Genetic Programming Bibliography entries for Tanja Alderliesten

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GP coauthors/coeditors: Joe Harrison, Peter A N Bosman, Marco Virgolin, Johannes Koch, Dazhuang Liu, Thalea Schlender, Mafalda Malafaia, Evi Sijben, J C Jansen, Jeroen Jansen, Thomas Uriot, Cees Witteveen, Arjan Bel, Ziyuan Wang, B V Balgobind, I W E M van Dijk, Jan Wiersma, P S Kroon, Geert O Janssens, M van Herk, David C Hodgson, Lorna Zadravec Zaletel, C R N Rasch, Eric Medvet,

Genetic Programming Articles by Tanja Alderliesten

  1. M. Virgolin and T. Alderliesten and C. Witteveen and P. A. N. Bosman. Improving Model-based Genetic Programming for Symbolic Regression of Small Expressions. Evolutionary Computation, 29(2):211-237, 2021. details

  2. M Virgolin and Ziyuan Wang and B V Balgobind and I W E M van Dijk and J Wiersma and P S Kroon and G O Janssens and M van Herk and D C Hodgson and L Zadravec Zaletel and C R N Rasch and A Bel and P A N Bosman and T Alderliesten. Surrogate-free machine learning-based organ dose reconstruction for pediatric abdominal radiotherapy. Physics in Medicine \& Biology, 65(24):245021, 2020. details

  3. Marco Virgolin and Ziyuan Wang and Tanja Alderliesten and Peter A. N. Bosman. Machine learning for the prediction of pseudorealistic pediatric abdominal phantoms for radiation dose reconstruction. Journal of Medical Imaging, 7(4):046501, 2020. Winner Silver HUMIES. details

  4. Marco Virgolin and Tanja Alderliesten and Peter A. N. Bosman. On explaining machine learning models by evolving crucial and compact features. Swarm and Evolutionary Computation, 53:100640, 2020. details

Genetic Programming conference papers by Tanja Alderliesten

  1. Evi Sijben and Jeroen Jansen and Peter Bosman and Tanja Alderliesten. Function Class Learning with Genetic Programming: Towards Explainable Meta Learning for Tumor Growth Functionals. In Ruhul Sarker and Patrick Siarry and Julia Handl and Xiaodong Li and Markus Wagner and Mario Garza-Fabre and Kate Smith-Miles and Richard Allmendinger and Ying Bi and Grant Dick and Amir H Gandomi and Marcella Scoczynski Ribeiro Martins and Hirad Assimi and Nadarajen Veerapen and Yuan Sun and Mario Andres Munyoz and Ahmed Kheiri and Nguyen Su and Dhananjay Thiruvady and Andy Song and Frank Neumann and Carla Silva editors, Proceedings of the 2024 Genetic and Evolutionary Computation Conference, pages 1354-1362, Melbourne, Australia, 2024. Association for Computing Machinery. details

  2. Thalea Schlender and Mafalda Malafaia and Tanja Alderliesten and Peter Bosman. Improving the efficiency of GP-GOMEA for higher-arity operators. In Ting Hu and Aniko Ekart and Julia Handl and Xiaodong Li and Markus Wagner and Mario Garza-Fabre and Kate Smith-Miles and Richard Allmendinger and Ying Bi and Grant Dick and Amir H Gandomi and Marcella Scoczynski Ribeiro Martins and Hirad Assimi and Nadarajen Veerapen and Yuan Sun and Mario Andres Munyoz and Ahmed Kheiri and Nguyen Su and Dhananjay Thiruvady and Andy Song and Frank Neumann and Carla Silva editors, Proceedings of the 2024 Genetic and Evolutionary Computation Conference, pages 971-979, Melbourne, Australia, 2024. Association for Computing Machinery. details

  3. Johannes Koch and Tanja Alderliesten and Peter Bosman. Simultaneous Model-Based Evolution of Constants and Expression Structure in GP-GOMEA 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

  4. Joe Harrison and Marco Virgolin and Tanja Alderliesten and Peter Bosman. Mini-Batching, Gradient-Clipping, First- versus Second-Order: What Works in Gradient-Based Coefficient Optimisation for Symbolic Regression?. 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 1127-1136, Lisbon, Portugal, 2023. Association for Computing Machinery. details

  5. Thomas Uriot and Marco Virgolin and Tanja Alderliesten and Peter Bosman. On genetic programming representations and fitness functions for interpretable dimensionality reduction. 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 458-466, Boston, USA, 2022. Association for Computing Machinery. details

  6. Evi Sijben and Tanja Alderliesten and Peter Bosman. Multi-modal multi-objective model-based genetic programming to find multiple diverse high-quality models. 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 440-448, Boston, USA, 2022. Association for Computing Machinery. details

  7. Dazhuang Liu and Marco Virgolin and Tanja Alderliesten and Peter Bosman. Evolvability Degeneration in Multi-Objective Genetic Programming for 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 973-981, Boston, USA, 2022. Association for Computing Machinery. Best Paper GP Track. details

  8. Joe Harrison and Tanja Alderliesten and Peter A. N. Bosman. Gene-pool Optimal Mixing in Cartesian Genetic Programming. In Guenter Rudolph and Anna V. Kononova and Hernan E. Aguirre and Pascal Kerschke and Gabriela Ochoa and Tea Tusar editors, Parallel Problem Solving from Nature - PPSN XVII - 17th International Conference, PPSN 2022, Proceedings, Part II, volume 13399, pages 19-32, Dortmund, Germany, 2022. Springer. details

  9. Marco Virgolin and Ziyuan Wang and Tanja Alderliesten and Peter A. N. Bosman. Machine learning for automatic construction of pediatric abdominal phantoms for radiation dose reconstruction. In P-H. Chen and T. M. Deserno editors, Medical Imaging 2020: Imaging Informatics for Healthcare, Research, and Applications, volume 11318, 2020. details

  10. Marco Virgolin and Tanja Alderliesten and Peter A. N. Bosman. Linear scaling with and within semantic backpropagation-based genetic programming for symbolic regression. In Manuel Lopez-Ibanez and Thomas Stuetzle and Anne Auger and Petr Posik and Leslie Peprez Caceres and Andrew M. Sutton and Nadarajen Veerapen and Christine Solnon and Andries Engelbrecht and Stephane Doncieux and Sebastian Risi and Penousal Machado and Vanessa Volz and Christian Blum and Francisco Chicano and Bing Xue and Jean-Baptiste Mouret and Arnaud Liefooghe and Jonathan Fieldsend and Jose Antonio Lozano and Dirk Arnold and Gabriela Ochoa and Tian-Li Yu and Holger Hoos and Yaochu Jin and Ting Hu and Miguel Nicolau and Robin Purshouse and Thomas Baeck and Justyna Petke and Giuliano Antoniol and Johannes Lengler and Per Kristian Lehre editors, GECCO '19: Proceedings of the Genetic and Evolutionary Computation Conference, pages 1084-1092, Prague, Czech Republic, 2019. ACM. details

  11. Marco Virgolin and Tanja Alderliesten and Arjan Bel and Cees Witteveen and Peter A. N. Bosman. Symbolic regression and feature construction with GP-GOMEA applied to radiotherapy dose reconstruction of childhood cancer survivors. 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 1395-1402, Kyoto, Japan, 2018. ACM. details

  12. Marco Virgolin and Tanja Alderliesten and Cees Witteveen and Peter A. N. Bosman. Scalable Genetic Programming by Gene-pool Optimal Mixing and Input-space Entropy-based Building-block Learning. In Proceedings of the Genetic and Evolutionary Computation Conference, pages 1041-1048, Berlin, Germany, 2017. ACM. details

Genetic Programming other entries for Tanja Alderliesten

  1. E. M. C. Sijben and J. C. Jansen and Peter A. N. Bosman and Tanja Alderliesten. Function Class Learning with Genetic Programming: Towards Explainable Meta Learning for Tumor Growth Functionals. 2024. details

  2. Dazhuang Liu and Marco Virgolin and Tanja Alderliesten and Peter A. N. Bosman. Evolvability Degeneration in Multi-Objective Genetic Programming for Symbolic Regression. 2022. details

  3. Marco Virgolin and Eric Medvet and Tanja Alderliesten and Peter A. N. Bosman. Less is More: A Call to Focus on Simpler Models in Genetic Programming for Interpretable Machine Learning. 2022. details

  4. Thomas Uriot and Marco Virgolin and Tanja Alderliesten and Peter A. N. Bosman. On genetic programming representations and fitness functions for interpretable dimensionality reduction. 2022. details

  5. Marco Virgolin and Tanja Alderliesten and Cees Witteveen and Peter A. N. Bosman. A Model-based Genetic Programming Approach for Symbolic Regression of Small Expressions. 2019. details