Evolutionary Computation and Machine Learning Research Group: Publications

Our publications are organised by year, or you can see the full list here.

2026 2025 2024 2023 2022 2021
2020 2019 2018 2017 2016 2015
2014 2013 2012 2011 2010 2009
2008 2007 2006 2005 2004 2003
2002 2001 2000 Older

Our 20 most recent publications:

  • Huang, J., Xue, B., Sun, Y., Zhang, M., & Yen, G. G. (2026) "Activation features empowered: An efficient gradient-free proxy for zero-shot neural architecture search". Pattern Recognition, 179. doi:10.1016/j.patcog.2026.113917
  • Jia, X., Guo, T., Mei, Y., Zhang, M., Xiao, F., Gu, X., & Du, W. (2026) "A self-adapting memetic algorithm with reinforcement learning for multi-objective aircraft recovery problems". Applied Soft Computing, 201. doi:10.1016/j.asoc.2026.115550
  • Zhang, T., Bi, Y., Wang, H., Liang, J., Xue, B., & Zhang, M. (2026) "Learning features for data-efficient image classification via improved decomposition-based multi-objective genetic programming". Swarm and Evolutionary Computation, 107, 102430. doi:10.1016/j.swevo.2026.102430
  • Xu, M., Mei, Y., Zhang, F., Ong, Y. S., & Zhang, M. (2026) "Genetic programming with advanced diverse partner selection for dynamic scheduling". Expert Systems with Applications, 322. doi:10.1016/j.eswa.2026.132158
  • Fang, Z., Ma, H., Chen, G., & Chen, S. (2026) "STAR: Spatial-temporal autoscaling for cloud applications with deep reinforcement learning". Expert Systems with Applications, 319. doi:10.1016/j.eswa.2026.132105
  • Zhang, H., Chen, Q., Xue, B., Banzhaf, W., & Zhang, M. (2026) "Enhancing Generalization in Evolutionary Feature Construction for Symbolic Regression Through Vicinal Jensen Gap Minimization". IEEE Transactions on Evolutionary Computation, 30(3), 1009-1023. doi:10.1109/TEVC.2025.3581739
  • Yuan, G., Xue, B., & Zhang, M. (2026) "Efficient Evolutionary Neural Architecture Search Using Reliable Fitness Evaluations for Image Classification". IEEE Transactions on Emerging Topics in Computational Intelligence, 10(3), 2276-2290. doi:10.1109/TETCI.2025.3602074
  • Xu, M., Mei, Y., Zhang, F., Soon Ong, Y., & Zhang, M. (2026) "Pareto Set Learning Through Genetic Programming for Multiobjective Dynamic Scheduling". IEEE Transactions on Evolutionary Computation, 30(3), 942-956. doi:10.1109/TEVC.2025.3568375
  • Xie, C., Xue, B., Zhang, M., Shi, Q., & Chen, S. (2026) "Particle Swarm Optimization for Automated Design of Reversible Residual Neural Networks for Turntable Servo Systems". IEEE Transactions on Emerging Topics in Computational Intelligence, 10(3), 2670-2681. doi:10.1109/TETCI.2025.3607400
  • Huang, Z., Xue, B., Zhang, M., Rooney, J. S., Gordon, K. C., & Killeen, D. P. (2026) "Symbolically Regressing Fish Biomass Spectral Data: A Linear Genetic Programming Method With Tunable Primitives". Journal of the Royal Society of New Zealand, 56(3). doi:10.1002/snz2.70051
  • Hancer, E., Chaput, R., Liu, I., Xue, B., Vennell, R., & Zhang, M. (2026) "Spatiotemporal Forecasting of Mediterranean Blue Mussel Biofouling Settlement to Inform Aquaculture Management". New Zealand Journal of Marine and Freshwater Research, 60(2). doi:10.1002/nzm2.70035
  • Dong, L., Bi, Y., Xue, B., & Zhang, M. (2026) "An enhanced genetic programming algorithm with new genetic operators for medical image classification". Genetic Programming and Evolvable Machines, 27(1). doi:10.1007/s10710-026-09533-0
  • Acampora, G., Vitiello, A., Wu, R., Xue, B., & Yen, G. (2026) "Guest Editorial: Special Issue on Quantum Computing Meets Computational Intelligence: A New Vision for Smart Systems". IEEE Transactions on Emerging Topics in Computational Intelligence, 10(3), 2180-2183. doi:10.1109/TETCI.2026.3691548
  • Zhai, R., Zhang, X., Mei, Y., Guo, T., & Du, W. (2026) "Co-evolution with hierarchical decomposition for Vehicle Routing Problem with Drones". Swarm and Evolutionary Computation, 105. doi:10.1016/j.swevo.2026.102402
  • Shabanov, I., Lensen, A., Tonkin, J., & Deslippe, J. R. (2026) "A machine learning framework for mapping shifts in species' abundance from long-term monitoring data". Journal of Ecology, 114(5). doi:10.1111/1365-2745.70344
  • Pei, W., Dai, R., Xue, B., Zhang, M., Zhang, Q., Cheung, Y. M., & Xia, S. (2026) "EvoSampling: A Granular Ball-Based Evolutionary Hybrid Sampling With Knowledge Transfer for Imbalanced Learning [Research Frontier]". IEEE Computational Intelligence Magazine, 21(2), 55-67. doi:10.1109/MCI.2026.3657694
  • Meng, W., Li, Y., Zhang, F., Gao, X., & Ma, J. (2026) "Developing distance-based genetic programming classifiers by reconstructing datasets for imbalanced binary classification". Pattern Recognition, 173. doi:10.1016/j.patcog.2025.112825
  • Chen, K., Zhou, F., Zhang, F., Yu, K., & Yang, D. (2026) "A multi-channel signal fault diagnosis method based on dynamic weighted data fusion and multi-scale feature enhancement". Expert Systems with Applications, 306. doi:10.1016/j.eswa.2025.130747
  • Gomes, H. M., Lee, A., Gunasekara, N., Sun, Y., Cassales, G. W., Liu, J., . . . Bifet, A. (2026) "CapyMOA: Efficient Machine Learning for Data Streams and Online Continual Learning in Python". __. doi:10.48550/arxiv.2502.07432
  • Li, Y., Wang, H., Xue, B., Zhang, M., & Jin, Y. (2026) "Solver-Independent Automated Problem Formulation via LLMs for High-Cost Simulation-Driven Design". __. doi:10.48550/arxiv.2512.18682
Print version | Backlinks |