Genetic Programming Bibliography entries for Andrew Lensen

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GP coauthors/coeditors: Harith Al-Sahaf, Ying Bi, Qi Chen, Yi Mei, Yanan Sun, Binh Ngan Tran, Bing Xue, Mengjie Zhang, Hayden Andersen, Will N Browne, Ben Cravens, Paula Maddigan, Brijesh Verma, Finn Schofield, Luis Slyfield, Peng Zeng, Xiaotian Song, Yuwei Ou, Jiancheng Lv, Rui Zhang,

Genetic Programming Articles by Andrew Lensen

  1. Yi Mei and Qi Chen and Andrew Lensen and Bing Xue and Mengjie Zhang. Explainable Artificial Intelligence by Genetic Programming: A Survey. IEEE Transactions on Evolutionary Computation, 27(3):621-641, 2023. details

  2. Andrew Lensen and Bing Xue and Mengjie Zhang. Genetic Programming for Manifold Learning: Preserving Local Topology. IEEE Transactions on Evolutionary Computation, 26(4):661-675, 2022. details

  3. Andrew Lensen and Bing Xue and Mengjie Zhang. Genetic Programming for Evolving a Front of Interpretable Models for Data Visualization. IEEE Transactions on Cybernetics, 51(11):5468-5482, 2021. details

  4. Andrew Lensen and Mengjie Zhang and Bing Xue. Multi-objective genetic programming for manifold learning: balancing quality and dimensionality. Genetic Programming and Evolvable Machines, 21(3):399-431, 2020. Special Issue: Highlights of Genetic Programming 2019 Events. details

  5. Andrew Lensen and Bing Xue and Mengjie Zhang. Genetic Programming for Evolving Similarity Functions for Clustering: Representations and Analysis. Evolutionary Computation, 28(4):531-561, 2020. Winter. details

  6. Harith Al-Sahaf and Ying Bi and Qi Chen and Andrew Lensen and Yi Mei and Yanan Sun and Binh Tran and Bing Xue and Mengjie Zhang. A survey on evolutionary machine learning. Journal of the Royal Society of New Zealand, 49(2):205-228, 2019. The 2019 Annual Collection of Reviews. details

Genetic Programming PhD doctoral thesis Andrew Lensen

Genetic Programming conference papers by Andrew Lensen

  1. Hayden Andersen and Andrew Lensen and Will Browne and Yi Mei. Intepretable Local Explanations Through Genetic Programming. In Jean-Baptiste Mouret and Kai Qin editors, Proceedings of the 2024 Genetic and Evolutionary Computation Conference Companion, pages 247-250, Melbourne, Australia, 2024. Association for Computing Machinery. details

  2. Finn Schofield and Luis Slyfield and Andrew Lensen. A Genetic Programming Encoder for Increasing Autoencoder Interpretability. In Gisele Pappa and Mario Giacobini and Zdenek Vasicek editors, EuroGP 2023: Proceedings of the 26th European Conference on Genetic Programming, volume 13986, pages 19-35, Brno, Czech Republic, 2023. Springer Verlag. details

  3. Rui Zhang and Andrew Lensen and Yanan Sun. Speeding up Genetic Programming Based Symbolic Regression Using GPUs. In PRICAI 2022: Trends in Artificial Intelligence, 2022. Springer. details

  4. Peng Zeng and Andrew Lensen and Yanan Sun. Large Scale Image Classification Using GPU-based 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 619-622, Boston, USA, 2022. Association for Computing Machinery. details

  5. Finn Schofield and Andrew Lensen. Using Genetic Programming to Find Functional Mappings for UMAP Embeddings. In Yew-Soon Ong editor, 2021 IEEE Congress on Evolutionary Computation (CEC), pages 704-711, Krakow, Poland, 2021. details

  6. Andrew Lensen. Mining Feature Relationships in Data. In Ting Hu and Nuno Lourenco and Eric Medvet editors, EuroGP 2021: Proceedings of the 24th European Conference on Genetic Programming, volume 12691, pages 247-262, Virtual Event, 2021. Springer Verlag. details

  7. Hayden Andersen and Andrew Lensen and Bing Xue. Genetic Programming for Evolving Similarity Functions Tailored to Clustering Algorithms. In Yew-Soon Ong editor, 2021 IEEE Congress on Evolutionary Computation (CEC), pages 688-695, Krakow, Poland, 2021. details

  8. Finn Schofield and Andrew Lensen. Evolving Simpler Constructed Features for Clustering Problems with Genetic Programming. In Yaochu Jin editor, 2020 IEEE Congress on Evolutionary Computation, CEC 2020, page paper id24602, internet, 2020. IEEE Press. details

  9. Andrew Lensen and Bing Xue and Mengjie Zhang. Can Genetic Programming Do Manifold Learning Too?. In Lukas Sekanina and Ting Hu and Nuno Lourenco editors, EuroGP 2019: Proceedings of the 22nd European Conference on Genetic Programming, volume 11451, pages 114-130, Leipzig, Germany, 2019. Springer Verlag. Best paper. details

  10. Andrew Lensen and Bing Xue and Mengjie Zhang. Automatically evolving difficult benchmark feature selection datasets with genetic programming. 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 458-465, Kyoto, Japan, 2018. ACM. details

  11. Andrew Lensen and Bing Xue and Mengjie Zhang. Generating Redundant Features with Unsupervised Multi-Tree 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 84-100, Parma, Italy, 2018. Springer Verlag. details

  12. Andrew Lensen and Bing Xue and Mengjie Zhang. New Representations in Genetic Programming for Feature Construction in k-Means Clustering. In Yuhui Shi and Kay Chen Tan and Mengjie Zhang and Ke Tang and Xiaodong Li and Qingfu Zhang and Ying Tan and Martin Middendorf and Yaochu Jin editors, Proceedings of the 11th International Conference on Simulated Evolution and Learning, SEAL-2017, volume 10593, pages 543-555, Shenzhen, China, 2017. Springer. details

  13. Andrew Lensen and Bing Xue and Mengjie Zhang. Improving K-means Clustering with Genetic Programming for Feature Construction. In Proceedings of the Genetic and Evolutionary Computation Conference Companion, pages 237-238, Berlin, Germany, 2017. ACM. details

  14. Andrew Lensen and Bing Xue and Mengjie Zhang. GPGC: Genetic Programming for Automatic Clustering Using a Flexible Non-hyper-spherical Graph-based Approach. In Proceedings of the Genetic and Evolutionary Computation Conference, pages 449-456, Berlin, Germany, 2017. ACM. details

  15. Andrew Lensen and Harith Al-Sahaf and Mengjie Zhang and Bing Xue. Genetic Programming for Region Detection, Feature Extraction, Feature Construction and Classification in Image Data. In Malcolm I. Heywood and James McDermott and Mauro Castelli and Ernesto Costa and Kevin Sim editors, EuroGP 2016: Proceedings of the 19th European Conference on Genetic Programming, volume 9594, pages 51-67, Porto, Portugal, 2016. Springer Verlag. details

  16. Andrew Lensen and Harith Al-Sahaf and Mengjie Zhang and Bing Xue. A hybrid Genetic Programming approach to feature detection and image classification. In 2015 International Conference on Image and Vision Computing New Zealand (IVCNZ), 2015. details

  17. Andrew Lensen and Harith Al-Sahaf and Mengjie Zhang and Brijesh Verma. Genetic Programming for Algae Detection in River Images. In Yadahiko Murata editor, Proceedings of 2015 IEEE Congress on Evolutionary Computation (CEC 2015), pages 2468-2475, Sendai, Japan, 2015. IEEE Press. details

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