Evolutionary Computation and Machine Learning Research Group: Publications
Our publications are organised by year, or you can see the full list
here.
Our 20 most recent publications:
- Zhang, H., Chen, Q., Xue, B., Banzhaf, W., & Zhang, M. (2024) "Automatically Choosing Selection Operator Based on Semantic Information in Evolutionary Feature Construction". In Unknown Book (Vol. 14326 LNAI, pp. 385-397). doi:10.1007/978-981-99-7022-3_36
- Xu, M., Mei, Y., Zhang, F., & Zhang, M. (2024) "A Semantic Genetic Programming Approach to Evolving Heuristics for Multi-objective Dynamic Scheduling". In Lecture Notes in Computer Science (pp. 403-415). Springer Nature Singapore. doi:10.1007/978-981-99-8391-9_32
- Rimas, M., Chen, Q., & Zhang, M. (2024) "Bloating Reduction in Symbolic Regression Through Function Frequency-Based Tree Substitution in Genetic Programming". In Lecture Notes in Computer Science (pp. 429-440). Springer Nature Singapore. doi:10.1007/978-981-99-8391-9_34
- Nguyen, B., Xue, B., Browne, W., & Zhang, M. (2024) "Evolutionary Classification". In Handbook of Evolutionary Machine Learning (pp. 171-204). Springer Nature Singapore. doi:10.1007/978-981-99-3814-8_7
- Lv, Z., Song, X., Feng, Y., Ou, Y., Sun, Y., & Zhang, M. (2024) "Evolutionary Neural Network Architecture Search". In Handbook of Evolutionary Machine Learning (pp. 247-281). Springer Nature Singapore. doi:10.1007/978-981-99-3814-8_9
- Londt, T., Gao, X., Andreae, P., & Mei, Y. (2024) "XC-NAS: A New Cellular Encoding Approach for Neural Architecture Search of Multi-path Convolutional Neural Networks". In Lecture Notes in Computer Science (pp. 416-428). Springer Nature Singapore. doi:10.1007/978-981-99-8391-9_33
- Liu, Z., Wang, R., Japkowicz, N., Gomes, H. M., Peng, B., & Zhang, W. (2024) "SeGDroid: An Android malware detection method based on sensitive function call graph learning[Formula presented]". Expert Systems with Applications, 235. doi:10.1016/j.eswa.2023.121125
- Huang, V., Wang, C., Datta, S., Chen, B., Chen, G., & Ma, H. (2024) "Evolving Epidemic Management Rules Using Deep Neuroevolution: A Novel Approach to Inspection Scheduling and Outbreak Minimization". In Lecture Notes in Computer Science (pp. 387-399). Springer Nature Singapore. doi:10.1007/978-981-99-8391-9_31
- Fan, Q., Bi, Y., Xue, B., & Zhang, M. (2024) "A genetic programming-based method for image classification with small training data". Knowledge-Based Systems, 283, 111188. doi:10.1016/j.knosys.2023.111188
- de Silva, A., Chen, G., Ma, H., & Nekooei, S. M. (2024) "Leiden Fitness-Based Genetic Algorithm with Niching for Community Detection in Large Social Networks". In Unknown Book (Vol. 14326 LNAI, pp. 423-435). doi:10.1007/978-981-99-7022-3_39
- Chen, Q., Xue, B., Browne, W., & Zhang, M. (2024) "Evolutionary Regression and Modelling". In Handbook of Evolutionary Machine Learning (pp. 121-149). Springer Nature Singapore. doi:10.1007/978-981-99-3814-8_5
- Li, B., Guo, T., Mei, Y., Li, Y., Chen, J., Zhang, Y., . . . Du, W. (2023) "A multi-objective memetic algorithm with adaptive local search for airspace complexity mitigation". Swarm and Evolutionary Computation, 83. doi:10.1016/j.swevo.2023.101400
- Hancer, E., Xue, B., & Zhang, M. (2023) "An evolutionary filter approach to feature selection in classification for both single- and multi-objective scenarios". Knowledge-Based Systems, 280. doi:10.1016/j.knosys.2023.111008
- Lythe, M., Mazorra de Cos, G., Mingallon, M., Lensen, A., Galloway, C., Knox, D., . . . Kumarasinghe, K. (2023) "Explainable AI – building trust through understanding: Explainable AI Whitepaper". AI Forum. Retrieved from https://aiforum.org.
- Zhang, Y., Mei, Y., Zhang, H., Cai, Q., & Wu, H. (2023) "RoCaSH2: An Effective Route Clustering and Search Heuristic for Large-Scale Multi-Depot Capacitated Arc Routing Problem". IEEE Computational Intelligence Magazine, 18(4), 43-56. doi:10.1109/MCI.2023.3304081
- Zhang, H., Chen, Q., Xue, B., Banzhaf, W., & Zhang, M. (2023) "MAP-Elites for Genetic Programming-Based Ensemble Learning: An Interactive Approach [AI-eXplained]". IEEE Computational Intelligence Magazine, 18(4), 62-63. doi:10.1109/MCI.2023.3304085
- Raymond, C., Chen, Q., Xue, B., & Zhang, M. (2023) "Learning Symbolic Model-Agnostic Loss Functions via Meta-Learning". IEEE Transactions on Pattern Analysis and Machine Intelligence, 45(11), 13699-13714. doi:10.1109/TPAMI.2023.3294394
- Cerqueira, V., Gomes, H. M., Bifet, A., & Torgo, L. (2023) "STUDD: a student–teacher method for unsupervised concept drift detection". Machine Learning, 112(11), 4351-4378. doi:10.1007/s10994-022-06188-7
- Lee, A., Zhang, Y., Gomes, H. M., Bifet, A., & Pfahringer, B. (2023) "Look At Me, No Replay! SurpriseNet: Anomaly Detection Inspired Class Incremental Learning". In Proceedings of the 32nd ACM International Conference on Information and Knowledge Management. ACM. doi:10.1145/3583780.3615236
- Lensen, A. (2023) "NZ’s political leaders are ignoring the mounting threats from AI – and that’s putting everyone at risk". The Conversation. Retrieved from https://theconversation.