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Qi Chen, Ph.D

You can find my publications from [Google Scholar]

Refereed Journal Articles

  1. Yi Mei, Qi Chen, Andrew Lensen, Bing Xue and Mengjie Zhang. “Explainable Artificial Intelligence by Genetic Programming: A Survey IEEE Transaction on Evolutionary Computation. 2022. DOI:10.1109/TEVC.2022.3225509 [http]

  2. Christian Raymond, Qi Chen, Bing Xue and Mengjie Zhang. “Learning Symbolic Model-Agnostic Loss Functions via Meta-Learning. arXiv preprint.2022. [http]

  3. Baligh Al-Helali, Qi Chen, Bing Xue and Mengjie Zhang. “Multi-Tree Genetic Programming with New Operators for Transfer Learning in Symbolic Regression with Incomplete IEEE Transaction on Evolutionary Computation. 2021. DOI:10.1109/TEVC.2021.3079843 [http]

  4. Baligh Al-Helali, Qi Chen, Bing Xue and Mengjie Zhang. “A New Imputation Method Based on Genetic Programming and Weighted KNN for Symbolic Regression with Incomplete Data. Soft Computing. 2021. DOI: https://doi.org/10.1007/s00500-021-05590-y [http]

  5. Qi Chen, Bing Xue, and Mengjie Zhang. “Preserving Population Diversity Based on Transformed Semantics in Genetic Programming for Symbolic Regression, IEEE Transaction on Evolutionary Computation, Vol.25, Issue 3, June 2021. pp.433-447. DOI: 10.1109/TEVC.2020.3046569. 15pp. [http]

  6. Qi Chen, Bing Xue, and Mengjie Zhang. “Rademacher Complexity for Enhancing the Generalisation of Genetic Programming for Symbolic Regression". IEEE Transactions on Cybernetics. 2020. DOI: 10.1109/TCYB.2020.3004361. 14pp.[http]

  7. Qi Chen, Bing Xue, and Mengjie Zhang. “Genetic Programming for Instance Transfer Learning in Symbolic Regression". IEEE Transactions on Cybnertics. 2020. DOI: 10.1109/TCYB.2020.2969689. 14pp. [http]

  8. Harith Al-Sahaf, Ying Bi, Qi Chen, Andrew Lensen, Yi Mei, Yanan Sun, Binh Tran, Bing Xue, and Mengjie Zhang. “A Survey on Evolutionary Machine Learning”. Journal of the Royal Society of New Zealand (TNZR). 2019. pp. 205-228. [http]

  9. Qi Chen, Bing Xue, and Mengjie Zhang. “Structural Risk Minimisation-Driven Genetic Programming for Enhancing Generalisation in Symbolic Regression”, IEEE Transaction on Evolutionary Computation, Vol.23, Issue 4, Aug. 2019. pp.703-717. DOI:10.1109/TEVC.2018.2881392 [http]

  10. Qi Chen, Bing Xue, and Mengjie Zhang. “Improving Generalisation of Genetic Programming for Symbolic Regression with Angle-Driven Geometric Semantic Operators”, IEEE Transaction on Evolutionary Computation, Vol.23, Issue 3, June. 2019. pp.488-502. DOI:10.1109/TEVC.2018.2869621. [http]

  11. Qi. Chen, Mengjie. Zhang, and Bing. Xue. “Feature Selection to Improve Generalisation of Genetic Programming for High-Dimensional Symbolic Regression”, IEEE Transaction on Evolutionary Computation, Vol.21, no. 5, pp. 792-806, 2017. DOI:10.1109/TEVC.2017.2683489. [http]

Refereed International Conference Papers

  1. Al-Helali, Baligh, Qi Chen, Bing Xue, and Mengjie Zhang. “A Hybrid GP-KNN Imputation for Symbolic Regression with Missing Values.” In Australasian Joint Conference on Artificial Intelligence (AI 2018), Springer, Cham, 2018. pp. 345-357. [http]

  2. Qi Chen, Mengjie Zhang and Bing Xue.“New Geometric Semantic Operators in Genetic Programming: Perpendicular Crossover and Random Segment Mutation”. Proceedings of 2017 Genetic and Evolutionary Computation Conference (GECCO 2017) Companion. ACM Press. Berlin, German, 15 - 19 July 2017.pp 223-224. [http]

  3. Qi Chen, Bing Xue, Yi Mei, and Mengjie Zhang. “Angle-aware Geometric Semantic Crossover in Genetic Programming for Symbolic Regression”. Proceedings of the 20th European Conference on Genetic Programming (EuroGP 2017). Lecture Notes in Computer Science. Vol. 10196. Amsterdam. 18-21 April 2017. pp. 229-245. [http]

  4. Qi Chen, Mengjie Zhang, and Bing Xue. “Geometric Semantic Genetic Programming with Perpendicular Crossover and Random Segment Mutation for Symbolic Regression”, 11th SEAL. Lecture Notes in Computer Science. Vol. 10593. 2017. pp. 422-434. [http]

  5. Qi Chen, Mengjie Zhang, and Bing Xue.“Genetic Programming with Embedded Feature Construction for High-Dimensional Symbolic Regression”. Asia-Pacific Symposium on Intelligent and Evolutionary Systems (IES2016), Canberra, Australia, 16-18 November 2016.pp.87–102. [http]

  6. Qi Chen, Bing Xue, Lin Shang and Mengjie Zhang.“Improving Generalisation of Genetic Programming for Symbolic Regression with Structural Risk Minimisation”. Proceedings of 2016 Genetic and Evolutionary Computation Conference (GECCO 2016). ACM Press. Dever, Colorado, USA. 20-24 July 2016.pp.709-716. [http]

  7. Qi Chen, Bing Xue, Ben Niu and Mengjie Zhang, “Improving Generalisation of Genetic Programming for High-Dimensional Symbolic Regression with Feature Selection”. Proceedings of 2016 IEEE World Congress on Computational Intelligence/ IEEE Congress on Evolutionary Computation (WCCI/CEC 2016). Vancouver, Canada. 24-29 July, 2016. pp.3793-3800. [http]

  8. Qi Chen, Bing Xue, and Mengjie Zhang, “Generalisation and Domain Adaptation in GP with Gradient Descent for Symbolic Regression”. Proceedings of 2015 IEEE Congress on Evolutionary Computation (CEC 2015). Sendai, Japan. 25-28 May, 2015. pp. 1137-1144. [http]

My PhD Thesis

  • Qi Chen: Improving the Generalisation of Genetic Programming for Symbolic Regression, PhD Thesis, (1 Aug. 2014 - 21 Dec. 2017), Victoria University of Wellington, New Zealand [http]