Genetic Programming Bibliography entries for William La Cava

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GP coauthors/coeditors: Kourosh Danai, Fabricio Olivetti de Franca, Marco Virgolin, Michael Kommenda, 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, Bogdan Burlacu, Jaan Kasak, Meera Machado, Casper Wilstrup, Guilherme Seidyo Imai Aldeia, Karthik Kannappan, Lee Spector, Moshe Sipper, Thomas Helmuth, Jake Wisdom, Omri Bernstein, Matthew A Lackner, Paul Fleming, Alan Wright, Jason H Moore, Sara Silva, Leonardo Vanneschi, Tilak Raj Singh, James Taggart, Srinivas Suri, Patryk Orzechowski, Ying Jin, Paul C Lee, Imran Ajmal, Xiruo Ding, Priyanka Solanki, Jordana B Cohen, Daniel S Herman, Randal S Olson, Sharon Tartarone, Steven Vitale, Weixuan Fu, Ryan J Urbanowicz, John H Holmes, Pawel Renc, Arkadiusz Sitek, Jaroslaw Was, Joost Wagenaar, Nuno Miguel Rodrigues Domingos, Joao E Batista, Saul Shanabrook, Edward R Pantridge, Markus Wagner, Julia Handl, Kuber Karthik, Danilo Vasconcellos Vargas, Silvino Fernandez Alzueta, Pablo Valledor Pellicer, Thomas Stuetzle, John R Woodward, Daniel R Tauritz, Manuel Lopez-Ibanez, Anne Auger, Dimo Brockhoff, Nikolaus Hansen, Tea Tusar, Dejan Tusar, Stephane Doncieux, Joshua E Auerbach, Richard Duro, Harold de Vladar, Jose Santos Reyes, Amarda Shehu, Mostafa M Hashim Ellabaan, Stefan Wagner, Michael Affenzeller, Frank Neumann, Paul Kaufmann, Oliver Kramer, P G M Baltus, Giovanni Iacca, M N Andraud, Vanessa Volz, Boris Naujoks, Frank Moore, Gunes Kayacik, Nur Zincir-Heywood, Anna Esparcia-Alcazar, Westley Weimer, Justyna Petke, David Robert White, William B Langdon, Nadarajen Veerapen, Fabio Daolio, Arnaud Liefooghe, Sebastien Verel, Gabriela Ochoa, Giovanni Squillero, Alberto Tonda, Stephen L Smith, Stefano Cagnoni, Robert M Patton, John A W McCall, Dirk Thierens, Randal Olson, Ernesto Tarantino, Ivanoe De Falco, Antonio Della Cioppa, Umberto Scafuri, Nicolas Bredeche, Evert Haasdijk, Abraham Prieto, Heiko Hamann, Jared Moore, Anthony Clark, David Walker, Richard Everson, Jonathan E Fieldsend, Bogdan Filipic, Alma Rahat, Handing Wang, Yaochu Jin,

Genetic Programming Articles by William La Cava

  1. Nuno M. Rodrigues and Joao E. Batista and William La Cava and Leonardo Vanneschi and Sara Silva. Exploring SLUG: Feature Selection Using Genetic Algorithms and Genetic Programming. SN Computer Science, 5(1) 2023. details

  2. William G. La Cava and Paul C. Lee and Imran Ajmal and Xiruo Ding and Priyanka Solanki and Jordana B. Cohen and Jason H. Moore and Daniel S. Herman. A flexible symbolic regression method for constructing interpretable clinical prediction models. npj Digital Medicine, 6:Article number: 107, 2023. Silver 2023 HUMIES. details

  3. Kourosh Danai and William G. La Cava. Controller design by symbolic regression. Mechanical Systems and Signal Processing, 151:107348, 2021. details

  4. William La Cava and Jason H. Moore. Learning feature spaces for regression with genetic programming. Genetic Programming and Evolvable Machines, 21(3):433-467, 2020. Special Issue: Highlights of Genetic Programming 2019 Events. details

  5. William La Cava and Thomas Helmuth and Lee Spector and Jason H. Moore. A probabilistic and multi-objective analysis of lexicase selection and epsilon-lexicase selection. Evolutionary Computation, 27(3):377-402, 2019. details

  6. William La Cava and Sara Silva and Kourosh Danai and Lee Spector and Leonardo Vanneschi and Jason H. Moore. Multidimensional genetic programming for multiclass classification. Swarm and Evolutionary Computation, 44:260-272, 2019. details

  7. William La Cava and Kourosh Danai and Lee Spector and Paul Fleming and Alan Wright and Matthew Lackner. Automatic identification of wind turbine models using evolutionary multiobjective optimization. Renewable Energy, 87, Part 2:892-902, 2016. Optimization Methods in Renewable Energy Systems Design. details

  8. William La Cava and Kourosh Danai and Lee Spector. Inference of compact nonlinear dynamic models by epigenetic local search. Engineering Applications of Artificial Intelligence, 55:292-306, 2016. details

  9. 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. details

Genetic Programming PhD doctoral thesis William La Cava

Genetic Programming Conference proceedings edited by William La Cava

Genetic Programming conference papers by William La Cava

  1. Guilherme Seidyo Imai Aldeia and Fabricio Olivetti De Franca and William G. La Cava. Minimum variance threshold for epsilon-lexicase selection. 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 905-913, Melbourne, Australia, 2024. Association for Computing Machinery. details

  2. Guilherme Seidyo Imai Aldeia and Fabricio Olivetti De Franca and William G. La Cava. Inexact Simplification of Symbolic Regression Expressions with Locality-sensitive Hashing. 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 896-904, Melbourne, Australia, 2024. Association for Computing Machinery. details

  3. Patryk Orzechowski and Pawel Renc and William La Cava and Jason Moore and Arkadiusz Sitek and Jaroslaw Was and Joost Wagenaar. A Comparative Study of GP-based and State-of-the-art Classifiers on a Synthetic Machine Learning Benchmark. In Heike Trautmann and Carola Doerr and Alberto Moraglio and Thomas Bartz-Beielstein and Bogdan Filipic and Marcus Gallagher and Yew-Soon Ong and Abhishek Gupta and Anna V Kononova and Hao Wang and Michael Emmerich and Peter A. N. Bosman and Daniela Zaharie and Fabio Caraffini and Johann Dreo and Anne Auger and Konstantin Dietric and Paul Dufosse and Tobias Glasmachers and Nikolaus Hansen and Olaf Mersmann and Petr Posik and Tea Tusar and Dimo Brockhoff and Tome Eftimov and Pascal Kerschke and Boris Naujoks and Mike Preuss and Vanessa Volz and Bilel Derbel and Ke Li and Xiaodong Li and Saul Zapotecas and Qingfu Zhang and Mark Coletti and Catherine (Katie) Schuman and Eric ``Siggy'' Scott and Robert Patton and Paul Wiegand and Jeffrey K. Bassett and Chathika Gunaratne and Tinkle Chugh and Richard Allmendinger and Jussi Hakanen and Daniel Tauritz and John Woodward and Manuel Lopez-Ibanez and John McCall and Jaume Bacardit and Alexander Brownlee and Stefano Cagnoni and Giovanni Iacca and David Walker and Jamal Toutouh and UnaMay O'Reilly and Penousal Machado and Joao Correia and Sergio Nesmachnow and Josu Ceberio and Rafael Villanueva and Ignacio Hidalgo and Francisco Fernandez de Vega and Giuseppe Paolo and Alex Coninx and Antoine Cully and Adam Gaier and Stefan Wagner and Michael Affenzeller and Bobby R. Bruce and Vesna Nowack and Aymeric Blot and Emily Winter and William B. Langdon and Justyna Petke and Silvino Fernandez Alzueta and Pablo Valledor Pellicer and Thomas Stuetzle and David Paetzel and Alexander Wagner and Michael Heider and Nadarajen Veerapen and Katherine Malan and Arnaud Liefooghe and Sebastien Verel and Gabriela Ochoa and Mohammad Nabi Omidvar and Yuan Sun and Ernesto Tarantino and De Falco Ivanoe and Antonio Della Cioppa and Scafuri Umberto and John Rieffel and Jean-Baptiste Mouret and Stephane Doncieux and Stefanos Nikolaidis and Julian Togelius and Matthew C. Fontaine and Serban Georgescu and Francisco Chicano and Darrell Whitley and Oleksandr Kyriienko and Denny Dahl and Ofer Shir and Lee Spector and Alma Rahat and Richard Everson and Jonathan Fieldsend and Handing Wang and Yaochu Jin and Erik Hemberg and Marwa A. Elsayed and Michael Kommenda and William La Cava and Gabriel Kronberger and Steven Gustafson editors, Proceedings of the 2022 Genetic and Evolutionary Computation Conference Companion, pages 276-279, Boston, USA, 2022. Association for Computing Machinery. details

  4. Nuno Rodrigues and Joao Batista and William La Cava and Leonardo Vanneschi and Sara Silva. SLUG: Feature Selection Using Genetic Algorithms and Genetic Programming. In Eric Medvet and Gisele Pappa and Bing Xue editors, EuroGP 2022: Proceedings of the 25th European Conference on Genetic Programming, volume 13223, pages 68-84, Madrid, Spain, 2022. Springer Verlag. details

  5. Bill LaCava. When to stop: an analysis of thresholdout for symbolic regression. In Leonardo Trujillo and Stephan M. Winkler and Sara Silva and Wolfgang Banzhaf editors, Genetic Programming Theory and Practice XIX, Ann Arbor, USA, 2022. details

  6. 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. details

  7. William La Cava and Jason H. Moore. Genetic Programming Approaches to Learning Fair Classifiers. In Carlos Artemio Coello Coello and Arturo Hernandez Aguirre and Josu Ceberio Uribe and Mario Garza Fabre and Gregorio Toscano Pulido and Katya Rodriguez-Vazquez and Elizabeth Wanner and Nadarajen Veerapen and Efren Mezura Montes and Richard Allmendinger and Hugo Terashima Marin and Markus Wagner and Thomas Bartz-Beielstein and Bogdan Filipic and Heike Trautmann and Ke Tang and John Koza and Erik Goodman and William B. Langdon and Miguel Nicolau and Christine Zarges and Vanessa Volz and Tea Tusar and Boris Naujoks and Peter A. N. Bosman and Darrell Whitley and Christine Solnon and Marde Helbig and Stephane Doncieux and Dennis G. Wilson and Francisco Fernandez de Vega and Luis Paquete and Francisco Chicano and Bing Xue and Jaume Bacardit and Sanaz Mostaghim and Jonathan Fieldsend and Oliver Schuetze and Dirk Arnold and Gabriela Ochoa and Carlos Segura and Carlos Cotta and Michael Emmerich and Mengjie Zhang and Robin Purshouse and Tapabrata Ray and Justyna Petke and Fuyuki Ishikawa and Johannes Lengler and Frank Neumann editors, Proceedings of the 2020 Genetic and Evolutionary Computation Conference, pages 967-975, internet, 2020. Association for Computing Machinery. Best Paper. details

  8. William La Cava and Tilak Raj Singh and James Taggart and Srinivas Suri and Jason H. Moore. Learning concise representations for regression by evolving networks of tree. In Tara Sainath editor, 7th International Conference on Learning Representations, ICLR 2019, New Orleans, Louisiana, USA, 2019. details

  9. William La Cava and Jason H. Moore. Semantic variation operators for multidimensional genetic programming. 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 1056-1064, Prague, Czech Republic, 2019. ACM. details

  10. Patryk Orzechowski and William La Cava and Jason H. Moore. Where are we now?: a large benchmark study of recent symbolic regression methods. 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 1183-1190, Kyoto, Japan, 2018. ACM. details

  11. William La Cava and Sara Silva and Kourosh Danai and Lee Spector and Leonardo Vanneschi and Jason H. Moore. A multidimensional genetic programming approach for identifying epsistatic gene interactions. In Carlos Cotta and Tapabrata Ray and Hisao Ishibuchi and Shigeru Obayashi and Bogdan Filipic and Thomas Bartz-Beielstein and Grant Dick and Masaharu Munetomo and Silvino Fernandez Alzueta and Thomas Stuetzle and Pablo Valledor Pellicer and Manuel Lopez-Ibanez and Daniel R. Tauritz and Pietro S. Oliveto and Thomas Weise and Borys Wrobel and Ales Zamuda and Anne Auger and Julien Bect and Dimo Brockhoff and Nikolaus Hansen and Rodolphe Le Riche and Victor Picheny and Bilel Derbel and Ke Li and Hui Li and Xiaodong Li and Saul Zapotecas and Qingfu Zhang and Stephane Doncieux and Richard Duro and Joshua Auerbach and Harold de Vladar and Antonio J. Fernandez-Leiva and JJ Merelo and Pedro A. Castillo-Valdivieso and David Camacho-Fernandez and Francisco Chavez de la O and Ozgur Akman and Khulood Alyahya and Juergen Branke and Kevin Doherty and Jonathan Fieldsend and Giuseppe Carlo Marano and Nikos D. Lagaros and Koichi Nakayama and Chika Oshima and Stefan Wagner and Michael Affenzeller and Boris Naujoks and Vanessa Volz and Tea Tusar and Pascal Kerschke and Riyad Alshammari and Tokunbo Makanju and Brad Alexander and Saemundur O. Haraldsson and Markus Wagner and John R. Woodward and Shin Yoo and John McCall and Nayat Sanchez-Pi and Luis Marti and Danilo Vasconcellos and Masaya Nakata and Anthony Stein and Nadarajen Veerapen and Arnaud Liefooghe and Sebastien Verel and Gabriela Ochoa and Stephen L. Smith and Stefano Cagnoni and Robert M. Patton and William La Cava and Randal Olson and Patryk Orzechowski and Ryan Urbanowicz and Ivanoe De Falco and Antonio Della Cioppa and Ernesto Tarantino and Umberto Scafuri and P. G. M. Baltus and Giovanni Iacca and Ahmed Hallawa and Anil Yaman and Alma Rahat and Handing Wang and Yaochu Jin and David Walker and Richard Everson and Akira Oyama and Koji Shimoyama and Hemant Kumar and Kazuhisa Chiba and Pramudita Satria Palar editors, GECCO '18: Proceedings of the Genetic and Evolutionary Computation Conference Companion, pages 23-24, Kyoto, Japan, 2018. ACM. details

  12. Lee Spector and William La Cava and Saul Shanabrook and Thomas Helmuth and Edward Pantridge. Relaxations of Lexicase Parent Selection. In Wolfgang Banzhaf and Randal S. Olson and William Tozier and Rick Riolo editors, Genetic Programming Theory and Practice XV, pages 105-120, University of Michigan in Ann Arbor, USA, 2017. Springer. details

  13. Randal S. Olson and Moshe Sipper and William La Cava and Sharon Tartarone and Steven Vitale and Weixuan Fu and Patryk Orzechowski and Ryan J. Urbanowicz and John H. Holmes and Jason H. Moore. A System for Accessible Artificial Intelligence. In Wolfgang Banzhaf and Randal S. Olson and William Tozier and Rick Riolo editors, Genetic Programming Theory and Practice XV, pages 121-134, University of Michigan in Ann Arbor, USA, 2017. Springer. details

  14. William La Cava and Sara Silva and Leonardo Vanneschi and Lee Spector and Jason Moore. Genetic Programming Representations for Multi-dimensional Feature Learning in Biomedical Classification. In Giovanni Squillero editor, 20th European Conference on the Applications of Evolutionary Computation, volume 10199, pages 158-173, Amsterdam, 2017. Springer. details

  15. William La Cava and Jason H. Moore. Ensemble Representation Learning: An Analysis of Fitness and Survival for Wrapper-based Genetic Programming Methods. In Proceedings of the Genetic and Evolutionary Computation Conference, pages 961-968, Berlin, Germany, 2017. ACM. details

  16. William La Cava and Jason Moore. A General Feature Engineering Wrapper for Machine Learning Using epsilon-Lexicase Survival. In Mauro Castelli and James McDermott and Lukas Sekanina editors, EuroGP 2017: Proceedings of the 20th European Conference on Genetic Programming, volume 10196, pages 80-95, Amsterdam, 2017. Springer Verlag. details

  17. William La Cava and Lee Spector and Kourosh Danai. Epsilon-lexicase Selection for Regression. In Tobias Friedrich editor, GECCO '16: Proceedings of the 2016 Annual Conference on Genetic and Evolutionary Computation, pages 741-748, Denver, USA, 2016. ACM. details

  18. William La Cava and Thomas Helmuth and Lee Spector and Kourosh Danai. Genetic Programming with Epigenetic Local Search. In Sara Silva and Anna I Esparcia-Alcazar and Manuel Lopez-Ibanez and Sanaz Mostaghim and Jon Timmis and Christine Zarges and Luis Correia and Terence Soule and Mario Giacobini and Ryan Urbanowicz and Youhei Akimoto and Tobias Glasmachers and Francisco Fernandez de Vega and Amy Hoover and Pedro Larranaga and Marta Soto and Carlos Cotta and Francisco B. Pereira and Julia Handl and Jan Koutnik and Antonio Gaspar-Cunha and Heike Trautmann and Jean-Baptiste Mouret and Sebastian Risi and Ernesto Costa and Oliver Schuetze and Krzysztof Krawiec and Alberto Moraglio and Julian F. Miller and Pawel Widera and Stefano Cagnoni and JJ Merelo and Emma Hart and Leonardo Trujillo and Marouane Kessentini and Gabriela Ochoa and Francisco Chicano and Carola Doerr editors, GECCO '15: Proceedings of the 2015 Annual Conference on Genetic and Evolutionary Computation, pages 1055-1062, Madrid, Spain, 2015. ACM. details

  19. William La Cava and Lee Spector. Inheritable Epigenetics in Genetic Programming. In Rick Riolo and William P. Worzel and Mark Kotanchek editors, Genetic Programming Theory and Practice XII, pages 37-51, Ann Arbor, USA, 2014. Springer. details

  20. William La Cava and Lee Spector and Kourosh Danai and Matthew Lackner. Evolving differential equations with developmental linear genetic programming and epigenetic hill climbing. In Christian Igel and Dirk V. Arnold and Christian Gagne and Elena Popovici and Anne Auger and Jaume Bacardit and Dimo Brockhoff and Stefano Cagnoni and Kalyanmoy Deb and Benjamin Doerr and James Foster and Tobias Glasmachers and Emma Hart and Malcolm I. Heywood and Hitoshi Iba and Christian Jacob and Thomas Jansen and Yaochu Jin and Marouane Kessentini and Joshua D. Knowles and William B. Langdon and Pedro Larranaga and Sean Luke and Gabriel Luque and John A. W. McCall and Marco A. Montes de Oca and Alison Motsinger-Reif and Yew Soon Ong and Michael Palmer and Konstantinos E. Parsopoulos and Guenther Raidl and Sebastian Risi and Guenther Ruhe and Tom Schaul and Thomas Schmickl and Bernhard Sendhoff and Kenneth O. Stanley and Thomas Stuetzle and Dirk Thierens and Julian Togelius and Carsten Witt and Christine Zarges editors, GECCO Comp '14: Proceedings of the 2014 conference companion on Genetic and evolutionary computation companion, pages 141-142, Vancouver, BC, Canada, 2014. ACM. details

  21. Karthik Kannappan and Lee Spector and Moshe Sipper and Thomas Helmuth and William La Cava and Jake Wisdom and Omri Bernstein. Analyzing a Decade of Human-Competitive (``HUMIE'') Winners: What Can We Learn?. In Rick Riolo and William P. Worzel and Mark Kotanchek editors, Genetic Programming Theory and Practice XII, pages 149-166, Ann Arbor, USA, 2014. Springer. details

Genetic Programming other entries for William La Cava