School of Engineering and Computer Science Te Kura Mātai Pūkaha, Pūrorohiko

  • Londt, T., Gao, X., Andreae, P., & Mei, Y. (2023) "XC-NAS: A New Cellular Encoding Approach for Neural Architecture Search of Multi-path Convolutional Neural Networks". __. doi:10.48550/arxiv.2312.07760
  • Zhang, F., Mei, Y., Nguyen, S., Tan, K. C., & Zhang, M. (2023) "Task Relatedness-Based Multitask Genetic Programming for Dynamic Flexible Job Shop Scheduling". IEEE Transactions on Evolutionary Computation, 27(6), 1705-1719. doi:10.1109/TEVC.2022.3199783
  • Wang, S., Mei, Y., & Zhang, M. (2023) "A Multi-Objective Genetic Programming Algorithm With α Dominance and Archive for Uncertain Capacitated Arc Routing Problem". IEEE Transactions on Evolutionary Computation, 27(6), 1633-1647. doi:10.1109/TEVC.2022.3195165
  • 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
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  • Cai, X., Wang, K., Mei, Y., Li, Z., Zhao, J., & Zhang, Q. (2023) "Decomposition-Based Lin-Kernighan Heuristic With Neighborhood Structure Transfer for Multi/Many-Objective Traveling Salesman Problem". IEEE Transactions on Evolutionary Computation, 27(6), 1604-1617. doi:10.1109/TEVC.2022.3215174
  • 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.
  • Zhao, J., Xue, B., Vennell, R., & Zhang, M. (2023) "Large-Scale Mussel Farm Reconstruction with GPS Auxiliary". In International Conference on Image and Vision Computing New Zealand (IVCNZ).
  • Zhao, J., McMillan, C., Xue, B., Vennell, R., & Zhang, M. (2023) "Buoy Detection under Extreme Low-light Illumination for Intelligent Mussel Farming (Best Paper Award)". In International Conference on Image and Vision Computing New Zealand (IVCNZ).
  • McMillan, C., Zhao, J., Xue, B., Vennell, R., & Zhang, M. (2023) "Improving Buoy Detection with Deep Transfer Learning for Mussel Farm Automation". In International Conference on Image and Vision Computing New Zealand (IVCNZ 2023).
  • 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
  • Shi, T., Ma, H., Chen, G., & Hartmann, S. (2023) "Auto-Scaling Containerized Applications in Geo-Distributed Clouds". IEEE Transactions on Services Computing, 16(6), 4261-4274. doi:10.1109/TSC.2023.3317262
  • 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". __. doi:10.48550/arxiv.2310.20052
  • 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 International Conference on Information and Knowledge Management, Proceedings (pp. 4038-4042). 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.
  • Zhang, F., Mei, Y., Nguyen, S., Tan, K. C., & Zhang, M. (2023) "Instance-Rotation-Based Surrogate in Genetic Programming with Brood Recombination for Dynamic Job-Shop Scheduling". IEEE Transactions on Evolutionary Computation, 27(5), 1192-1206. doi:10.1109/TEVC.2022.3180693
  • Yu, H., Fan, X., Hou, Y., Pei, W., Ge, H., Yang, X., . . . Zhang, M. (2023) "Toward Realistic 3D Human Motion Prediction With a Spatio-Temporal Cross- Transformer Approach". IEEE Transactions on Circuits and Systems for Video Technology, 33(10), 5707-5720. doi:10.1109/TCSVT.2023.3255186
  • Yang, C., Cheung, Y. M., Ding, J., Tan, K. C., Xue, B., & Zhang, M. (2023) "Contrastive Learning Assisted-Alignment for Partial Domain Adaptation". IEEE Transactions on Neural Networks and Learning Systems, 34(10), 7621-7634. doi:10.1109/TNNLS.2022.3145034
  • Wang, P., Xue, B., Liang, J., & Zhang, M. (2023) "Differential Evolution With Duplication Analysis for Feature Selection in Classification". IEEE Transactions on Cybernetics, 53(10), 6676-6689. doi:10.1109/TCYB.2022.3213236
  • Huang, J., Xue, B., Sun, Y., Zhang, M., & Yen, G. G. (2023) "Particle Swarm Optimization for Compact Neural Architecture Search for Image Classification". IEEE Transactions on Evolutionary Computation, 27(5), 1298-1312. doi:10.1109/TEVC.2022.3217290
  • Li, N., Ma, L., Yu, G., Xue, B., Zhang, M., & Jin, Y. (2023) "Survey on Evolutionary Deep Learning: Principles, Algorithms, Applications, and Open Issues". ACM Computing Surveys, 56(2). doi:10.1145/3603704
  • Liu, G., Chen, G., & Huang, V. (2023) "Policy ensemble gradient for continuous control problems in deep reinforcement learning". Neurocomputing, 548. doi:10.1016/j.neucom.2023.126381
  • Li, A. D., Xue, B., & Zhang, M. (2023) "Multi-objective particle swarm optimization for key quality feature selection in complex manufacturing processes". Information Sciences, 641. doi:10.1016/j.ins.2023.119062
  • Cassales, G., Gomes, H. M., Bifet, A., Pfahringer, B., & Senger, H. (2023) "Balancing Performance and Energy Consumption of Bagging Ensembles for the Classification of Data Streams in Edge Computing". IEEE Transactions on Network and Service Management, 20(3), 3038-3054. doi:10.1109/TNSM.2022.3226505
  • Wang, P., Xue, B., Liang, J., & Zhang, M. (2023) "Feature clustering-Assisted feature selection with differential evolution". Pattern Recognition, 140. doi:10.1016/j.patcog.2023.109523
  • Pei, W., Xue, B., Shang, L., & Zhang, M. (2023) "Detecting Overlapping Areas in Unbalanced High-Dimensional Data Using Neighborhood Rough Set and Genetic Programming". IEEE Transactions on Evolutionary Computation, 27(4), 1130-1144. doi:10.1109/TEVC.2022.3203862
  • Nguyen, T. B., Browne, W. N., & Zhang, M. (2023) "ConCS: A Continual Classifier System for Continual Learning of Multiple Boolean Problems". IEEE Transactions on Evolutionary Computation, 27(4), 1057-1071. doi:10.1109/TEVC.2022.3210872
  • Li, S., Sun, Y., Yen, G. G., & Zhang, M. (2023) "Automatic Design of Convolutional Neural Network Architectures under Resource Constraints". IEEE Transactions on Neural Networks and Learning Systems, 34(8), 3832-3846. doi:10.1109/TNNLS.2021.3123105
  • Jiao, R., Xue, B., & Zhang, M. (2023) "A Multiform Optimization Framework for Constrained Multiobjective Optimization". IEEE Transactions on Cybernetics, 53(8), 5165-5177. doi:10.1109/TCYB.2022.3178132
  • Zhu, L., Zhang, F., Zhu, X., Chen, K., & Zhang, M. (2023) "Sample-Aware Surrogate-Assisted Genetic Programming for Scheduling Heuristics Learning in Dynamic Flexible Job Shop Scheduling". In GECCO 2023 - Proceedings of the 2023 Genetic and Evolutionary Computation Conference (pp. 384-392). doi:10.1145/3583131.3590440
  • Zhang, M., & Cagnoni, S. (2023) "Evolutionary Computation and Evolutionary Deep Learning for Image Analysis, Signal Processing and Pattern Recognition". In GECCO 2023 Companion - Proceedings of the 2023 Genetic and Evolutionary Computation Conference Companion (pp. 1533-1561). doi:10.1145/3583133.3595045
  • Zhang, H., Zhou, A., Chen, Q., Xue, B., & Zhang, M. (2023) "Genetic Programming-based Evolutionary Feature Construction for Heterogeneous Ensemble Learning [Hot of the Press]". In GECCO 2023 Companion - Proceedings of the 2023 Genetic and Evolutionary Computation Conference Companion (pp. 49-50). doi:10.1145/3583133.3595831
  • Zhang, H., Chen, Q., Xue, B., Banzhaf, W., & Zhang, M. (2023) "A Double Lexicase Selection Operator for Bloat Control in Evolutionary Feature Construction for Regression". In GECCO 2023 - Proceedings of the 2023 Genetic and Evolutionary Computation Conference (pp. 1194-1202). doi:10.1145/3583131.3590365
  • Yuan, G., Xue, B., & Zhang, M. (2023) "An Effective One-Shot Neural Architecture Search Method with Supernet Fine-Tuning for Image Classification". In GECCO 2023 - Proceedings of the 2023 Genetic and Evolutionary Computation Conference (pp. 615-623). doi:10.1145/3583131.3590438
  • Xue, B., & Zhang, M. (2023) "Evolutionary Computation for Feature Selection and Feature Construction". In GECCO 2023 Companion - Proceedings of the 2023 Genetic and Evolutionary Computation Conference Companion (pp. 1129-1156). doi:10.1145/3583133.3595050
  • Ul Ain, Q., Al-Sahaf, H., Xue, B., & Zhang, M. (2023) "A New Genetic Programming Representation for Feature Learning in Skin Cancer Detection". In GECCO 2023 Companion - Proceedings of the 2023 Genetic and Evolutionary Computation Conference Companion (pp. 707-710). doi:10.1145/3583133.3590550
  • Raymond, C., Chen, Q., Xue, B., & Zhang, M. (2023) "Fast and Efficient Local-Search for Genetic Programming Based Loss Function Learning". In GECCO 2023 - Proceedings of the 2023 Genetic and Evolutionary Computation Conference (pp. 1184-1193). doi:10.1145/3583131.3590361
  • Liu, Y., Cui, Y., Xue, B., Browne, W. N., Cheng, W., Li, Y., & Zeng, L. (2023) "Absumption and Subsumption based Learning Classifier System for Real-World Continuous-based Problems". In GECCO 2023 Companion - Proceedings of the 2023 Genetic and Evolutionary Computation Conference Companion (pp. 299-302). doi:10.1145/3583133.3590564
  • Huang, J., Xue, B., Sun, Y., & Zhang, M. (2023) "Multi-Objective Evolutionary Search of Compact Convolutional Neural Networks with Training-Free Estimation". In GECCO 2023 Companion - Proceedings of the 2023 Genetic and Evolutionary Computation Conference Companion (pp. 655-658). doi:10.1145/3583133.3590535
  • Demir, K., Nguyen, B., Xue, B., & Zhang, M. (2023) "Co-operative Co-evolutionary Many-objective Embedded Multi-label Feature Selection with Decomposition-based PSO". In GECCO 2023 - Proceedings of the 2023 Genetic and Evolutionary Computation Conference (pp. 438-446). doi:10.1145/3583131.3590373
  • Chen, Q., Xue, B., Banzhaf, W., & Zhang, M. (2023) "Relieving Genetic Programming from Coefficient Learning for Symbolic Regression via Correlation and Linear Scaling". In GECCO 2023 - Proceedings of the 2023 Genetic and Evolutionary Computation Conference (pp. 420-428). doi:10.1145/3583131.3595918
  • Zhang, F., Mei, Y., Nguyen, S., & Zhang, M. (2023) "Multitask Multiobjective Genetic Programming for Automated Scheduling Heuristic Learning in Dynamic Flexible Job-Shop Scheduling". IEEE Transactions on Cybernetics, 53(7), 4473-4486. doi:10.1109/TCYB.2022.3196887
  • Xu, M., Mei, Y., Zhu, S., Zhang, B., Xiang, T., Zhang, F., & Zhang, M. (2023) "Genetic Programming for Dynamic Workflow Scheduling in Fog Computing". IEEE Transactions on Services Computing, 16(4), 2657-2671. doi:10.1109/TSC.2023.3249160
  • Wang, P., Xue, B., Liang, J., & Zhang, M. (2023) "Multiobjective Differential Evolution for Feature Selection in Classification". IEEE Transactions on Cybernetics, 53(7), 4579-4593. doi:10.1109/TCYB.2021.3128540
  • Wang, C., Ma, H., Chen, G., & Hartmann, S. (2023) "Using an Estimation of Distribution Algorithm to Achieve Multitasking Semantic Web Service Composition". IEEE Transactions on Evolutionary Computation, 27(3), 490-504. doi:10.1109/TEVC.2022.3170899
  • Sadeghiram, S., Ma, H., & Chen, G. (2023) "Multi-objective distributed Web service composition—A link-dominance driven evolutionary approach". Future Generation Computer Systems, 143, 163-178. doi:10.1016/j.future.2023.01.001
  • John, T. C., Abbasi, M. S., Al-Sahaf, H., Welch, I., & Jang-Jaccard, J. (2023) "Evolving malice scoring models for ransomware detection: An automated approach by utilising genetic programming and cooperative coevolution". Computers and Security, 129. doi:10.1016/j.cose.2023.103215
  • Fan, Q., Bi, Y., Xue, B., & Zhang, M. (2023) "Genetic Programming for Image Classification: A New Program Representation With Flexible Feature Reuse". IEEE Transactions on Evolutionary Computation, 27(3), 460-474. doi:10.1109/TEVC.2022.3169490
  • Chen, G., & Huang, V. (2023) "Deep Metric Tensor Regularized Policy Gradient". __. doi:10.48550/arXiv.2305.11017
  • Xiao, Q., Niu, B., Xue, B., & Hu, L. (2023) "Graph Convolutional Reinforcement Learning for Advanced Energy-Aware Process Planning". IEEE Transactions on Systems, Man, and Cybernetics: Systems, 53(5), 2802-2814. doi:10.1109/TSMC.2022.3219407
  • Wang, P., Xue, B., Liang, J., & Zhang, M. (2023) "Feature Selection Using Diversity-Based Multi-objective Binary Differential Evolution". Information Sciences, 626, 586-606. doi:10.1016/j.ins.2022.12.117
  • Jia, Y. H., Mei, Y., & Zhang, M. (2023) "Learning Heuristics with Different Representations for Stochastic Routing". IEEE Transactions on Cybernetics, 53(5), 3205-3219. doi:10.1109/TCYB.2022.3169210
  • Bi, Y., Xue, B., & Zhang, M. (2023) "Multitask Feature Learning as Multiobjective Optimization: A New Genetic Programming Approach to Image Classification". IEEE Transactions on Cybernetics, 53(5), 3007-3020. doi:10.1109/TCYB.2022.3174519
  • Ain, Q. U., Al-Sahaf, H., Xue, B., & Zhang, M. (2023) "Automatically Diagnosing Skin Cancers from Multimodality Images Using Two-Stage Genetic Programming". IEEE Transactions on Cybernetics, 53(5), 2727-2740. doi:10.1109/TCYB.2022.3182474
  • Barddal, J. P., Gomes, H. M., & Enembreck, F. (2023) "Advances on Concept Drift Detection in Regression Tasks using Social Networks Theory". __. doi:10.48550/arxiv.2304.09788
  • Zeng, P., Song, X., Lensen, A., Ou, Y., Sun, Y., Zhang, M., & Lv, J. (2023) "Differentiable Genetic Programming for High-dimensional Symbolic Regression". __. doi:10.48550/arXiv.2304.08915
  • Lensen, A. (2023) "Genetic Programming, Explainability, and Interdisciplinary AI (Invited Talk)". Centrum Wiskunde & Informatica (CWI).
  • Schofield, F., Slyfield, L., & Lensen, A. (2023) "A Genetic Programming Encoder for Increasing Autoencoder Interpretability". In 26th European Conference on Genetic Programming. Brno, Czech Republic.
  • Mei, Y. (2023) "Invited Speaker of "Genetic Programming and Reinforcement Learning for Dynamic Scheduling"". IEEE Computational Intelligence Society Early Career Researcher Forum.
  • Yazdani-Asrami, M., Song, W., Morandi, A., De Carne, G., Murta-Pina, J., Pronto, A., . . . Abraham, A. (2023) "Roadmap on artificial intelligence and big data techniques for superconductivity". Superconductor Science and Technology, 36(4). doi:10.1088/1361-6668/acbb34
  • Wang, P., Xue, B., Liang, J., & Zhang, M. (2023) "Differential Evolution-Based Feature Selection: A Niching-Based Multiobjective Approach". IEEE Transactions on Evolutionary Computation, 27(2), 296-310. doi:10.1109/TEVC.2022.3168052
  • Ma, J., Gao, X., & Li, Y. (2023) "Multi-generation multi-criteria feature construction using Genetic Programming". Swarm and Evolutionary Computation, 78. doi:10.1016/j.swevo.2023.101285
  • Ardeh, M. A., Mei, Y., Zhang, M., & Yao, X. (2023) "Knowledge Transfer Genetic Programming With Auxiliary Population for Solving Uncertain Capacitated Arc Routing Problem". IEEE Transactions on Evolutionary Computation, 27(2), 311-325. doi:10.1109/TEVC.2022.3169289
  • Bifet, A., Gama, J., Gomes, H. M., & Veloso, B. (2023) "EDITORIAL MESSAGE: Special Track on Data Streams". Proceedings of the ACM Symposium on Applied Computing, 381.
  • Jia, Y. H., Mei, Y., & Zhang, M. (2023) "A Two-Stage Swarm Optimizer with Local Search for Water Distribution Network Optimization". IEEE Transactions on Cybernetics, 53(3), 1667-1681. doi:10.1109/TCYB.2021.3107900
  • Liu, Y., Sun, Y., Xue, B., Zhang, M., Yen, G. G., & Tan, K. C. (2023) "A Survey on Evolutionary Neural Architecture Search". IEEE Transactions on Neural Networks and Learning Systems, 34(2), 550-570. doi:10.1109/TNNLS.2021.3100554
  • Ceschin, F., Botacin, M., Gomes, H. M., Pinagé, F., Oliveira, L. S., & Grégio, A. (2023) "Fast & Furious: On the modelling of malware detection as an evolving data stream[Formula presented]". Expert Systems with Applications, 212. doi:10.1016/j.eswa.2022.118590
  • Bi, Y., Xue, B., & Zhang, M. (2023) "Instance Selection-Based Surrogate-Assisted Genetic Programming for Feature Learning in Image Classification". IEEE Transactions on Cybernetics, 53(2), 1118-1132. doi:10.1109/TCYB.2021.3105696
  • Bi, Y., Xue, B., Mesejo, P., Cagnoni, S., & Zhang, M. (2023) "A Survey on Evolutionary Computation for Computer Vision and Image Analysis: Past, Present, and Future Trends". IEEE Transactions on Evolutionary Computation, 27(1), 5-25. doi:10.1109/TEVC.2022.3220747
  • Raymond, C., Chen, Q., Xue, B., & Zhang, M. (2023) "Online Loss Function Learning". __. doi:10.48550/arxiv.2301.13247
  • O'Sullivan, F., Escott, K., Shaw, R., & Lensen, A. (2023) "Feature-based Image Matching for Identifying Individual Kākā". __. doi:10.48550/arXiv.2301.06678
  • O'Sullivan, F., Escott, K., Shaw, R., & Lensen, A. (2023) "Feature-based Image Matching for Identifying Individual Kākā". __. doi:10.48550/arXiv.2301.06678
  • Dang, B., Nguyen, A., Hong, Y., Nguyen, P., & Tran, B. -N. (2023) "Revealing the Hidden Structure of Affective States During Emotion Regulation in Synchronous Online Collaborative Learning". In The 56th Hawaii International Conference on System Sciences (HICSS).. Hawaii International Conference on System Sciences. Retrieved from https://hdl.handle.
  • Zhang, R., Sun, Y., & Zhang, M. (2023) "GPU Based Genetic Programming for Faster Feature Extraction in Binary Image Classification". IEEE Transactions on Evolutionary Computation. doi:10.1109/TEVC.2023.3294639
  • Zhang, H., Zhou, A., Chen, Q., Xue, B., & Zhang, M. (2023) "SR-Forest: A Genetic Programming based Heterogeneous Ensemble Learning Method". IEEE Transactions on Evolutionary Computation. doi:10.1109/TEVC.2023.3243172
  • Zhang, H., Chen, Q., Xue, B., Banzhaf, W., & Zhang, M. (2023) "Modular Multi-Tree Genetic Programming for Evolutionary Feature Construction for Regression". IEEE Transactions on Evolutionary Computation. doi:10.1109/TEVC.2023.3318638
  • Zhang, H., Chen, Q., Xue, B., Banzhaf, W., & Zhang, M. (2023) "A Semantic-Based Hoist Mutation Operator for Evolutionary Feature Construction in Regression". IEEE Transactions on Evolutionary Computation. doi:10.1109/TEVC.2023.3331234
  • Zhang, H., Chen, Q., Tonda, A., Xue, B., Banzhaf, W., & Zhang, M. (2023) "MAP-Elites with Cosine-Similarity for Evolutionary Ensemble Learning". In Unknown Book (Vol. 13986 LNCS, pp. 84-100). doi:10.1007/978-3-031-29573-7_6
  • Zeng, D., Liu, I., Bi, Y., Vennell, R., Briscoe, D., Xue, B., & Zhang, M. (2023) "A new multi-object tracking pipeline based on computer vision techniques for mussel farms". Journal of the Royal Society of New Zealand. doi:10.1080/03036758.2023.2240466
  • Zeng, D., Bi, Y., Liu, I., Xue, B., Vennell, R., & Zhang, M. (2023) "A New Genetic Programming-Based Approach to Object Detection in Mussel Farm Images". In International Conference Image and Vision Computing New Zealand. doi:10.1109/IVCNZ61134.2023.10343758
  • Yuan, G., Wang, B., Xue, B., & Zhang, M. (2023) "Particle Swarm Optimization for Efficiently Evolving Deep Convolutional Neural Networks Using an Autoencoder-based Encoding Strategy". IEEE Transactions on Evolutionary Computation. doi:10.1109/TEVC.2023.3245322
  • Yang, Y., Ma, H., Chen, G., & Hartmann, S. (2023) "A model-driven machine learning approach to dynamic multi-workflow scheduling". In CEUR Workshop Proceedings Vol. 3618.
  • Xue, B., Green, R., & Zhang, M. (2023) "Artificial Intelligence in New Zealand: applications and innovation". Journal of the Royal Society of New Zealand, 53(1), 1-5. doi:10.1080/03036758.2023.2170165
  • Xu, M., Mei, Y., Zhang, F., & Zhang, M. (2023) "Genetic Programming with Lexicase Selection for Large-scale Dynamic Flexible Job Shop Scheduling". IEEE Transactions on Evolutionary Computation. doi:10.1109/TEVC.2023.3244607
  • Xu, M., Mei, Y., Zhang, F., & Zhang, M. (2023) "Genetic Programming for Dynamic Flexible Job Shop Scheduling: Evolution With Single Individuals and Ensembles". IEEE Transactions on Evolutionary Computation. doi:10.1109/TEVC.2023.3334626
  • Wang, S., Mei, Y., & Zhang, M. (2023) "Explaining Genetic Programming-Evolved Routing Policies for Uncertain Capacitated Arc Routing Problems". IEEE Transactions on Evolutionary Computation. doi:10.1109/TEVC.2023.3238741
  • Wang, C., Ma, H., Chen, G., Huang, V., Yu, Y., & Christopher, K. (2023) "Energy-Aware Dynamic Resource Allocation in Container-Based Clouds via Cooperative Coevolution Genetic Programming". In Unknown Book (Vol. 13989 LNCS, pp. 539-555). doi:10.1007/978-3-031-30229-9_35
  • Sun, Z., Xue, B., Zhang, M., & Schindler, J. (2023) "An Improved Mask R-CNN for Instance Segmentation of Tree Crowns in Aerial Imagery". In International Conference Image and Vision Computing New Zealand. doi:10.1109/IVCNZ61134.2023.10343827
  • Sun, Y., Yen, G. G., & Zhang, M. (2023) "Preface". Studies in Computational Intelligence, 1070, v-vi.
  • Sun, Y., Yen, G. G., & Zhang, M. (2023) "Internet Protocol Based Architecture Design". In Studies in Computational Intelligence (Vol. 1070, pp. 181-192). doi:10.1007/978-3-031-16868-0_10
  • Sun, Y., Yen, G. G., & Zhang, M. (2023) "Hybrid GA and PSO for Architecture Design". In Studies in Computational Intelligence (Vol. 1070, pp. 171-180). doi:10.1007/978-3-031-16868-0_9
  • Sun, Y., Yen, G. G., & Zhang, M. (2023) "Evolutionary Deep Neural Architecture Search: Fundamentals, Methods, and Recent Advances". Springer International Publishing. doi:10.1007/978-3-031-16868-0
  • Sun, Y., Yen, G. G., & Zhang, M. (2023) "Evolutionary Computation". In Studies in Computational Intelligence (Vol. 1070, pp. 3-7). doi:10.1007/978-3-031-16868-0_1
  • Sun, Y., Yen, G. G., & Zhang, M. (2023) "End-to-End Performance Predictors". In Studies in Computational Intelligence (Vol. 1070, pp. 237-255). doi:10.1007/978-3-031-16868-0_14
  • Sun, Y., Yen, G. G., & Zhang, M. (2023) "Encoding Space Based on Directed Acyclic Graphs". In Studies in Computational Intelligence (Vol. 1070, pp. 223-236). doi:10.1007/978-3-031-16868-0_13
  • Sun, Y., Yen, G. G., & Zhang, M. (2023) "Distribution Training Framework for Architecture Design". In Studies in Computational Intelligence (Vol. 1070, pp. 311-329). doi:10.1007/978-3-031-16868-0_17
  • Sun, Y., Yen, G. G., & Zhang, M. (2023) "Differential Evolution for Architecture Design". In Studies in Computational Intelligence (Vol. 1070, pp. 193-202). doi:10.1007/978-3-031-16868-0_11
  • Sun, Y., Yen, G. G., & Zhang, M. (2023) "Deep Neural Networks". In Studies in Computational Intelligence (Vol. 1070, pp. 9-30). doi:10.1007/978-3-031-16868-0_2
  • Sun, Y., Yen, G. G., & Zhang, M. (2023) "Deep Neural Architecture Pruning". In Studies in Computational Intelligence (Vol. 1070, pp. 257-279). doi:10.1007/978-3-031-16868-0_15
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