Genetic Programming Bibliography entries for Andrew James Turner
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GP coauthors/coeditors:
Piotr Kaszuba,
Bartosz Mikulski,
Nl Shasha Jumbe,
Andreas Schuh,
Michael Morimoto,
Peter Rexelius,
Ryan Hafen,
Ron Deiotte,
Kevin Hammond,
Jerry Swan,
Krzysztof Krawiec,
Michael A Lones,
Jane E Alty,
Phillipa Duggan-Carter,
D R Stuart Jamieson,
Stephen L Smith,
Jeremy Cosgrove,
Philippa Duggan-Carter,
Rebecca Frances Naylor,
Julian F Miller,
Genetic Programming Articles by Andrew James Turner
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Andrew James Turner and Julian Francis Miller.
Recurrent Cartesian Genetic Programming of Artificial Neural Networks.
Genetic Programming and Evolvable Machines, 18(2):185-212, 2017.
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Michael A. Lones and Jane E. Alty and Jeremy Cosgrove and Philippa Duggan-Carter and Stuart Jamieson and Rebecca F. Naylor and Andrew J. Turner and Stephen L. Smith.
A New Evolutionary Algorithm-Based Home Monitoring Device for Parkinson's Dyskinesia.
Journal of Medical Systems, 41(11):176, 2017.
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Andrew James Turner and Julian Francis Miller.
Neutral genetic drift: an investigation using Cartesian Genetic Programming.
Genetic Programming and Evolvable Machines, 16(4):531-558, 2015.
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Andrew James Turner and Julian Francis Miller.
Introducing a cross platform open source Cartesian Genetic Programming library.
Genetic Programming and Evolvable Machines, 16(1):83-91, 2015.
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Andrew James Turner and Julian Francis Miller.
NeuroEvolution: Evolving Heterogeneous Artificial Neural Networks.
Evolutionary Intelligence, 7(3):135-154, 2014.
Special Issue: Evolution in UK 20.
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Genetic Programming PhD doctoral thesis Andrew James Turner
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Andrew James Turner.
Evolving Artificial Neural Networks using Cartesian Genetic Programming. PhD thesis,
Electronics, University of York, UK, 2015.
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Genetic Programming conference papers by Andrew James Turner
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Piotr Kaszuba and Andrew Turner and Bartosz Mikulski and Nl Shasha Jumbe and Andreas Schuh and Michael Morimoto and Peter Rexelius and Ryan Hafen and Ron Deiotte and Kevin Hammond and Jerry Swan and Krzysztof Krawiec.
Synthesizing Effective Diagnostic Models from Small Samples Using Structural Machine Learning: A Case Study in Automating COVID-19 Diagnosis. 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 727-730, Lisbon, Portugal, 2023. Association for Computing Machinery.
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Andrew James Turner and Julian Francis Miller.
Recurrent Cartesian Genetic Programming Applied to Series Forecasting. 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 Companion '15: Proceedings of the Companion Publication of the 2015 Annual Conference on Genetic and Evolutionary Computation, pages 1499-1500, Madrid, Spain, 2015. ACM.
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Julian Miller and Andrew Turner.
Cartesian Genetic Programming. In
Anabela Simoes editor,
GECCO 2015 Introductory Tutorials, pages 179-198, Madrid, Spain, 2015. ACM.
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Andrew Turner and Julian Miller.
Cartesian Genetic Programming: Why No Bloat?. In
Miguel Nicolau and Krzysztof Krawiec and Malcolm I. Heywood and Mauro Castelli and Pablo Garcia-Sanchez and Juan J. Merelo and Victor M. Rivas Santos and Kevin Sim editors,
17th European Conference on Genetic Programming, volume 8599, pages 222-233, Granada, Spain, 2014. Springer.
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Andrew Turner and Julian Miller.
Recurrent Cartesian Genetic Programming. In
Thomas Bartz-Beielstein and Juergen Branke and Bogdan Filipic and Jim Smith editors,
13th International Conference on Parallel Problem Solving from Nature, volume 8672, pages 476-486, Ljubljana, Slovenia, 2014. Springer.
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Michael A. Lones and Jane E. Alty and Phillipa Duggan-Carter and Andrew J. Turner and D. R. Stuart Jamieson and Stephen L. Smith.
Classification and characterisation of movement patterns during levodopa therapy for parkinson's disease. In
Stephen L. Smith and Stefano Cagnoni and Robert M. Patton editors,
GECCO 2014 Workshop on Medical Applications of Genetic and Evolutionary Computation (MedGEC), pages 1321-1328, Vancouver, BC, Canada, 2014. ACM.
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Andrew James Turner and Julian Francis Miller.
Cartesian genetic programming encoded artificial neural networks: a comparison using three benchmarks. In
Christian Blum and Enrique Alba and Anne Auger and Jaume Bacardit and Josh Bongard and Juergen Branke and Nicolas Bredeche and Dimo Brockhoff and Francisco Chicano and Alan Dorin and Rene Doursat and Aniko Ekart and Tobias Friedrich and Mario Giacobini and Mark Harman and Hitoshi Iba and Christian Igel and Thomas Jansen and Tim Kovacs and Taras Kowaliw and Manuel Lopez-Ibanez and Jose A. Lozano and Gabriel Luque and John McCall and Alberto Moraglio and Alison Motsinger-Reif and Frank Neumann and Gabriela Ochoa and Gustavo Olague and Yew-Soon Ong and Michael E. Palmer and Gisele Lobo Pappa and Konstantinos E. Parsopoulos and Thomas Schmickl and Stephen L. Smith and Christine Solnon and Thomas Stuetzle and El-Ghazali Talbi and Daniel Tauritz and Leonardo Vanneschi editors,
GECCO '13: Proceeding of the fifteenth annual conference on Genetic and evolutionary computation conference, pages 1005-1012, Amsterdam, The Netherlands, 2013. ACM.
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Andrew James Turner and Julian Francis Miller.
The Importance of Topology Evolution in NeuroEvolution: A Case Study Using Cartesian Genetic Programming of Artificial Neural Networks. In
Max Bramer and Miltos Petridis editors,
Research and Development in Intelligent Systems XXX, pages 213-226, Cambridge, 2013. Springer International Publishing.
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