto Moreno-Diaz and Franz Pichler and Alexis Quesada-Arencibia editors,
Computer Aided Systems Theory, EUROCAST 2013, volume 8111, pages 284-291, Las Palmas de Gran Canaria, Spain, 2013. Springer.
14th International Conference, Revised Selected Papers.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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Genetic Programming book chapters by Michael Kommenda
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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.
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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.
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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.
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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.
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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.
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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.
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Genetic Programming other entries for Michael Kommenda