Genetic Programming Bibliography entries for Qi Chen

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GP coauthors/coeditors: Baligh Al-Helali, Bing Xue, Mengjie Zhang, Harith Al-Sahaf, Ying Bi, Andrew Lensen, Yi Mei, Yanan Sun, Binh Ngan Tran, Ben Niu, Wolfgang Banzhaf, Will N Browne, Christian Raymond, Mohamad Rimas Mohamad Anfar, Shanshan Tang, Min Huang, Chunyu Wang, Jizhong Xu, Hengzhe Zhang, Aimin Zhou, Alberto Tonda,

Genetic Programming Articles by Qi Chen

  1. Hengzhe Zhang and Aimin Zhou and Qi Chen and Bing Xue and Mengjie Zhang. SR-Forest: A Genetic Programming based Heterogeneous Ensemble Learning Method. IEEE Transactions on Evolutionary Computation, 28(5):1484-1498, 2024. details

  2. Hengzhe Zhang and Qi Chen and Bing Xue and Wolfgang Banzhaf and Mengjie Zhang. A geometric semantic macro-crossover operator for evolutionary feature construction in regression. Genetic Programming and Evolvable Machines, 25:Article number: 2, 2024. Online first. details

  3. Hengzhe Zhang and Qi Chen and Bing Xue and Wolfgang Banzhaf and Mengjie Zhang. Modular Multi-Tree Genetic Programming for Evolutionary Feature Construction for Regression. IEEE Transactions on Evolutionary Computation, 28(5):1455-1469, 2024. details

  4. Hengzhe Zhang and Qi Chen and Bing Xue and Wolfgang Banzhaf and Mengjie Zhang. MAP-Elites for Genetic Programming-Based Ensemble Learning: An Interactive Approach [AI-eXplained]. IEEE Computational Intelligence Magazine, 18(4):62-63, 2023. details

  5. 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

  6. Qi Chen and Bing Xue and Mengjie Zhang. Genetic Programming for Instance Transfer Learning in Symbolic Regression. IEEE Transactions on Cybernetics, 52(1):25-38, 2022. details

  7. Qi Chen and Bing Xue and Mengjie Zhang. Preserving Population Diversity Based on Transformed Semantics in Genetic Programming for Symbolic Regression. IEEE Transactions on Evolutionary Computation, 25(3):433-447, 2021. details

  8. Baligh Al-Helali and Qi Chen and Bing Xue and Mengjie Zhang. A new imputation method based on genetic programming and weighted KNN for symbolic regression with incomplete data. Soft Computing, 25(8):5993-6012, 2021. details

  9. Baligh Al-Helali and Qi Chen and Bing Xue and Mengjie Zhang. Multi-Tree Genetic Programming with New Operators for Transfer Learning in Symbolic Regression with Incomplete Data. IEEE Transactions on Evolutionary Computation, 25(6):1049-1063, 2021. details

  10. Qi Chen and Mengjie Zhang and Bing Xue. Structural Risk Minimisation-Driven Genetic Programming for Enhancing Generalisation in Symbolic Regression. IEEE Transactions on Evolutionary Computation, 23(4):703-717, 2019. details

  11. Qi Chen and Bing Xue and Mengjie Zhang. Improving Generalisation of Genetic Programming for Symbolic Regression with Angle-Driven Geometric Semantic Operators. IEEE Transactions on Evolutionary Computation, 23(3):488-502, 2019. details

  12. 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

  13. Qi Chen and Mengjie Zhang and Bing Xue. Feature Selection to Improve Generalisation of Genetic Programming for High-Dimensional Symbolic Regression. IEEE Transactions on Evolutionary Computation, 21(5):792-806, 2017. details

  14. Hengzhe Zhang and Qi Chen and Bing Xue and Wolfgang Banzhaf and Mengjie Zhang. A Semantic-Based Hoist Mutation Operator for Evolutionary Feature Construction in Regression. IEEE Transactions on Evolutionary Computation. Accepted for future publication. details

  15. Baligh Al-Helali and Qi Chen and Bing Xue and Mengjie Zhang. Genetic Programming for Feature Selection Based on Feature Removal Impact in High-Dimensional Symbolic Regression. IEEE Transactions on Emerging Topics in Computational Intelligence. Early access. details

  16. Baligh Al-Helali and Qi Chen and Bing Xue and Mengjie Zhang. Multitree Genetic Programming With Feature-Based Transfer Learning for Symbolic Regression on Incomplete Data. IEEE Transactions on Cybernetics. Early access. details

Genetic Programming PhD doctoral thesis Qi Chen

Genetic Programming conference papers by Qi Chen

  1. Hengzhe Zhang and Qi Chen and Bing Xue and Wolfgang Banzhaf and Mengjie Zhang. A Semantic-based Hoist Mutation Operator for Evolutionary Feature Construction in Regression [Hot off the Press]. In Marcus Gallagher editor, Proceedings of the 2024 Genetic and Evolutionary Computation Conference Companion, pages 65-66, Melbourne, Australia, 2024. Association for Computing Machinery. details

  2. Hengzhe Zhang and Qi Chen and Bing Xue and Wolfgang Banzhaf and Mengjie Zhang. Bias-Variance Decomposition: An Effective Tool to Improve Generalization of Genetic Programming-based Evolutionary Feature Construction for Regression. 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 998-1006, Melbourne, Australia, 2024. Association for Computing Machinery. details

  3. Jizhong Xu and Qi Chen and Bing Xue and Mengjie Zhang. A New Concordance Correlation Coefficient based Fitness Function for Genetic Programming for Symbolic Regression. In Bing Xue editor, 2024 IEEE Congress on Evolutionary Computation (CEC), Yokohama, Japan, 2024. IEEE. details

  4. Chunyu Wang and Qi Chen and Bing Xue and Mengjie Zhang. Multi-task Genetic Programming with Semantic based Crossover for Multi-output Regression. In Ting Hu and Aniko Ekart editors, Proceedings of the 2024 Genetic and Evolutionary Computation Conference Companion, pages 543-546, Melbourne, Australia, 2024. Association for Computing Machinery. details

  5. Shanshan Tang and Qi Chen and Bing Xue and Min Huang and Mengjie Zhang. Genetic Programming with Multi-Task Feature Selection for Alzheimer's Disease Diagnosis. In Bing Xue editor, 2024 IEEE Congress on Evolutionary Computation (CEC), Yokohama, Japan, 2024. IEEE. details

  6. Mohamad Rimas Mohamad Anfar and Qi Chen and Mengjie Zhang. Feature Selection for GPSR Based on Maximal Information Coefficient and Shapley Values. In Bing Xue editor, 2024 IEEE Congress on Evolutionary Computation (CEC), Yokohama, Japan, 2024. IEEE. details

  7. Hengzhe Zhang and Qi Chen and Bing Xue and Mengjie Zhang and Wolfgang Banzhaf. P-Mixup: Improving Generalization Performance of Evolutionary Feature Construction with Pessimistic Vicinal Risk Minimization. In Heike Trautmann and Tea Tusar and Penousal Machado and Thomas Baeck editors, 18th International Conference on Parallel Problem Solving from Nature, University of Applied Sciences Upper Austria, Hagenberg, Austria, 2024. Springer. details

  8. Hengzhe Zhang and Qi Chen and Bing Xue and Wolfgang Banzhaf and Mengjie Zhang. Improving Generalization of Evolutionary Feature Construction with Minimal Complexity Knee Points in Regression. In Mario Giacobini and Bing Xue and Luca Manzoni editors, EuroGP 2024: Proceedings of the 27th European Conference on Genetic Programming, volume 14631, pages 142-158, Aberystwyth, 2024. Springer. details

  9. Hengzhe Zhang and Qi Chen and Bing Xue and Wolfgang Banzhaf and Mengjie Zhang. Automatically Choosing Selection Operator Based on Semantic Information in Evolutionary Feature Construction. In Fenrong Liu and Arun Anand Sadanandan and Duc Nghia Pham and Petrus Mursanto and Dickson Lukose editors, Pacific Rim International Conference on Artificial Intelligence, volume 14326, pages 385-397, Jakarta, Indonesia, 2023. Springer Nature. details

  10. Hengzhe Zhang and Aimin Zhou and Qi Chen and Bing Xue and Mengjie Zhang. Genetic Programming-Based Evolutionary Feature Construction for Heterogeneous Ensemble Learning [Hot of the Press]. In Alberto Moraglio editor, Proceedings of the 2023 Genetic and Evolutionary Computation Conference, pages 49-50, Lisbon, Portugal, 2023. Association for Computing Machinery. details

  11. Chunyu Wang and Qi Chen and Bing Xue and Mengjie Zhang. Shapley Value Based Feature Selection to Improve Generalization of Genetic Programming for High-Dimensional Symbolic Regression. In Australasian Conference on Data Science and Machine Learning, AusDM 2023, pages 163-176, Auckland, New Zealand, 2023. Springer. details

  12. Christian Raymond and Qi Chen and Bing Xue and Mengjie Zhang. Fast and Efficient Local-Search for Genetic Programming Based Loss Function Learning. 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 1184-1193, Lisbon, Portugal, 2023. Association for Computing Machinery. details

  13. Qi Chen and Bing Xue and Wolfgang Banzhaf and Mengjie Zhang. Relieving Genetic Programming from Coefficient Learning for Symbolic Regression via Correlation and Linear Scaling. 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 420-428, Lisbon, Portugal, 2023. Association for Computing Machinery. details

  14. Hengzhe Zhang and Qi Chen and Bing Xue and Wolfgang Banzhaf and Mengjie Zhang. A Double Lexicase Selection Operator for Bloat Control in Evolutionary Feature Construction for Regression. 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 1194-1202, Lisbon, Portugal, 2023. Association for Computing Machinery. details

  15. Hengzhe Zhang and Qi Chen and Alberto Tonda and Bing Xue and Wolfgang Banzhaf and Mengjie Zhang. MAP-Elites with Cosine-Similarity for Evolutionary Ensemble Learning. In Gisele Pappa and Mario Giacobini and Zdenek Vasicek editors, EuroGP 2023: Proceedings of the 26th European Conference on Genetic Programming, volume 13986, pages 84-100, Brno, Czech Republic, 2023. Springer Verlag. details

  16. Mohamad Rimas and Qi Chen and Mengjie Zhang. Bloating Reduction in Symbolic Regression Through Function Frequency-Based Tree Substitution in Genetic Programming. In Tongliang Liu and Geoff Webb and Lin Yue and Dadong Wang editors, 36th Australasian Joint Conference on Artificial Intelligence, Part II, volume 14472, pages 429-440, Brisbane, Australia, 2023. Springer Nature. details

  17. Qi Chen and Bing Xue. Generalisation in Genetic Programming for Symbolic Regression: Challenges and Future Directions. In Women in Computational Intelligence, 2022. Springer. details

  18. Christian Raymond and Qi Chen and Bing Xue and Mengjie Zhang. Multi-objective Genetic Programming with the Adaptive Weighted Splines Representation for Symbolic Regression. In Eric Medvet and Gisele Pappa and Bing Xue editors, EuroGP 2022: Proceedings of the 25th European Conference on Genetic Programming, volume 13223, pages 51-67, Madrid, Spain, 2022. Springer Verlag. details

  19. Christian Raymond and Qi Chen and Bing Xue and Mengjie Zhang. Multi-objective Genetic Programming for Symbolic Regression with the Adaptive Weighted Splines Representation. 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 165-166, internet, 2021. Association for Computing Machinery. details

  20. Baligh Al-Helali and Qi Chen and Bing Xue and Mengjie Zhang. GP with a Hybrid Tree-vector Representation for Instance Selection and Symbolic Regression on Incomplete Data. In Yew-Soon Ong editor, 2021 IEEE Congress on Evolutionary Computation (CEC), pages 604-611, Krakow, Poland, 2021. details

  21. Christian Raymond and Qi Chen and Bing Xue and Mengjie Zhang. Adaptive Weighted Splines: A New Representation to Genetic Programming for Symbolic Regression. 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 1003-1011, internet, 2020. Association for Computing Machinery. details

  22. Baligh Al-Helali and Qi Chen and Bing Xue and Mengjie Zhang. Genetic Programming-Based Selection of Imputation Methods in Symbolic Regression with Missing Values. In Marcus Gallagher and Nour Moustafa and Erandi Lakshika editors, AI 2020: Advances in Artificial Intelligence - 33rd Australasian Joint Conference, AI 2020, Canberra, ACT, Australia, November 29-30, 2020, Proceedings, volume 12576, pages 163-175, 2020. Springer. details

  23. Qi Chen and Bing Xue and Mengjie Zhang. Improving Symbolic Regression Based on Correlation between Residuals and Variables. 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 922-930, internet, 2020. Association for Computing Machinery. details

  24. Baligh Al-Helali and Qi Chen and Bing Xue and Mengjie Zhang. Data Imputation for Symbolic Regression with Missing Values: A Comparative Study. In 2020 IEEE Symposium Series on Computational Intelligence (SSCI), pages 2093-2100, 2020. details

  25. Baligh Al-Helali and Qi Chen and Bing Xue and Mengjie Zhang. Multi-Tree Genetic Programming for Feature Construction-Based Domain Adaptation in Symbolic Regression with Incomplete Data. 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 913-921, internet, 2020. Association for Computing Machinery. details

  26. Baligh Al-Helali and Qi Chen and Bing Xue and Mengjie Zhang. Hessian Complexity Measure for Genetic Programming-based Imputation Predictor Selection in Symbolic Regression with Incomplete Data. In Ting Hu and Nuno Lourenco and Eric Medvet editors, EuroGP 2020: Proceedings of the 23rd European Conference on Genetic Programming, volume 12101, pages 1-17, Seville, Spain, 2020. Springer Verlag. details

  27. Baligh Al-Helali and Qi Chen and Bing Xue and Mengjie Zhang. Multi-Tree Genetic Programming-based Transformation for Transfer Learning in Symbolic Regression with Highly Incomplete Data. In Yaochu Jin editor, 2020 IEEE Congress on Evolutionary Computation, CEC 2020, page paper id24250, internet, 2020. IEEE Press. details

  28. Baligh Al-Helali and Qi Chen and Bing Xue and Mengjie Zhang. Genetic Programming with Noise Sensitivity for Imputation Predictor Selection in Symbolic Regression with Incomplete Data. In Yaochu Jin editor, 2020 IEEE Congress on Evolutionary Computation, CEC 2020, page paper id24344, internet, 2020. IEEE Press. details

  29. Christian Raymond and Qi Chen and Bing Xue and Mengjie Zhang. Genetic Programming with Rademacher Complexity for Symbolic Regression. In Carlos A. Coello Coello editor, 2019 IEEE Congress on Evolutionary Computation, CEC 2019, pages 2657-2664, Wellington, New Zealand, 2019. IEEE Press. details

  30. Baligh Al-Helali and Qi Chen and Bing Xue and Mengjie Zhang. Genetic Programming for Imputation Predictor Selection and Ranking in Symbolic Regression with High-Dimensional Incomplete Data. In Jixue Liu and James Bailey editors, AI 2019: Advances in Artificial Intelligence - 32nd Australasian Joint Conference, Adelaide, SA, Australia, December 2-5, 2019, Proceedings, volume 11919, pages 523-535, 2019. Springer. details

  31. Baligh Al-Helali and Qi Chen and Bing Xue and Mengjie Zhang. Genetic Programming-Based Simultaneous Feature Selection and Imputation for Symbolic Regression with Incomplete Data. In Shivakumara Palaiahnakote and Gabriella Sanniti di Baja and Liang Wang and Wei Qi Yan editors, Pattern Recognition - 5th Asian Conference, ACPR 2019, Auckland, New Zealand, November 26-29, 2019, Revised Selected Papers, Part II, volume 12047, pages 566-579, 2019. Springer. details

  32. Qi Chen and Bing Xue and Mengjie Zhang. Differential evolution for instance based transfer learning in genetic programming for symbolic regression. 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 161-162, Prague, Czech Republic, 2019. ACM. details

  33. Qi Chen and Bing Xue and Mengjie Zhang. Instance based Transfer Learning for Genetic Programming for Symbolic Regression. In Carlos A. Coello Coello editor, 2019 IEEE Congress on Evolutionary Computation, CEC 2019, pages 3006-3013, Wellington, New Zealand, 2019. IEEE Press. details

  34. Baligh Al-Helali and Qi Chen and Bing Xue and Mengjie Zhang. A Genetic Programming-based Wrapper Imputation Method for Symbolic Regression with Incomplete Data. In 2019 IEEE Symposium Series on Computational Intelligence (SSCI), pages 2395-2402, 2019. details

  35. Qi Chen and Mengjie Zhang and Bing Xue. Geometric Semantic Genetic Programming with Perpendicular Crossover and Random Segment Mutation for Symbolic Regression. 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 422-434, Shenzhen, China, 2017. Springer. details

  36. Qi Chen and Mengjie Zhang and Bing Xue. Genetic Programming with Embedded Feature Construction for High-Dimensional Symbolic Regression. In Intelligent and Evolutionary Systems, 2017. Springer. details

  37. Qi Chen and Mengjie Zhang and Bing Xue. New Geometric Semantic Operators in Genetic Programming: Perpendicular Crossover and Random Segment Mutation. In Proceedings of the Genetic and Evolutionary Computation Conference Companion, pages 223-224, Berlin, Germany, 2017. ACM. details

  38. Qi Chen and Bing Xue and Yi Mei and Mengjie Zhang. Geometric Semantic Crossover with an Angle-aware Mating Scheme in Genetic Programming for Symbolic Regression. In Mauro Castelli and James McDermott and Lukas Sekanina editors, EuroGP 2017: Proceedings of the 20th European Conference on Genetic Programming, volume 10196, pages 229-245, Amsterdam, 2017. Springer Verlag. details

  39. Qi Chen and Mengjie Zhang and Bing Cue. Improving Generalisation of Genetic Programming for Symbolic Regression with Structural Risk Minimisation. In Tobias Friedrich editor, GECCO '16: Proceedings of the 2016 Annual Conference on Genetic and Evolutionary Computation, pages 709-716, Denver, USA, 2016. ACM. details

  40. Qi Chen and Bing Xue and Ben Niu and Mengjie Zhang. Improving Generalisation of Genetic Programming for High-Dimensional Symbolic Regression with Feature Selection. In Yew-Soon Ong editor, Proceedings of 2016 IEEE Congress on Evolutionary Computation (CEC 2016), pages 3793-3800, Vancouver, 2016. IEEE Press. details

  41. Qi Chen and Bing Xue and Mengjie Zhang. Generalisation and Domain Adaptation in GP with Gradient Descent for Symbolic Regression. In Yadahiko Murata editor, Proceedings of 2015 IEEE Congress on Evolutionary Computation (CEC 2015), pages 1137-1144, Sendai, Japan, 2015. IEEE Press. details

Genetic Programming book chapters by Qi Chen