• Mei, Y. (2022) "Invited Speaker of “Explainable Genetic Programming and its Applications in Combinatorial Optimisation"". IEEE Guangzhou Chapter Emerging Technology Forum.
  • Wang, B., Xue, B., & Zhang, M. (2022) "An Efficient Evolutionary Deep Learning Framework Based on Multi-source Transfer Learning to Evolve Deep Convolutional Neural Networks". __. doi:10.48550/arxiv.2212.03942
  • Stanley, M., Lensen, A., & Zhang, M. (2022) "Using Neural Networks to Automate Monitoring of Fish Stocks". __.
  • Xie, X., Liu, Y., Sun, Y., Yen, G. G., Xue, B., & Zhang, M. (2022) "BenchENAS: A Benchmarking Platform for Evolutionary Neural Architecture Search". IEEE Transactions on Evolutionary Computation, 26(6), 1473-1485. doi:10.1109/TEVC.2022.3147526
  • Jia, Y. H., Mei, Y., & Zhang, M. (2022) "Confidence-Based Ant Colony Optimization for Capacitated Electric Vehicle Routing Problem With Comparison of Different Encoding Schemes". IEEE Transactions on Evolutionary Computation, 26(6), 1394-1408. doi:10.1109/TEVC.2022.3144142
  • Gao, G., Mei, Y., Xin, B., Jia, Y. H., & Browne, W. N. (2022) "Automated Coordination Strategy Design Using Genetic Programming for Dynamic Multipoint Dynamic Aggregation". IEEE Transactions on Cybernetics, 52(12), 13521-13535. doi:10.1109/TCYB.2021.3080044
  • Cai, X., Sun, Q., Li, Z., Xiao, Y., Mei, Y., Zhang, Q., & Li, X. (2022) "Cooperative Coevolution With Knowledge-Based Dynamic Variable Decomposition for Bilevel Multiobjective Optimization". IEEE Transactions on Evolutionary Computation, 26(6), 1553-1565. doi:10.1109/TEVC.2022.3154057
  • Lensen, A., & Betkier, M. (2022) "We built an algorithm that predicts the length of court sentences – could AI play a role in the justice system?". The Conversation. Retrieved from https://theconversation.
  • Wang, B., Pei, W., Xue, B., & Zhang, M. (2022) "Explaining Deep Convolutional Neural Networks for Image Classification by Evolving Local Interpretable Model-agnostic Explanations". __. doi:10.48550/arxiv.2211.15143
  • Mei, Y. (2022) "AI for Emergency Medical Dispatch". New Zealand AI Researcher Association Workshop 2022.
  • Lensen, A. (2022) "AI & Image Analysis: Computational Pathology in Aotearoa Online Hui". __.
  • Nguyen, L., Nguyen Vo, T. H., Trinh, Q. H., Nguyen, B. H., Nguyen-Hoang, P. U., Le, L., & Nguyen, B. P. (2022) "IANP-EC: Identifying Anticancer Natural Products Using Ensemble Learning Incorporated with Evolutionary Computation". Journal of Chemical Information and Modeling, 62(21), 5080-5089. doi:10.1021/acs.jcim.1c00920
  • Palli, A. S., Jaafar, J., Gomes, H. M., Hashmani, M. A., & Gilal, A. R. (2022) "An Experimental Analysis of Drift Detection Methods on Multi-Class Imbalanced Data Streams". Applied Sciences (Switzerland), 12(22). doi:10.3390/app122211688
  • Rodger, H., Lensen, A., & Betkier, M. (2022) "Explainable Artificial Intelligence for Assault Sentence Prediction in New Zealand". Journal of the Royal Society of New Zealand, 53(1), 133-147. doi:10.1080/03036758.2022.2114506
  • Zhang, F., Mei, Y., Nguyen, S., Tan, K. C., & Zhang, M. (2022) "Multitask Genetic Programming-Based Generative Hyperheuristics: A Case Study in Dynamic Scheduling". IEEE Transactions on Cybernetics, 52(10), 10515-10528. doi:10.1109/TCYB.2021.3065340
  • Peng, B., Bi, Y., Xue, B., Zhang, M., & Wan, S. (2022) "A Survey on Fault Diagnosis of Rolling Bearings". Algorithms, 15(10). doi:10.3390/a15100347
  • Jiao, R., Xue, B., & Zhang, M. (2022) "Investigating the Correlation Amongst the Objective and Constraints in Gaussian Process-Assisted Highly Constrained Expensive Optimization". IEEE Transactions on Evolutionary Computation, 26(5), 872-885. doi:10.1109/TEVC.2021.3120980
  • Jia, Y. H., Mei, Y., & Zhang, M. (2022) "A Bilevel Ant Colony Optimization Algorithm for Capacitated Electric Vehicle Routing Problem". IEEE Transactions on Cybernetics, 52(10), 10855-10868. doi:10.1109/TCYB.2021.3069942
  • Chen, K., Xue, B., Zhang, M., & Zhou, F. (2022) "Correlation-Guided Updating Strategy for Feature Selection in Classification with Surrogate-Assisted Particle Swarm Optimization". IEEE Transactions on Evolutionary Computation, 26(5), 1015-1029. doi:10.1109/TEVC.2021.3134804
  • Bi, Y., Xue, B., & Zhang, M. (2022) "Genetic Programming-Based Evolutionary Deep Learning for Data-Efficient Image Classification". __. doi:10.48550/arxiv.2209.13233
  • Raymond, C., Chen, Q., Xue, B., & Zhang, M. (2022) "Learning Symbolic Model-Agnostic Loss Functions via Meta-Learning". __. doi:10.48550/arxiv.2209.08907
  • Bi, Y., Xue, B., Mesejo, P., Cagnoni, S., & Zhang, M. (2022) "A Survey on Evolutionary Computation for Computer Vision and Image Analysis: Past, Present, and Future Trends". __. doi:10.48550/arxiv.2209.06399
  • Trujillo, L., Hu, T., Lourenço, N., & Zhang, M. (2022) "Editorial Introduction". Genetic Programming and Evolvable Machines, 23(3), 305-307. doi:10.1007/s10710-022-09437-9
  • Sun, Y., Pfahringer, B., Gomes, H. M., & Bifet, A. (2022) "SOKNL: A novel way of integrating K-nearest neighbours with adaptive random forest regression for data streams". Data Mining and Knowledge Discovery, 36(5), 2006-2032. doi:10.1007/s10618-022-00858-9
  • Nguyen, S., Thiruvady, D., Zhang, M., & Alahakoon, D. (2022) "Automated Design of Multipass Heuristics for Resource-Constrained Job Scheduling with Self-Competitive Genetic Programming". IEEE Transactions on Cybernetics, 52(9), 8603-8616. doi:10.1109/TCYB.2021.3062799
  • Ali, M., Chen, Y., Cree, M. J., & Zhang, M. (2022) "In vivo computation with sensor fusion and search acceleration for smart tumor homing". Computers in Biology and Medicine, 148. doi:10.1016/j.compbiomed.2022.105887
  • Li, N., Ma, L., Yu, G., Xue, B., Zhang, M., & Jin, Y. (2022) "Survey on Evolutionary Deep Learning: Principles, Algorithms, Applications and Open Issues". __. doi:10.48550/arxiv.2208.10658
  • Zhang, F., Mei, Y., Nguyen, S., & Zhang, M. (2022) "Importance-Aware Genetic Programming for Automated Scheduling Heuristics Learning in Dynamic Flexible Job Shop Scheduling". In International Conference on Parallel Problem Solving from Nature (PPSN). Springer. doi:10.1007/978-3-031-14721-0_4
  • Rodger, H., Lensen, A., & Betkier, M. (2022) "Explainable Artificial Intelligence for Assault Sentence Prediction in New Zealand". __. doi:10.48550/arxiv.2208.06981
  • Mei, Y. (2022) "Keynote Speaker of “Automatic Heuristic Learning for Complex Optimisation Problems with Genetic Programming”". International Workshop on Evolutionary Computation and Learning.
  • Zhang, Y., Mei, Y., Huang, S., Zheng, X., & Zhang, C. (2022) "A Route Clustering and Search Heuristic for Large-Scale Multidepot-Capacitated Arc Routing Problem". IEEE Transactions on Cybernetics, 52(8), 8286-8299. doi:10.1109/TCYB.2020.3043265
  • Zhang, F., Mei, Y., Nguyen, S., & Zhang, M. (2022) "Collaborative Multifidelity-Based Surrogate Models for Genetic Programming in Dynamic Flexible Job Shop Scheduling". IEEE Transactions on Cybernetics, 52(8), 8142-8156. doi:10.1109/TCYB.2021.3050141
  • Wang, B., Xue, B., & Zhang, M. (2022) "Surrogate-Assisted Particle Swarm Optimization for Evolving Variable-Length Transferable Blocks for Image Classification". IEEE Transactions on Neural Networks and Learning Systems, 33(8), 3727-3740. doi:10.1109/TNNLS.2021.3054400
  • Sun, Y., Yen, G. G., Xue, B., Zhang, M., & Lv, J. (2022) "ArcText: A Unified Text Approach to Describing Convolutional Neural Network Architectures". IEEE Transactions on Artificial Intelligence, 3(4), 526-540. doi:10.1109/TAI.2021.3128502
  • Shi, T., Ma, H., Chen, G., & Hartmann, S. (2022) "Cost-Effective Web Application Replication and Deployment in Multi-Cloud Environment". IEEE Transactions on Parallel and Distributed Systems, 33(8), 1982-1995. doi:10.1109/TPDS.2021.3133884
  • Mann, E., Williamson, A. J., Gomes, H. M., Dillon, S., & Bifet, A. (2022) "Should a Social Enterprise Publicly “Toot its Virtuous Horn”? An Artificial Intelligence Approach". Academy of Management Proceedings, 2022(1). doi:10.5465/ambpp.2022.15344abstract
  • Lu, M., Bi, Y., Xue, B., Hu, Q., Zhang, M., Wei, Y., . . . Wu, W. (2022) "Genetic Programming for High-Level Feature Learning in Crop Classification". Remote Sensing, 14(16). doi:10.3390/rs14163982
  • Lensen, A., Xue, B., & Zhang, M. (2022) "Genetic Programming for Manifold Learning: Preserving Local Topology". IEEE Transactions on Evolutionary Computation, 26(4), 661-675. doi:10.1109/TEVC.2021.3106672
  • Gao, G., Mei, Y., Jia, Y. H., Browne, W. N., & Xin, B. (2022) "Adaptive Coordination Ant Colony Optimization for Multipoint Dynamic Aggregation". IEEE Transactions on Cybernetics, 52(8), 7362-7376. doi:10.1109/TCYB.2020.3042511
  • Bi, Y., Xue, B., & Zhang, M. (2022) "Genetic Programming-Based Discriminative Feature Learning for Low-Quality Image Classification". IEEE Transactions on Cybernetics, 52(8), 8272-8285. doi:10.1109/TCYB.2021.3049778
  • Barracchia, E. P., Pio, G., Bifet, A., Gomes, H. M., Pfahringer, B., & Ceci, M. (2022) "LP-ROBIN: Link prediction in dynamic networks exploiting incremental node embedding". Information Sciences, 606, 702-721. doi:10.1016/j.ins.2022.05.079
  • Ardeh, M. A., Mei, Y., & Zhang, M. (2022) "Genetic Programming with Knowledge Transfer and Guided Search for Uncertain Capacitated Arc Routing Problem". IEEE Transactions on Evolutionary Computation, 26(4), 765-779. doi:10.1109/TEVC.2021.3129278
  • Zhu, J., Jang-Jaccard, J., Welch, I., Al-Sahaf, H., & Camtepe, S. (2022) "Malware Triage Approach using a Task Memory based on Meta-Transfer Learning Framework". __. doi:10.48550/arxiv.2207.10242
  • Xu, M., Mei, Y., Zhang, F., & Zhang, M. (2022) "Genetic programming with cluster selection for dynamic flexible job shop scheduling". In IEEE Congress on Evolutionary Computation (CEC). doi:10.1109/CEC55065.2022.9870431
  • Mei, Y., & Lensen, A. (2022) "Tutorial on “Towards Better AI Interpretability Through Genetic Programming”". IEEE Congress on Evolutionary Computation 2022.
  • Zhang, M., & Cagnoni, S. (2022) "Evolutionary computation and evolutionary deep learning for image analysis, signal processing and pattern recognition". In GECCO 2022 Companion - Proceedings of the 2022 Genetic and Evolutionary Computation Conference (pp. 1602-1630). doi:10.1145/3520304.3533636
  • Zeng, P., Lensen, A., & Sun, Y. (2022) "Large scale image classification using GPU-based genetic programming". In GECCO 2022 Companion - Proceedings of the 2022 Genetic and Evolutionary Computation Conference (pp. 619-622). doi:10.1145/3520304.3528892
  • Xue, B., & Zhang, M. (2022) "Evolutionary computation for feature selection and feature construction". In GECCO 2022 Companion - Proceedings of the 2022 Genetic and Evolutionary Computation Conference (pp. 1200-1229). doi:10.1145/3520304.3533659
  • Xu, M., Mei, Y., Zhang, F., & Zhang, M. (2022) "Genetic programming with diverse partner selection for dynamic flexible job shop scheduling". In GECCO 2022 Companion - Proceedings of the 2022 Genetic and Evolutionary Computation Conference (pp. 615-618). doi:10.1145/3520304.3528920
  • Liu, Y., Browne, W. N., & Xue, B. (2022) "A comparison of rule compaction algorithms for michigan style learning classifier systems". In GECCO 2022 Companion - Proceedings of the 2022 Genetic and Evolutionary Computation Conference (pp. 31-32). doi:10.1145/3520304.3534068
  • Lin, J., Chen, Q., Xue, B., & Zhang, M. (2022) "Multi-task optimisation for multi-objective feature selection in classification". In GECCO 2022 Companion - Proceedings of the 2022 Genetic and Evolutionary Computation Conference (pp. 264-267). doi:10.1145/3520304.3528903
  • John, T. C., Abbasi, M. S., Al-Sahaf, H., & Welch, I. (2022) "Automatically Evolving Malice Scoring Models through Utilisation of Genetic Programming: A Cooperative Coevolution Approach". In GECCO 2022 Companion - Proceedings of the 2022 Genetic and Evolutionary Computation Conference (pp. 562-565). doi:10.1145/3520304.3529063
  • Durasević, M., Jakobović, D., Mei, Y., Nguyen, S., & Zhang, M. (2022) "Introduction to automated design of scheduling heuristics with genetic programming". In GECCO 2022 Companion - Proceedings of the 2022 Genetic and Evolutionary Computation Conference (pp. 1506-1526). doi:10.1145/3520304.3533667
  • Demir, K., Nguyen, B. H., Xue, B., & Zhang, M. (2022) "Particle swarm optimisation for sparsity-based feature selection in multi-label classification". In GECCO 2022 Companion - Proceedings of the 2022 Genetic and Evolutionary Computation Conference (pp. 232-235). doi:10.1145/3520304.3529074
  • Andersen, H., Lensen, A., & Browne, W. N. (2022) "Improving the search of learning classifier systems through interpretable feature clustering". In GECCO 2022 Companion - Proceedings of the 2022 Genetic and Evolutionary Computation Conference (pp. 1752-1756). doi:10.1145/3520304.3534027
  • Wang, S., Mei, Y., & Zhang, M. (2022) "Local ranking explanation for genetic programming evolved routing policies for uncertain capacitated Arc routing problems". In GECCO 2022 - Proceedings of the 2022 Genetic and Evolutionary Computation Conference (pp. 314-322). doi:10.1145/3512290.3528723
  • Huang, Z., Mei, Y., Zhang, F., & Zhang, M. (2022) "Graph-based Linear Genetic Programming: A Case Study of Dynamic Scheduling". In GECCO 2022 - Proceedings of the 2022 Genetic and Evolutionary Computation Conference (pp. 955-963). doi:10.1145/3512290.3528730
  • Gao, G., Xin, B., Mei, Y., Lu, S., & Ding, S. (2022) "A multi-objective evolutionary algorithm with new reproduction and decomposition mechanisms for the multi-point dynamic aggregation problem". In GECCO 2022 - Proceedings of the 2022 Genetic and Evolutionary Computation Conference (pp. 1182-1190). doi:10.1145/3512290.3528728
  • Costa, J. G. C., Mei, Y., & Zhang, M. (2022) "Guided local search with an adaptive neighbourhood size heuristic for large scale vehicle routing problems". In GECCO 2022 - Proceedings of the 2022 Genetic and Evolutionary Computation Conference (pp. 213-221). doi:10.1145/3512290.3528865
  • Xie, X., Liu, Y., Sun, Y., Zhang, M., & Tan, K. C. (2022) "Architecture Augmentation for Performance Predictor Based on Graph Isomorphism". __. doi:10.48550/arxiv.2207.00987
  • Ruigrok, M., Xue, B., Catanach, A., Zhang, M., Jesson, L., Davy, M., & Wellenreuther, M. (2022) "The Relative Power of Structural Genomic Variation versus SNPs in Explaining the Quantitative Trait Growth in the Marine Teleost Chrysophrys auratus". Genes, 13(7). doi:10.3390/genes13071129
  • Johnson, D., Chen, G., & Lu, Y. (2022) "Multi-Agent Reinforcement Learning for Real-Time Dynamic Production Scheduling in a Robot Assembly Cell". IEEE Robotics and Automation Letters, 7(3), 7684-7691. doi:10.1109/LRA.2022.3184795
  • Chen, K., Xue, B., Zhang, M., & Zhou, F. (2022) "An Evolutionary Multitasking-Based Feature Selection Method for High-Dimensional Classification". IEEE Transactions on Cybernetics, 52(7), 7172-7186. doi:10.1109/TCYB.2020.3042243
  • Ain, Q. U., Al-Sahaf, H., Xue, B., & Zhang, M. (2022) "Genetic programming for automatic skin cancer image classification". Expert Systems with Applications, 197. doi:10.1016/j.eswa.2022.116680
  • Zhu, J., Jang-Jaccard, J., Singh, A., Welch, I., AL-Sahaf, H., & Camtepe, S. (2022) "A few-shot meta-learning based siamese neural network using entropy features for ransomware classification". Computers and Security, 117. doi:10.1016/j.cose.2022.102691
  • Wang, C., Ma, H., Chen, G., & Hartmann, S. (2022) "Memetic EDA-Based Approaches to QoS-Aware Fully Automated Semantic Web Service Composition". IEEE Transactions on Evolutionary Computation, 26(3), 570-584. doi:10.1109/TEVC.2021.3127633
  • Liu, Y., Browne, W. N., & Xue, B. (2022) "Visualizations for rule-based machine learning". Natural Computing, 21(2), 243-264. doi:10.1007/s11047-020-09840-0
  • Jia, Y. H., Mei, Y., & Zhang, M. (2022) "Contribution-Based Cooperative Co-Evolution for Nonseparable Large-Scale Problems With Overlapping Subcomponents". IEEE Transactions on Cybernetics, 52(6), 4246-4259. doi:10.1109/TCYB.2020.3025577
  • Chen, K., Xue, B., Zhang, M., & Zhou, F. (2022) "Evolutionary Multitasking for Feature Selection in High-Dimensional Classification via Particle Swarm Optimization". IEEE Transactions on Evolutionary Computation, 26(3), 446-460. doi:10.1109/TEVC.2021.3100056
  • Bi, Y., Xue, B., & Zhang, M. (2022) "Dual-Tree Genetic Programming for Few-Shot Image Classification". IEEE Transactions on Evolutionary Computation, 26(3), 555-569. doi:10.1109/TEVC.2021.3100576
  • Ceschin, F., Botacin, M., Gomes, H. M., Pinagé, F., Oliveira, L. S., & Grégio, A. (2022) "Fast & Furious: Modelling Malware Detection as Evolving Data Streams". __. doi:10.48550/arxiv.2205.12311
  • Tian, Y., Xiong, T., Liu, Z., Mei, Y., & Wan, L. (2022) "Multi-Objective multi-skill resource-constrained project scheduling problem with skill switches: Model and evolutionary approaches". Computers and Industrial Engineering, 167. doi:10.1016/j.cie.2021.107897
  • Madukwe, K. J., Gao, X., & Xue, B. (2022) "Token replacement-based data augmentation methods for hate speech detection". World Wide Web, 25(3), 1129-1150. doi:10.1007/s11280-022-01025-2
  • Bi, Y., Xue, B., & Zhang, M. (2022) "Using a small number of training instances in genetic programming for face image classification". Information Sciences, 593, 488-504. doi:10.1016/j.ins.2022.01.055
  • Abbasi, M. S., Al-Sahaf, H., Mansoori, M., & Welch, I. (2022) "Behavior-based ransomware classification: A particle swarm optimization wrapper-based approach for feature selection". Applied Soft Computing, 121. doi:10.1016/j.asoc.2022.108744
  • Bifet, A., Ferreira, C., Gama, J., & Gomes, H. M. (2022) "EDITORIAL MESSAGE Special Track on Data Streams". In Proceedings of the ACM Symposium on Applied Computing (pp. 449). doi:10.1145/3535426
  • Mandal, R., Azam, B., Verma, B., & Zhang, M. (2022) "Deep Learning Model with GA based Feature Selection and Context Integration". __. doi:10.48550/arxiv.2204.06189
  • Hancer, E., Xue, B., & Zhang, M. (2022) "Fuzzy filter cost-sensitive feature selection with differential evolution". Knowledge-Based Systems, 241. doi:10.1016/j.knosys.2022.108259
  • Fang, W., Zhu, H., & Mei, Y. (2022) "Hybrid meta-heuristics for the unrelated parallel machine scheduling problem with setup times". Knowledge-Based Systems, 241. doi:10.1016/j.knosys.2022.108193
  • Gupta, A., Ong, Y. S., De Jong, K. A., & Zhang, M. (2022) "Guest Editorial Special Issue on Multitask Evolutionary Computation". IEEE Transactions on Evolutionary Computation, 26(2), 202-205. doi:10.1109/TEVC.2022.3156325
  • Chen, Q., Xue, B., & Zhang, M. (2022) "Rademacher Complexity for Enhancing the Generalization of Genetic Programming for Symbolic Regression". IEEE Transactions on Cybernetics, 52(4), 2382-2395. doi:10.1109/TCYB.2020.3004361
  • Chen, F., Wei, J., Xue, B., & Zhang, M. (2022) "Feature fusion and kernel selective in Inception-v4 network". Applied Soft Computing, 119. doi:10.1016/j.asoc.2022.108582
  • Bi, Y., Xue, B., & Zhang, M. (2022) "Learning and Sharing: A Multitask Genetic Programming Approach to Image Feature Learning". IEEE Transactions on Evolutionary Computation, 26(2), 218-232. doi:10.1109/TEVC.2021.3097043
  • Wen, C., Lu, M., Bi, Y., Zhang, S., Xue, B., Zhang, M., . . . Wu, W. (2022) "An Object-Based Genetic Programming Approach for Cropland Field Extraction". Remote Sensing, 14(5). doi:10.3390/rs14051275
  • Pei, W., Xue, B., Shang, L., & Zhang, M. (2022) "High-Dimensional Unbalanced Binary Classification by Genetic Programming with Multi-Criterion Fitness Evaluation and Selection". Evolutionary Computation, 30(1), 99-129. doi:10.1162/evco_a_00304
  • Manapragada, C., Gomes, H. M., Salehi, M., Bifet, A., & Webb, G. I. (2022) "An eager splitting strategy for online decision trees in ensembles". Data Mining and Knowledge Discovery, 36(2), 566-619. doi:10.1007/s10618-021-00816-x
  • Fan, Q., Bi, Y., Xue, B., & Zhang, M. (2022) "Genetic programming for feature extraction and construction in image classification". Applied Soft Computing, 118. doi:10.1016/j.asoc.2022.108509
  • Wang, S., Mei, Y., Zhang, M., & Yao, X. (2022) "Genetic Programming With Niching for Uncertain Capacitated Arc Routing Problem". IEEE Transactions on Evolutionary Computation, 26(1), 73-87. doi:10.1109/TEVC.2021.3095261
  • Wang, C., Ma, H., Chen, G., Hartmann, S., & Branke, J. (2022) "Robustness Estimation and Optimisation for Semantic Web Service Composition With Stochastic Service Failures". IEEE Transactions on Emerging Topics in Computational Intelligence, 6(1), 77-92. doi:10.1109/TETCI.2020.3027870
  • Haseeb, J., Mansoori, M., Hirose, Y., Al-Sahaf, H., & Welch, I. (2022) "Autoencoder-based feature construction for IoT attacks clustering". Future Generation Computer Systems, 127, 487-502. doi:10.1016/j.future.2021.09.025
  • Cassales, G., Gomes, H., Bifet, A., Pfahringer, B., & Senger, H. (2022) "Balancing Performance and Energy Consumption of Bagging Ensembles for the Classification of Data Streams in Edge Computing". __. doi:10.48550/arxiv.2201.06205
  • Zhao, Y., Chen, G., Ma, H., Zuo, X., & Ai, G. (2022) "Dynamic Bus Holding Control Using Spatial-Temporal Data – A Deep Reinforcement Learning Approach". In Unknown Book (Vol. 13728 LNAI, pp. 661-674). doi:10.1007/978-3-031-22695-3_46
  • Zhang, F., Mei, Y., Nguyen, S., & Zhang, M. (2022) "Phenotype Based Surrogate-Assisted Multi-objective Genetic Programming with Brood Recombination for Dynamic Flexible Job Shop Scheduling". In Proceedings of the 2022 IEEE Symposium Series on Computational Intelligence, SSCI 2022 (pp. 1218-1225). doi:10.1109/SSCI51031.2022.10022169
  • Zhang, F., Mei, Y., Nguyen, S., & Zhang, M. (2022) "Learning Strategies on Scheduling Heuristics of Genetic Programming in Dynamic Flexible Job Shop Scheduling". In 2022 IEEE Congress on Evolutionary Computation, CEC 2022 - Conference Proceedings. doi:10.1109/CEC55065.2022.9870243
  • Zhang, F., Mei, Y., Nguyen, S., & Zhang, M. (2022) "Importance-Aware Genetic Programming for Automated Scheduling Heuristics Learning in Dynamic Flexible Job Shop Scheduling". In Unknown Book (Vol. 13399 LNCS, pp. 48-62). doi:10.1007/978-3-031-14721-0_4
  • Yu, Y., Shi, T., Ma, H., & Chen, G. (2022) "A Genetic Programming-Based Hyper-Heuristic Approach for Multi-Objective Dynamic Workflow Scheduling in Cloud Environment". In 2022 IEEE Congress on Evolutionary Computation, CEC 2022 - Conference Proceedings. doi:10.1109/CEC55065.2022.9870403
  • Yang, Y., Chen, G., Ma, H., & Zhang, M. (2022) "Dual-Tree Genetic Programming for Deadline-Constrained Dynamic Workflow Scheduling in Cloud". In Unknown Book (Vol. 13740 LNCS, pp. 433-448). doi:10.1007/978-3-031-20984-0_31
  • Xue, B., Zhao, H., & Yao, W. (2022) "Deep Transfer Learning for IoT Intrusion Detection". In Proceedings - 2022 3rd International Conference on Computing, Networks and Internet of Things, CNIOT 2022 (pp. 88-94). doi:10.1109/CNIOT55862.2022.00023
  • Xu, M., Zhang, F., Mei, Y., & Zhang, M. (2022) "Genetic Programming with Multi-case Fitness for Dynamic Flexible Job Shop Scheduling". In 2022 IEEE Congress on Evolutionary Computation, CEC 2022 - Conference Proceedings. doi:10.1109/CEC55065.2022.9870340
  • Xu, M., Mei, Y., Zhang, F., & Zhang, M. (2022) "Genetic Programming with Cluster Selection for Dynamic Flexible Job Shop Scheduling". __.
  • Xu, B., Bi, Y., Xue, B., Schindler, J., Martin, B., & Zhang, M. (2022) "Automatically Designing U-Nets Using A Genetic Algorithm for Tree Image Segmentation". In Proceedings of the 2022 IEEE Symposium Series on Computational Intelligence, SSCI 2022 (pp. 626-633). doi:10.1109/SSCI51031.2022.10022182
  • Wood, J., Nguyen, B. H., Xue, B., Zhang, M., & Killeen, D. (2022) "Automated Fish Classification Using Unprocessed Fatty Acid Chromatographic Data: A Machine Learning Approach". In Unknown Book (Vol. 13728 LNAI, pp. 516-529). doi:10.1007/978-3-031-22695-3_36
  • Wang, P., Xue, B., Liang, J., & Zhang, M. (2022) "Niching-Assisted Genetic Programming for Finding Multiple High-Quality Classifiers". In Unknown Book (Vol. 13728 LNAI, pp. 279-293). doi:10.1007/978-3-031-22695-3_20
  • Wang, B., Pei, W., Xue, B., & Zhang, M. (2022) "A Multi-objective Genetic Algorithm to Evolving Local Interpretable Model-agnostic Explanations for Deep Neural Networks in Image Classification". IEEE Transactions on Evolutionary Computation. doi:10.1109/TEVC.2022.3225591
  • Trueman, J., Ma, H., Chen, A., & Hartmann, S. (2022) "Multi-objective Social Network Detection - A Graph Database Supported NSGA-II Based Approach". In Unknown Book (Vol. 13459 LNCS, pp. 21-33). doi:10.1007/978-3-031-15512-3_2
  • Tan, B., Ma, H., Mei, Y., & Zhang, M. (2022) "A Cooperative Coevolution Genetic Programming Hyper-Heuristics Approach for On-Line Resource Allocation in Container-Based Clouds". IEEE Transactions on Cloud Computing, 10(3), 1500-1514. doi:10.1109/TCC.2020.3026338
  • Steinmetz, D., Merz, F., Burmester, G., Ma, H., & Hartmann, S. (2022) "A Modeling Rule for Improving the Performance of Graph Models". In Unknown Book (Vol. 13607 LNCS, pp. 336-346). doi:10.1007/978-3-031-17995-2_24
  • Shi, G., Zhang, F., & Mei, Y. (2022) "A Novel Fitness Function for Genetic Programming in Dynamic Flexible Job Shop Scheduling". In 2022 IEEE Congress on Evolutionary Computation, CEC 2022 - Conference Proceedings. doi:10.1109/CEC55065.2022.9870235
  • Sargisson, F., Gao, X., & Xue, B. (2022) "Learning CNN architecture for multi-view text classification using genetic algorithms". In Proceedings of the 2022 IEEE Symposium Series on Computational Intelligence, SSCI 2022 (pp. 1507-1514). doi:10.1109/SSCI51031.2022.10022150
  • Robinson, D., Chen, Q., Xue, B., Killeen, D., Gordon, K. C., & Zhang, M. (2022) "A New Genetic Algorithm for Automated Spectral Pre-processing in Nutrient Assessment". In Unknown Book (Vol. 13224 LNCS, pp. 283-298). doi:10.1007/978-3-031-02462-7_19
  • Raymond, C., Chen, Q., Xue, B., & Zhang, M. (2022) "Multi-objective Genetic Programming with the Adaptive Weighted Splines Representation for Symbolic Regression". In Unknown Book (Vol. 13223 LNCS, pp. 51-67). doi:10.1007/978-3-031-02056-8_4
  • Petri, I., Chirila, I., Gomes, H. M., Bifet, A., & Rana, O. F. (2022) "Resource-Aware Edge-Based Stream Analytics". IEEE Internet Computing, 26(4), 79-88. doi:10.1109/MIC.2022.3152478
  • Pei, J., Mei, Y., Liu, J., & Yao, X. (2022) "An Investigation of Adaptive Operator Selection in Solving Complex Vehicle Routing Problem". In Unknown Book (Vol. 13629 LNCS, pp. 562-573). doi:10.1007/978-3-031-20862-1_41
  • Park, L. A. F., Gomes, H. M., Doborjeh, M., Zhao, Y., Williams, G., & Simoff, S. (2022) "Preface". Communications in Computer and Information Science, 1741 CCIS, v-vi.
  • Panda, S., Mei, Y., & Zhang, M. (2022) "Simplifying Dispatching Rules in Genetic Programming for Dynamic Job Shop Scheduling". In Unknown Book (Vol. 13222 LNCS, pp. 95-110). doi:10.1007/978-3-031-04148-8_7
  • Palli, A. S., Jaafar, J., Hashmani, M. A., Gomes, H. M., & Gilal, A. R. (2022) "A Hybrid Sampling Approach for Imbalanced Binary and Multi-Class Data Using Clustering Analysis". IEEE Access, 10, 118639-118653. doi:10.1109/ACCESS.2022.3218463
  • Masood, A., Chen, G., Mei, Y., Al-Sahaf, H., & Zhang, M. (2022) "Genetic Programming Hyper-heuristic with Gaussian Process-based Reference Point Adaption for Many-Objective Job Shop Scheduling". In 2022 IEEE Congress on Evolutionary Computation, CEC 2022 - Conference Proceedings. doi:10.1109/CEC55065.2022.9870322
  • Mandal, R., Azam, B., Verma, B., & Zhang, M. (2022) "Genetic Algorithms for Optimising Context-based Neural Networks for Image Segmentation". In Proceedings of the 2022 IEEE Symposium Series on Computational Intelligence, SSCI 2022 (pp. 642-648). doi:10.1109/SSCI51031.2022.10022103
  • MacLachlan, J., Mei, Y., Zhang, F., & Zhang, M. (2022) "Genetic Programming for Vehicle Subset Selection in Ambulance Dispatching". In 2022 IEEE Congress on Evolutionary Computation, CEC 2022 - Conference Proceedings. doi:10.1109/CEC55065.2022.9870323
  • Lu, Y., Nguyen, B. H., & Xue, B. (2022) "Label Clustering for Particle Swarm Optimisation based Multi-Label Feature Selection". In Proceedings of the 2022 IEEE Symposium Series on Computational Intelligence, SSCI 2022 (pp. 1515-1522). doi:10.1109/SSCI51031.2022.10022306
  • Liu, G., Ma, J., Hu, T., & Gao, X. (2022) "A feature selection method with feature ranking using genetic programming". Connection Science, 34(1), 1146-1168. doi:10.1080/09540091.2022.2049702
  • Lin, B. C., Liu, X. F., & Mei, Y. (2022) "Efficient Extended Ant Colony Optimization for Capacitated Electric Vehicle Routing". In Proceedings of the 2022 IEEE Symposium Series on Computational Intelligence, SSCI 2022 (pp. 504-511). doi:10.1109/SSCI51031.2022.10022179
  • Lee, A., Gomes, H. M., & Zhang, Y. (2022) "Balancing the Stability-Plasticity Dilemma with Online Stability Tuning for Continual Learning". In Proceedings of the International Joint Conference on Neural Networks Vol. 2022-July. doi:10.1109/IJCNN55064.2022.9892055
  • Jiao, R., Xue, B., & Zhang, M. (2022) "Solving Multi-objective Feature Selection Problems in Classification via Problem Reformulation and Duplication Handling". IEEE Transactions on Evolutionary Computation. doi:10.1109/TEVC.2022.3215745
  • Jiao, R., Xue, B., & Zhang, M. (2022) "Handling Different Preferences Between Objectives for Multi-objective Feature Selection in Classification". In Unknown Book (Vol. 13728 LNAI, pp. 237-251). doi:10.1007/978-3-031-22695-3_17
  • Huang, Z., Zhang, F., Mei, Y., & Zhang, M. (2022) "An Investigation of Multitask Linear Genetic Programming for Dynamic Job Shop Scheduling". In Unknown Book (Vol. 13223 LNCS, pp. 162-178). doi:10.1007/978-3-031-02056-8_11
  • Huang, Z., Mei, Y., Zhang, F., & Zhang, M. (2022) "A Further Investigation to Improve Linear Genetic Programming in Dynamic Job Shop Scheduling". In Proceedings of the 2022 IEEE Symposium Series on Computational Intelligence, SSCI 2022 (pp. 496-503). doi:10.1109/SSCI51031.2022.10022208
  • Huang, V., Wang, C., Ma, H., Chen, G., & Christopher, K. (2022) "Cost-Aware Dynamic Multi-Workflow Scheduling in Cloud Data Center Using Evolutionary Reinforcement Learning". In Unknown Book (Vol. 13740 LNCS, pp. 449-464). doi:10.1007/978-3-031-20984-0_32
  • Huang, J., Xue, B., Sun, Y., & Zhang, M. (2022) "EDE-NAS: An Eclectic Differential Evolution Approach to Single-Path Neural Architecture Search". In Unknown Book (Vol. 13728 LNAI, pp. 116-130). doi:10.1007/978-3-031-22695-3_9
  • Gunasekara, N., Gomes, H. M., Pfahringer, B., & Bifet, A. (2022) "Online Hyperparameter Optimization for Streaming Neural Networks". In Proceedings of the International Joint Conference on Neural Networks Vol. 2022-July. doi:10.1109/IJCNN55064.2022.9891953
  • Gunasekara, N., Gomes, H., Bifet, A., & Pfahringer, B. (2022) "Adaptive Online Domain Incremental Continual Learning". In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 13529 LNCS (pp. 491-502). doi:10.1007/978-3-031-15919-0_41
  • Gunasekara, N., Gomes, H., Bifet, A., & Pfahringer, B. (2022) "Adaptive Neural Networks for Online Domain Incremental Continual Learning". In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 13601 LNAI (pp. 89-103). doi:10.1007/978-3-031-18840-4_7
  • Fan, Q., Bi, Y., Xue, B., & Zhang, M. (2022) "Evolving Effective Ensembles for Image Classification Using Multi-objective Multi-tree Genetic Programming". In Unknown Book (Vol. 13728 LNAI, pp. 294-307). doi:10.1007/978-3-031-22695-3_21
  • Escott, K. R., Ma, H., & Chen, G. (2022) "Transfer Learning Assisted GPHH for Dynamic Multi-Workflow Scheduling in Cloud Computing". In Unknown Book (Vol. 13151 LNAI, pp. 440-451). doi:10.1007/978-3-030-97546-3_36
  • de Silva, A., Chen, A., Ma, H., & Nekooei, M. (2022) "Genetic Algorithm with a Novel Leiden-based Mutation Operator for Community Detection". In Unknown Book (Vol. 13728 LNAI, pp. 252-265). doi:10.1007/978-3-031-22695-3_18
  • Dang, B. T., Nguyen, B. H., & Andreae, P. (2022) "Operation-based Greedy Algorithm for Discounted Knapsack Problem". In Unknown Book (Vol. 13728 LNAI, pp. 646-660). doi:10.1007/978-3-031-22695-3_45
  • Curran, B., Nekooei, S. M., & Chen, G. (2022) "Accurate New Zealand Wildlife Image Classification-Deep Learning Approach". In Unknown Book (Vol. 13151 LNAI, pp. 632-644). doi:10.1007/978-3-030-97546-3_51
  • Chen, Y., Shi, T., Ma, H., & Chen, G. (2022) "Automatically Design Heuristics for Multi-Objective Location-Aware Service Brokering in Multi-Cloud". In Proceedings - 2022 IEEE International Conference on Services Computing, SCC 2022 (pp. 206-214). doi:10.1109/SCC55611.2022.00039
  • Chen, Q., Xue, B., & Zhang, M. (2022) "Genetic Programming for Instance Transfer Learning in Symbolic Regression". IEEE Transactions on Cybernetics, 52(1), 25-38. doi:10.1109/TCYB.2020.2969689
  • Chen, Q., & Xue, B. (2022) "Generalisation in Genetic Programming for Symbolic Regression: Challenges and Future Directions". In Women in Engineering and Science (pp. 281-302). Springer International Publishing. doi:10.1007/978-3-030-79092-9_13
  • Chanajitt, R., Pfahringer, B., Gomes, H. M., & Yogarajan, V. (2022) "Multiclass Malware Classification Using Either Static Opcodes or Dynamic API Calls". In Unknown Book (Vol. 13728 LNAI, pp. 427-441). doi:10.1007/978-3-031-22695-3_30
  • Chanajitt, R., Pfahringer, B., & Gomes, H. M. (2022) "A Comparison of Neural Network Architectures for Malware Classification Based on Noriben Operation Sequences". In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 13529 LNCS (pp. 428-440). doi:10.1007/978-3-031-15919-0_36
  • Andersen, H., Lensen, A., Browne, W. N., & Mei, Y. (2022) "Evolving Counterfactual Explanations with Particle Swarm Optimization and Differential Evolution". In 2022 IEEE Congress on Evolutionary Computation, CEC 2022 - Conference Proceedings. doi:10.1109/CEC55065.2022.9870283
  • Al-Sahaf, H., Gregory, M. A., & Welch, I. (2022) "Welcome Message". 2022 32nd International Telecommunication Networks and Applications Conference, ITNAC 2022. doi:10.1109/ITNAC55475.2022.9998403
  • Allen, J. M. U., Bennett, J. L., Clark, Z. L., Escott, K. R., Fa’avae, D. T. M., Kaulamatoa, J. L., . . . Woolner, V. H. (2022) "Relational and collective excellence: unfolding the potential of Pacific early career researchers". Journal of the Royal Society of New Zealand, 52(S1), 75-91. doi:10.1080/03036758.2022.2093228
  • Al Mamun, A., Al-Sahaf, H., Welch, I., & Camtepe, S. (2022) "Advanced Persistent Threat Detection: A Particle Swarm Optimization Approach". In 2022 32nd International Telecommunication Networks and Applications Conference, ITNAC 2022 (pp. 42-49). doi:10.1109/ITNAC55475.2022.9998358
  • Akindele, T., Tan, B., Mei, Y., & Ma, H. (2022) "Hybrid Grouping Genetic Algorithm for Large-Scale Two-Level Resource Allocation of Containers in the Cloud". In Unknown Book (Vol. 13151 LNAI, pp. 519-530). doi:10.1007/978-3-030-97546-3_42
  • Ain, Q. U. I., Xue, B., Al-Sahaf, H., & Zhang, M. (2022) "A Genetic Programming Approach to Automatically Construct Informative Attributes for Mammographic Density Classification". In IEEE International Conference on Data Mining Workshops, ICDMW Vol. 2022-November (pp. 378-387). doi:10.1109/ICDMW58026.2022.00057