Genetic Programming Bibliography entries for Randal S Olson

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GP coauthors/coeditors: Wolfgang Banzhaf, William Tozier, Rick L Riolo, Pieter Gijsbers, Joaquin Vanschoren, Jason H Moore, Maksim Shestov, Peter Schmitt, Yong Chen, Moshe Sipper, Ryan J Urbanowicz, Peter C Andrews, Nicole A Lavender, La Creis Renee Kidd, Nathan Bartley, William La Cava, Sharon Tartarone, Steven Vitale, Weixuan Fu, Patryk Orzechowski, John H Holmes, Alena Orlenko, Junmei Cairns, Pedro J Caraballo, Richard M Weinshilboum, Liewei Wang, Matthew K Breitenstein, Andrew Sohn,

Genetic Programming Articles by Randal S Olson

Genetic Programming Conference proceedings edited by Randal S Olson

Genetic Programming conference papers by Randal S Olson

  1. Jason H. Moore and Randal S. Olson and Yong Chen and Moshe Sipper. Discovering test statistics using genetic programming. 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 29-30, Prague, Czech Republic, 2019. ACM. details

  2. Alena Orlenko and Jason H. Moore and Patryk Orzechowski and Randal S. Olson and Junmei Cairns and Pedro J. Caraballo and Richard M. Weinshilboum and Liewei Wang and Matthew K. Breitenstein. Considerations for automated machine learning in clinical metabolic profiling: Altered homocysteine plasma concentration associated with metformin exposure. In Russ B. Altman and A. Keith Dunker and Lawrence Hunter and Marylyn D. Ritchie and Tiffany Murray and Teri E. Klein editors, Pacific Symposium on Biocomputing, pages 460-471, Hawaii, USA, 2018. World Scientific. details

  3. Jason H. Moore and Maksim Shestov and Peter Schmitt and Randal S. Olson. A heuristic method for simulating open-data of arbitrary complexity that can be used to compare and evaluate machine learning methods. In Russ B. Altman and A. Keith Dunker and Lawrence Hunter and Marylyn D. Ritchie and Tiffany Murray and Teri E. Klein editors, Pacific Symposium on Biocomputing, pages 259-267, Hawaii, USA, 2018. details

  4. Andrew Sohn and Randal S. Olson and Jason H. Moore. Toward the Automated Analysis of Complex Diseases in Genome-wide Association Studies Using Genetic Programming. In Proceedings of the Genetic and Evolutionary Computation Conference, pages 489-496, Berlin, Germany, 2017. ACM. details

  5. 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

  6. Pieter Gijsbers and Joaquin Vanschoren and Randal S. Olson. Layered TPOT: Speeding up Tree-based Pipeline Optimization. In Pavel Brazdil and Joaquin Vanschoren and Frank Hutter and Holger H. Hoos editors, Proceedings of the International Workshop on Automatic Selection, Configuration and Composition of Machine Learning Algorithms, volume 1998, pages 49-68, Skopje, Macedonia, 2017. CEUR-WS.org. co-located with the European Conference on Machine Learning \& Principles and Practice of Knowledge Discovery in Databases, AutoML@PKDD/ECML 2017. details

  7. Randal S. Olson and Jason H. Moore. TPOT: A Tree-based Pipeline Optimization Tool for Automating Data Science. In Frank Hutter and Lars Kotthoff and Joaquin Vanschoren editors, AutoML 2016 workshop, New York City, USA, 2016. Collocated with ICML. details

  8. Randal S. Olson and Nathan Bartley and Ryan J. Urbanowicz and Jason H. Moore. Evaluation of a Tree-based Pipeline Optimization Tool for Automating Data Science. 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: Proceedings of the 2016 Annual Conference on Genetic and Evolutionary Computation, pages 485-492, Denver, USA, 2016. ACM. details

  9. Randal S. Olson and Jason H. Moore. Identifying and Harnessing the Building Blocks of Machine Learning Pipelines for Sensible Initialization of a Data Science Automation Tool. In Rick Riolo and Bill Worzel and Brian Goldman and Bill Tozier editors, Genetic Programming Theory and Practice XIV, pages 211-223, Ann Arbor, USA, 2016. Springer. details

  10. Randal S. Olson and Ryan J. Urbanowicz and Peter C. Andrews and Nicole A. Lavender and La Creis Kidd and Jason H. Moore. Automating Biomedical Data Science Through Tree-Based Pipeline Optimization. In Giovanni Squillero and Paolo Burelli editors, Proceedings of the 19th European Conference on Applications of Evolutionary Computation, EvoApplications 2016, Part I, volume 9597, pages 123-137, Porto, Portugal, 2016. Springer. Best paper, EvoBio track. details

Genetic Programming book chapters by Randal S Olson

Genetic Programming other entries for Randal S Olson