Genetic Programming Bibliography entries for Ting Hu 
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GP coauthors/coeditors: 
Wolfgang Banzhaf,
Gabriela Ochoa,
Christian Darabos,
Mario Giacobini,
Jason H Moore,
Shengkai Geng,
Simon Harding,
Joshua L Payne,
Karoliina Oksanen,
Weidong Zhang,
Edward Randell,
Andrew Furey,
Guangju Zhai,
Marco Tomassini,
Lukas Sekanina,
Miguel Nicolau,
Nuno Lourenco,
Eric Medvet,
Stephan M Winkler,
Leonardo Trujillo,
Charles Ofria,
Krzysztof Krawiec,
Alberto Moraglio,
A Sima Etaner-Uyar,
Bin Hu,
Michael Y Lee,
Kyle L Nickerson,
Antonina Kolokolova,
Gisele L Pappa,
Domagoj Jakobovic,
Mengjie Zhang,
Jinting Zhang,
Yu Zhang2,
Xiaodong Liang,
Mohammad Zawad Ali,
Md Nasmus Sakib Khan Shabbir,
Yuanzhu Chen,
Ryan Zhou,
Christian Muise,
Genetic Programming Articles by Ting Hu
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  Gisele L. Pappa and  Mario Giacobini and  Ting Hu and                  Domagoj Jakobovic.
Editorial introduction for the special issue on                 highlights of genetic programming 2023 events.
Genetic Programming and Evolvable Machines, 26:Article no: 13, 2025.
EditorialOnline first.
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  Leonardo Trujillo and  Ting Hu and  Nuno Lourenco and                  Mengjie Zhang.
Editorial Introduction.
Genetic Programming and Evolvable Machines, 23(3):305-307, 2022.
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  Ting Hu and  Miguel Nicolau and  Lukas Sekanina.
Special issue on highlights of genetic programming                 2019 events.
Genetic Programming and Evolvable Machines, 21(3):283-285, 2020.
Guest Editorial.
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  Ting Hu and  Marco Tomassini and  Wolfgang Banzhaf.
A network perspective on genotype-phenotype mapping in                 genetic programming.
Genetic Programming and Evolvable Machines, 21(3):375-397, 2020.
Special Issue: Highlights of Genetic Programming 2019                 Events.
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  Michael Y. Lee and  Ting Hu.
Computational Methods for the Discovery of Metabolic                 Markers of Complex Traits.
Metabolites, 9(4)  2019.
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  Ting Hu and  Lukas Sekanina.
EuroGP 2019 Panel Discussion: What is the Killer                 Application of GP?.
SIGEVOlution newsletter of the ACM Special Interest                 Group on Genetic and Evolutionary Computation, 12(2):3-7, 2019.
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  Ting Hu and  Wolfgang Banzhaf and  Jason H. Moore.
The effects of recombination on phenotypic exploration                 and robustness in evolution.
Artificial Life, 20(4):457-470, 2014.
Ten thousandth GP entry in the genetic programming                 bibliography.
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  Ting Hu and  Joshua Payne and  Wolfgang Banzhaf and                  Jason Moore.
Evolutionary dynamics on multiple scales: a                 quantitative analysis of the interplay between                 genotype, phenotype, and fitness in linear genetic                 programming.
Genetic Programming and Evolvable Machines, 13(3):305-337, 2012.
Special issue on selected papers from the 2011                 European conference on genetic programming.
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  Ting Hu and  Wolfgang Banzhaf.
Evolvability and Speed of Evolutionary Algorithms in                 Light of Recent Developments in Biology.
Journal of Artificial Evolution and Applications, 2010:Article ID 568375, 2010.
Review Article.
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  Ting Hu and  Simon Harding and  Wolfgang Banzhaf.
Variable population size and evolution acceleration: a                 case study with a parallel evolutionary algorithm.
Genetic Programming and Evolvable Machines, 11(2):205-225, 2010.
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Genetic Programming PhD doctoral thesis Ting Hu
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  Ting Hu.
Evolvability and Rate of Evolution in Evolutionary                 Computation. PhD thesis,
Department of Computer Science, Memorial University of                 Newfoundland, ST. John's, Newfoundland, Canada, 2010.
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Genetic Programming Conference proceedings edited by Ting Hu
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 Stephan Winkler and  Leonardo Trujillo and                  Charles Ofria and Ting Hu editors,
Genetic Programming Theory and Practice XX. Michigan State University, USA, Springer, 2023.
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 Ting Hu and  Nuno Lourenco and  Eric Medvet editors,
EuroGP 2021: Proceedings of the 24th European                 Conference on Genetic Programming. Volume 12691 of LNCS, Virtual Event, Springer Verlag, 2021.
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 Ting Hu and  Nuno Lourenco and  Eric Medvet editors,
EuroGP 2020: Proceedings of the 23rd European                 Conference on Genetic Programming. Volume 12101 of LNCS, Seville, Spain, Springer Verlag, 2020.
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 Lukas Sekanina and  Ting Hu and  Nuno Lourenco editors,
EuroGP 2019: Proceedings of the 22nd European                 Conference on Genetic Programming. Volume 11451 of LNCS, Leipzig, Germany, Springer Verlag, 2019.
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 Krzysztof Krawiec and  Alberto Moraglio and  Ting Hu and                  A. Sima Uyar and Bin Hu editors,
Proceedings of the 16th European Conference on Genetic                 Programming, EuroGP 2013. Volume 7831 of LNCS, Vienna, Austria, Springer, 2013.
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Genetic Programming conference papers by Ting Hu
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  Ting Hu and  Wolfgang Banzhaf and  Gabriela Ochoa.
How Neutrality Shapes Evolution: Simplicity Bias and                 Search. In
 Aniko Ekart and  Nelishia Pillay editors,
Proceedings of the 2025 Genetic and Evolutionary                 Computation Conference, pages 1008-1016, Malaga, Spain, 2025. Association for Computing Machinery.
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  Wolfgang Banzhaf and  Ting Hu.
Linear Genetic Programming. In
 Mengjie Zhang and  Emma Hart editors,
Proceedings of the 2025 Genetic and Evolutionary                 Computation Conference Companion, pages 1749-1766, Malaga, Spain, 2025. Association for Computing Machinery.
Tutorial.
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  Wolfgang Banzhaf and  Ting Hu.
Linear Genetic Programming. In
 Mengjie Zhang and  Emma Hart editors,
Proceedings of the 2024 Genetic and Evolutionary                 Computation Conference Companion, pages 759-771, Melbourne, Australia, 2024. Association for Computing Machinery.
Tutorial.
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  Ting Hu and  Gabriela Ochoa and  Wolfgang Banzhaf.
Phenotype Search Trajectory Networks for Linear                 Genetic Programming. In
 Gisele Pappa and  Mario Giacobini and  Zdenek Vasicek editors,
EuroGP 2023: Proceedings of the 26th European                 Conference on Genetic Programming, volume 13986, pages 52-67, Brno, Czech Republic, 2023. Springer Verlag.
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  Wolfgang Banzhaf and  Ting Hu and  Gabriela Ochoa.
How the Combinatorics of Neutral Spaces Leads Genetic                 Programming to Discover Simple Solutions. In
 Stephan Winkler and  Leonardo Trujillo and                  Charles Ofria and Ting Hu editors,
Genetic Programming Theory and Practice XX, pages 65-86, Michigan State University, USA, 2023. Springer.
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  Jinting Zhang and  Ting Hu.
Regulatory Genotype-to-Phenotype Mappings Improve                 Evolvability in Genetic Programming. 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 623-626, Boston, USA, 2022. Association for Computing Machinery.
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  Ryan Zhou and  Christian Muise and  Ting Hu.
Permutation-Invariant Representation of Neural                 Networks with Neuron Embeddings. In
 Eric Medvet and  Gisele Pappa and  Bing Xue editors,
EuroGP 2022: Proceedings of the 25th European                 Conference on Genetic Programming, volume 13223, pages 294-308, Madrid, Spain, 2022. Springer Verlag.
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  Kyle Nickerson and  Antonina Kolokolova and  Ting Hu.
Creating Diverse Ensembles for Classification with                 Genetic Programming and Neuro-MAP-Elites. In
 Eric Medvet and  Gisele Pappa and  Bing Xue editors,
EuroGP 2022: Proceedings of the 25th European                 Conference on Genetic Programming, volume 13223, pages 212-227, Madrid, Spain, 2022. Springer Verlag.
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  Ting Hu.
Genetic Programming for Interpretable and Explainable                 Machine Learning. In
 Leonardo Trujillo and  Stephan M. Winkler and                  Sara Silva and Wolfgang Banzhaf editors,
Genetic Programming Theory and Practice XIX, pages 81-90, Ann Arbor, USA, 2022. Springer.
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  Kyle L. Nickerson and  Ting Hu.
Principled quality diversity for ensemble classifiers                 using MAP-Elites. In
 Francisco Chicano and  Alberto Tonda and                  Krzysztof Krawiec and Marde Helbig and                  Christopher W. Cleghorn and Dennis G. Wilson and Georgios Yannakakis and                  Luis Paquete and Gabriela Ochoa and Jaume Bacardit and                  Christian Gagne and Sanaz Mostaghim and                  Laetitia Jourdan and Oliver Schuetze and Petr Posik and                  Carlos Segura and Renato Tinos and Carlos Cotta and                  Malcolm Heywood and Mengjie Zhang and Leonardo Trujillo and                  Risto Miikkulainen and Bing Xue and Aneta Neumann and                  Richard Allmendinger and Fuyuki Ishikawa and                  Inmaculada Medina-Bulo and Frank Neumann and Andrew M. Sutton editors,
Proceedings of the 2021 Genetic and Evolutionary                 Computation Conference Companion, pages 259-260, internet, 2021. Association for Computing Machinery.
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  Yu Zhang2 and  Yuanzhu Chen and  Ting Hu.
Classification of Autism Genes using Network Science                 and Linear Genetic Programming. In
 Ting Hu and  Nuno Lourenco and  Eric Medvet editors,
EuroGP 2020: Proceedings of the 23rd European                 Conference on Genetic Programming, volume 12101, pages 279-294, Seville, Spain, 2020. Springer Verlag.
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  Shengkai Geng and  Ting Hu.
Sports Games Modeling and Prediction using Genetic                 Programming. In
 Yaochu Jin editor,
2020 IEEE Congress on Evolutionary Computation, CEC                 2020, page paper id24100, internet, 2020. IEEE Press.
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  Yu Zhang2 and  Ting Hu and  Xiaodong Liang and                  Mohammad Zawad Ali and Md Nasmus Sakib Khan Shabbir.
Fault Detection and Classification for Induction                 Motors using Genetic Programming. In
 Lukas Sekanina and  Ting Hu and  Nuno Lourenco editors,
EuroGP 2019: Proceedings of the 22nd European                 Conference on Genetic Programming, volume 11451, pages 178-193, Leipzig, Germany, 2019. Springer Verlag.
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  Ting Hu.
Can Genetic Programming Perform Explainable Machine                 Learning for Bioinformatics?. In
 Wolfgang Banzhaf and  Erik Goodman and                  Leigh Sheneman and Leonardo Trujillo and Bill Worzel editors,
Genetic Programming Theory and Practice XVII, pages 63-77, East Lansing, MI, USA, 2019. Springer.
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  Ting Hu and  Marco Tomassini and  Wolfgang Banzhaf.
Complex Network Analysis of a Genetic Programming                 Phenotype Network. In
 Lukas Sekanina and  Ting Hu and  Nuno Lourenco editors,
EuroGP 2019: Proceedings of the 22nd European                 Conference on Genetic Programming, volume 11451, pages 49-63, Leipzig, Germany, 2019. Springer Verlag.
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  Ting Hu and  Karoliina Oksanen and  Weidong Zhang and                  Edward Randell and Andrew Furey and Guangju Zhai.
Analyzing Feature Importance for Metabolomics using                 Genetic Programming. In
 Mauro Castelli and  Lukas Sekanina and                  Mengjie Zhang and Stefano Cagnoni and Pablo Garcia-Sanchez editors,
EuroGP 2018: Proceedings of the 21st European                 Conference on Genetic Programming, volume 10781, pages 68-83, Parma, Italy, 2018. Springer Verlag.
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  Karoliina Oksanen and  Ting Hu.
Lexicase selection promotes effective search and                 behavioural diversity of solutions in Linear Genetic                 Programming. In
 Jose A. Lozano editor,
2017 IEEE Congress on Evolutionary Computation (CEC), pages 169-176, Donostia, San Sebastian, Spain, 2017. IEEE.
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  Ting Hu and  Wolfgang Banzhaf.
Neutrality, Robustness, and Evolvability in Genetic                 Programming. In
 Rick Riolo and  Bill Worzel and  Brian Goldman and                  Bill Tozier editors,
Genetic Programming Theory and Practice XIV, pages 101-117, Ann Arbor, USA, 2016. Springer.
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  Ting Hu and  Wolfgang Banzhaf.
Quantitative Analysis of Evolvability using Vertex                 Centralities in Phenotype Network. In
 Tobias Friedrich editor,
GECCO '16: Proceedings of the 2016 Annual Conference                 on Genetic and Evolutionary Computation, pages 733-740, Denver, USA, 2016. ACM.
Nominated for best paper.
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  Ting Hu and  Wolfgang Banzhaf and  Jason Moore.
Population Exploration on Genotype Networks in 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 424-333, Ljubljana, Slovenia, 2014. Springer.
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  Ting Hu and  Wolfgang Banzhaf and  Jason H. Moore.
Robustness and Evolvability of Recombination in Linear                 Genetic Programming. In
 Krzysztof Krawiec and  Alberto Moraglio and  Ting Hu and                  A. Sima Uyar and Bin Hu editors,
Proceedings of the 16th European Conference on Genetic                 Programming, EuroGP 2013, volume 7831, pages 97-108, Vienna, Austria, 2013. Springer Verlag.
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  Christian Darabos and  Mario Giacobini and  Ting Hu and                  Jason H. Moore.
Levy-Flight Genetic Programming: Towards a New                 Mutation Paradigm. In
 Mario Giacobini and  Leonardo Vanneschi and                  William S. Bush editors,
10th European Conference on Evolutionary Computation,                 Machine Learning and Data Mining in Bioinformatics,                 EvoBIO 2012, volume 7246, pages 38-49, Malaga, Spain, 2012. Springer Verlag.
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  Ting Hu and  Joshua Payne and  Jason Moore and                  Wolfgang Banzhaf.
Robustness, Evolvability, and Accessibility in Linear                 Genetic Programming. In
 Sara Silva and  James A. Foster and  Miguel Nicolau and                  Mario Giacobini and Penousal Machado editors,
Proceedings of the 14th European Conference on Genetic                 Programming, EuroGP 2011, volume 6621, pages 13-24, Turin, Italy, 2011. Springer Verlag.
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  Ting Hu and  Wolfgang Banzhaf.
The Role of Population Size in Rate of Evolution in                 Genetic Programming. In
 Leonardo Vanneschi and  Steven Gustafson and                  Alberto Moraglio and Ivanoe De Falco and Marc Ebner editors,
Proceedings of the 12th European Conference on Genetic                 Programming, EuroGP 2009, volume 5481, pages 85-96, Tuebingen, 2009. Springer.
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  Ting Hu and  Wolfgang Banzhaf.
Neutrality and variability: two sides of evolvability                 in linear genetic programming. In
 Guenther Raidl and  Franz Rothlauf and                  Giovanni Squillero and Rolf Drechsler and Thomas Stuetzle and                  Mauro Birattari and Clare Bates Congdon and                  Martin Middendorf and Christian Blum and Carlos Cotta and                  Peter Bosman and Joern Grahl and Joshua Knowles and                  David Corne and Hans-Georg Beyer and Ken Stanley and                  Julian F. Miller and Jano van Hemert and                  Tom Lenaerts and Marc Ebner and Jaume Bacardit and                  Michael O'Neill and Massimiliano Di Penta and Benjamin Doerr and                  Thomas Jansen and Riccardo Poli and Enrique Alba editors,
GECCO '09: Proceedings of the 11th Annual conference                 on Genetic and evolutionary computation, pages 963-970, Montreal, 2009. ACM.
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  Ting Hu and  Wolfgang Banzhaf.
Measuring rate of evolution in genetic programming                 using amino acid to synonymous substitution ratio                 ka/ks. In
 Maarten Keijzer and  Giuliano Antoniol and                  Clare Bates Congdon and Kalyanmoy Deb and Benjamin Doerr and                  Nikolaus Hansen and John H. Holmes and                  Gregory S. Hornby and Daniel Howard and James Kennedy and                  Sanjeev Kumar and Fernando G. Lobo and                  Julian Francis Miller and Jason Moore and Frank Neumann and                  Martin Pelikan and Jordan Pollack and Kumara Sastry and                  Kenneth Stanley and Adrian Stoica and El-Ghazali Talbi and                  Ingo Wegener editors,
GECCO '08: Proceedings of the 10th annual conference                 on Genetic and evolutionary computation, pages 1337-1338, Atlanta, GA, USA, 2008. ACM.
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  Ting Hu and  Wolfgang Banzhaf.
Nonsynonymous to Synonymous Substitution Ratio ka/ks:                 Measurement for Rate of Evolution in Evolutionary                 Computation. In
 Gunter Rudolph and  Thomas Jansen and  Simon Lucas and                  Carlo Poloni and Nicola Beume editors,
Parallel Problem Solving from Nature - PPSN X, volume 5199, pages 448-457, Dortmund, 2008. Springer.
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Genetic Programming book chapters by Ting Hu
Genetic Programming technical reports by Ting Hu
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  Ting Hu and  Wolfgang Banzhaf.
Evolvability and Acceleration in Evolutionary                 Computation. Technical report,
2008-04,
Department of Computer Science, Memorial University of                 Newfoundland, St. John's, NL, Canada A1B 3X5, 2008.
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Genetic Programming other entries for Ting Hu