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

  • Wang, S., Mei, Y., Park, J., & Zhang, M. (2019) "Evolving Ensembles of Routing Policies using Genetic Programming for Uncertain Capacitated Arc Routing Problem". In 2019 IEEE Symposium Series on Computational Intelligence, SSCI 2019 (pp. 1628-1635). doi:10.1109/SSCI44817.2019.9002749
  • Wang, S., Mei, Y., Park, J., & Zhang, M. (2019) "A Two-Stage Genetic Programming Hyper-Heuristic for Uncertain Capacitated Arc Routing Problem". In 2019 IEEE Symposium Series on Computational Intelligence, SSCI 2019 (pp. 1606-1613). doi:10.1109/SSCI44817.2019.9002912
  • Pei, W., Xue, B., Zhang, M., & Shang, L. (2019) "A Cost-sensitive Genetic Programming Approach for High-dimensional Unbalanced Classification". In 2019 IEEE Symposium Series on Computational Intelligence, SSCI 2019 (pp. 1770-1777). doi:10.1109/SSCI44817.2019.9003041
  • O'Neill, D., Xue, B., & Zhang, M. (2019) "The Evolution of Adjacency Matrices for Sparsity of Connection in DenseNets". In International Conference Image and Vision Computing New Zealand Vol. 2019-December. doi:10.1109/IVCNZ48456.2019.8961027
  • Le Nguyen, M. H., Gomes, H. M., & Bifet, A. (2019) "Semi-supervised Learning over Streaming Data using MOA". In Proceedings - 2019 IEEE International Conference on Big Data, Big Data 2019 (pp. 553-562). doi:10.1109/BigData47090.2019.9006217
  • Kho, Y. H., Watterson, C., Andreae, P., & Nekooei, M. (2019) "An analysis of students' writing: The design of an online repository as a writing support". In TALE 2019 - 2019 IEEE International Conference on Engineering, Technology and Education. doi:10.1109/TALE48000.2019.9225963
  • Karunakaran, D., Mei, Y., & Zhang, M. (2019) "Multitasking Genetic Programming for Stochastic Team Orienteering Problem with Time Windows". In 2019 IEEE Symposium Series on Computational Intelligence, SSCI 2019 (pp. 1598-1605). doi:10.1109/SSCI44817.2019.9002804
  • Gomes, H. M., Mello, R. F. D., Pfahringer, B., & Bifet, A. (2019) "Feature Scoring using Tree-Based Ensembles for Evolving Data Streams". In Proceedings - 2019 IEEE International Conference on Big Data, Big Data 2019 (pp. 761-769). doi:10.1109/BigData47090.2019.9006366
  • Desai, J., Nguyen, B. H., & Xue, B. (2019) "Multi-Label Feature Selection Using Particle Swarm Optimization: Novel Local Search Mechanisms". In 2019 IEEE Symposium Series on Computational Intelligence, SSCI 2019 (pp. 1762-1769). doi:10.1109/SSCI44817.2019.9002734
  • Al-Helali, B., Chen, Q., Xue, B., & Zhang, M. (2019) "A Genetic Programming-based Wrapper Imputation Method for Symbolic Regression with Incomplete Data". In 2019 IEEE Symposium Series on Computational Intelligence, SSCI 2019 (pp. 2395-2402). doi:10.1109/SSCI44817.2019.9002861
  • Ceschin, F., Botacin, M., Gomes, H. M., Oliveira, L. S., & Grégio, A. (2019) "Shallow Security". In Proceedings of the 3rd Reversing and Offensive-oriented Trends Symposium. ACM. doi:10.1145/3375894.3375898
  • Gomes, H. M., Read, J., Bifet, A., Barddal, J. P., & Gama, J. (2019) "Machine learning for streaming data". ACM SIGKDD Explorations Newsletter, 21(2), 6-22. doi:10.1145/3373464.3373470
  • MacLachlan, J., Mei, Y., Branke, J., & Zhang, M. (2019) "Genetic Programming Hyper-Heuristics with Vehicle Collaboration for Uncertain Capacitated Arc Routing Problems". __. doi:10.48550/arxiv.1911.08650
  • Mirghasemi, S., Andreae, P., & Zhang, M. (2019) "Domain-independent severely noisy image segmentation via adaptive wavelet shrinkage using particle swarm optimization and fuzzy C-means". Expert Systems with Applications, 133, 126-150. doi:10.1016/j.eswa.2019.04.050
  • Gomes, H. M., Read, J., & Bifet, A. (2019) "Streaming random patches for evolving data stream classification". In Proceedings - IEEE International Conference on Data Mining, ICDM Vol. 2019-November (pp. 240-249). doi:10.1109/ICDM.2019.00034
  • Lensen, A., Xue, B., & Zhang, M. (2019) "Genetic Programming for Evolving Similarity Functions for Clustering: Representations and Analysis". __. doi:10.48550/arxiv.1910.10264
  • Chen, G. (2019) "A New Framework for Multi-Agent Reinforcement Learning -- Centralized Training and Exploration with Decentralized Execution via Policy Distillation". arXiv.
  • Gomes, H. M., Bifet, A., Read, J., Barddal, J. P., Enembreck, F., Pfahringer, B., . . . Abdessalem, T. (2019) "Correction to: Adaptive random forests for evolving data stream classification (Machine Learning, (2017), 106, 9-10, (1469-1495), 10". 1007/s10994-017-5642-8). Machine Learning, 108(10), 1877-1878. doi:10.1007/s10994-019-05793-3
  • Sun, Y., Xue, B., Zhang, M., & Yen, G. G. (2019) "A New Two-Stage Evolutionary Algorithm for Many-Objective Optimization". IEEE Transactions on Evolutionary Computation, 23(5), 748-761. doi:10.1109/TEVC.2018.2882166
  • Ma, J., Xue, B., & Zhang, M. (2019) "A hybrid filter-wrapper feature selection approach for authorship attribution". International Journal of Innovative Computing, Information and Control, 15(5), 1989-2006. doi:10.24507/ijicic.15.05.1989
  • Jiao, R., Zeng, S., & Li, C. (2019) "A feasible-ratio control technique for constrained optimization". Information Sciences, 502, 201-217. doi:10.1016/j.ins.2019.06.030
  • Granatyr, J., Gomes, H. M., DIas, J. M., Paiva, A. M., Nunes, M. A. S. N., Scalabrin, E. E., & Spak, F. (2019) "Inferring trust using personality aspects extracted from texts". In Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics Vol. 2019-October (pp. 3840-3846). doi:10.1109/SMC.2019.8914641
  • Evans, B. P., Al-Sahaf, H., Xue, B., & Zhang, M. (2019) "Genetic Programming and Gradient Descent: A Memetic Approach to Binary Image Classification". __. doi:10.48550/arxiv.1909.13030
  • Xue, Y., Xue, B., & Zl, M. (2019) "Self-Adaptive particle swarm optimization for large-scale feature selection in classification". ACM Transactions on Knowledge Discovery from Data, 13(5). doi:10.1145/3340848
  • Tran, B., Xue, B., & Zhang, M. (2019) "Genetic programming for multiple-feature construction on high-dimensional classification". Pattern Recognition, 93, 404-417. doi:10.1016/j.patcog.2019.05.006
  • Santana, R., Marti, L., & Zhang, M. (2019) "GP-based methods for domain adaptation: using brain decoding across subjects as a test-case". Genetic Programming and Evolvable Machines, 20(3), 385-411. doi:10.1007/s10710-019-09352-6
  • Azari, S., Xue, B., Zhang, M., & Peng, L. (2019) "Improving the Results of De novo Peptide Identification via Tandem Mass Spectrometry Using a Genetic Programming-based Scoring Function for Re-ranking Peptide-Spectrum Matches". __. doi:10.48550/arxiv.1908.08010
  • Sun, Y., Xue, B., Zhang, M., & Yen, G. G. (2019) "A Particle Swarm Optimization-Based Flexible Convolutional Autoencoder for Image Classification". IEEE Transactions on Neural Networks and Learning Systems, 30(8), 2295-2309. doi:10.1109/TNNLS.2018.2881143
  • Chen, Q., Zhang, M., & Xue, B. (2019) "Structural Risk Minimization-Driven Genetic Programming for Enhancing Generalization in Symbolic Regression". IEEE Transactions on Evolutionary Computation, 23(4), 703-717. doi:10.1109/TEVC.2018.2881392
  • Wang, B., Xue, B., & Zhang, M. (2019) "Particle Swarm Optimisation for Evolving Deep Neural Networks for Image Classification by Evolving and Stacking Transferable Blocks". __. doi:10.48550/arxiv.1907.12659
  • Azari, S., Xue, B., Zhang, M., & Peng, L. (2019) "Preprocessing Tandem Mass Spectra Using Genetic Programming for Peptide Identification". Journal of the American Society for Mass Spectrometry, 30(7), 1294-1307. doi:10.1007/s13361-019-02196-5
  • Zhang, M., & Cagnoni, S. (2019) "Evolutionary computation and evolutionary deep learning for image analysis, signal processing and pattern recognition". In GECCO 2019 Companion - Proceedings of the 2019 Genetic and Evolutionary Computation Conference Companion (pp. 1226-1251). doi:10.1145/3319619.3323388
  • Wang, C., Ma, H., Chen, G., & Hartmann, S. (2019) "A memetic NSGA-II with EDA-based local search for fully automated multiobjective web service composition". In GECCO 2019 Companion - Proceedings of the 2019 Genetic and Evolutionary Computation Conference Companion (pp. 421-422). doi:10.1145/3319619.3321937
  • Wang, B., Sun, Y., Xue, B., & Zhang, M. (2019) "Evolving deep neural networks by multi-objective particle swarm optimization for image classification". In GECCO 2019 - Proceedings of the 2019 Genetic and Evolutionary Computation Conference (pp. 490-498). doi:10.1145/3321707.3321735
  • Trung Nguyen, B., Browne, W. N., & Zhang, M. (2019) "Improvement of code fragment fitness to guide feature construction in XCS". In GECCO 2019 - Proceedings of the 2019 Genetic and Evolutionary Computation Conference (pp. 428-436). doi:10.1145/3321707.3321751
  • Tran, B., Xue, B., & Zhang, M. (2019) "Adaptive multi-subswarm optimisation for feature selection on high-dimensional classification". In GECCO 2019 - Proceedings of the 2019 Genetic and Evolutionary Computation Conference (pp. 481-489). doi:10.1145/3321707.3321713
  • Sadeghiram, S., Ma, H., & Chen, G. (2019) "A memetic algorithm with distance-guided crossover: Distributed data-intensive web service composition". In GECCO 2019 Companion - Proceedings of the 2019 Genetic and Evolutionary Computation Conference Companion (pp. 155-156). doi:10.1145/3319619.3322015
  • Pei, W., Xue, B., Shang, L., & Zhang, M. (2019) "Reuse of program trees in genetic programming with a new fitness function in high-dimensional unbalanced classification". In GECCO 2019 Companion - Proceedings of the 2019 Genetic and Evolutionary Computation Conference Companion (pp. 187-188). doi:10.1145/3319619.3321958
  • Nguyen, B. H., Xue, B., Zhang, M., & Andreae, P. (2019) "Population-based ensemble classifier induction for domain adaptation". In GECCO 2019 - Proceedings of the 2019 Genetic and Evolutionary Computation Conference (pp. 437-445). doi:10.1145/3321707.3321716
  • Liu, Y., Browne, W. N., & Xue, B. (2019) "Absumption to complement subsumption in learning classifier systems". In GECCO 2019 - Proceedings of the 2019 Genetic and Evolutionary Computation Conference (pp. 410-418). doi:10.1145/3321707.3321719
  • Evans, B. P., Xue, B., & Zhang, M. (2019) "What's inside the black-box? A genetic programming method for interpreting complex machine learning models". In GECCO 2019 - Proceedings of the 2019 Genetic and Evolutionary Computation Conference (pp. 1012-1020). doi:10.1145/3321707.3321726
  • Chen, Q., Xue, B., & Zhang, M. (2019) "Differential evolution for instance based transfer learning in genetic programming for symbolic regression". In GECCO 2019 Companion - Proceedings of the 2019 Genetic and Evolutionary Computation Conference Companion (pp. 161-162). doi:10.1145/3319619.3321941
  • Bi, Y., Xue, B., & Zhang, M. (2019) "An automated ensemble learning framework using genetic programming for image classification". In GECCO 2019 - Proceedings of the 2019 Genetic and Evolutionary Computation Conference (pp. 365-373). doi:10.1145/3321707.3321750
  • Escott, K. R., & Noble, J. (2019) "Design patterns for Angular Hotdraw". In ACM International Conference Proceeding Series. doi:10.1145/3361149.3361185
  • Zhang, F., Mei, Y., & Zhang, M. (2019) "A Two-Stage Genetic Programming Hyper-heuristic Approach with Feature Selection for Dynamic Flexible Job Shop Scheduling". In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO) (pp. 347-355). IEEE. doi:10.1145/3321707.3321790
  • Wang, S., Mei, Y., & Zhang, M. (2019) "Novel Ensemble Genetic Programming Hyper-Heuristics for Uncertain Capacitated Arc Routing Problem". In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO) (pp. 1093-1101). IEEE. doi:10.1145/3321707.3321797
  • Tan, B., Ma, H., & Mei, Y. (2019) "Novel genetic algorithm with dual chromosome representation for resource allocation in container-based clouds". In IEEE International Conference on Cloud Computing, CLOUD Vol. 2019-July (pp. 452-456). doi:10.1109/CLOUD.2019.00078
  • Shi, T., Ma, H., & Chen, G. (2019) "A genetic-based approach to location-aware cloud service brokering in multi-cloud environment". In Proceedings - 2019 IEEE International Conference on Services Computing, SCC 2019 - Part of the 2019 IEEE World Congress on Services (pp. 146-153). doi:10.1109/SCC.2019.00034
  • Liang, Y., Zhang, M., & Browne, W. N. (2019) "Figure-ground image segmentation using feature-based multi-objective genetic programming techniques". Neural Computing and Applications, 31(7), 3075-3094. doi:10.1007/s00521-017-3253-8
  • Boiko Ferreira, L. E., Murilo Gomes, H., Bifet, A., & Oliveira, L. S. (2019) "Adaptive Random Forests with Resampling for Imbalanced data Streams". In Proceedings of the International Joint Conference on Neural Networks Vol. 2019-July. doi:10.1109/IJCNN.2019.8852027
  • Barddal, J. P., Enembreck, F., Gomes, H. M., Bifet, A., & Pfahringer, B. (2019) "Boosting decision stumps for dynamic feature selection on data streams". Information Systems, 83, 13-29. doi:10.1016/j.is.2019.02.003
  • Ardeh, M. A., Mei, Y., & Zhang, M. (2019) "Genetic Programming Hyper-Heuristic with Knowledge Transfer for Uncertain Capacitated Arc Routing Problem". In Proceedings of the Genetic and Evolutionary Computation Conference Companion (GECCO) (pp. 334-335). IEEE. doi:10.1145/3319619.3321988
  • Zhang, F., Mei, Y., & Zhang, M. (2019) "Evolving Dispatching Rules for Multi-objective Dynamic Flexible Job Shop Scheduling via Genetic Programming Hyper-heuristics". In 2019 IEEE Congress on Evolutionary Computation, CEC 2019 - Proceedings (pp. 1366-1373). doi:10.1109/CEC.2019.8790112
  • Zhang, F., Mei, Y., & Zhang, M. (2019) "Can Stochastic Dispatching Rules Evolved by Genetic Programming Hyper-heuristics Help in Dynamic Flexible Job Shop Scheduling?". In 2019 IEEE Congress on Evolutionary Computation, CEC 2019 - Proceedings (pp. 41-48). doi:10.1109/CEC.2019.8790030
  • Yu, Y., Feng, Y., Ma, H., Chen, A., & Wang, C. (2019) "Achieving Flexible Scheduling of Heterogeneous Workflows in Cloud through a Genetic Programming Based Approach". In 2019 IEEE Congress on Evolutionary Computation, CEC 2019 - Proceedings (pp. 3102-3109). doi:10.1109/CEC.2019.8789896
  • Watts, T., Xue, B., & Zhang, M. (2019) "Blocky Net: A New NeuroEvolution Method". In 2019 IEEE Congress on Evolutionary Computation, CEC 2019 - Proceedings (pp. 586-593). doi:10.1109/CEC.2019.8790302
  • Wang, C., Ma, H., Chen, G., & Hartmann, S. (2019) "Evolutionary Multitasking for Semantic Web Service Composition". In 2019 IEEE Congress on Evolutionary Computation, CEC 2019 - Proceedings (pp. 2490-2497). doi:10.1109/CEC.2019.8790085
  • Viswambaran, R. A., Chen, G., Xue, B., & Nekooei, M. (2019) "Evolutionary Design of Recurrent Neural Network Architecture for Human Activity Recognition". In 2019 IEEE Congress on Evolutionary Computation, CEC 2019 - Proceedings (pp. 554-561). doi:10.1109/CEC.2019.8790050
  • Tran, B., Xue, B., & Zhang, M. (2019) "Variable-Length Particle Swarm Optimization for Feature Selection on High-Dimensional Classification". IEEE Transactions on Evolutionary Computation, 23(3), 473-487. doi:10.1109/TEVC.2018.2869405
  • Tan, B., Ma, H., & Mei, Y. (2019) "A Hybrid Genetic Programming Hyper-Heuristic Approach for Online Two-level Resource Allocation in Container-based Clouds". In 2019 IEEE Congress on Evolutionary Computation, CEC 2019 - Proceedings (pp. 2681-2688). doi:10.1109/CEC.2019.8790220
  • Shi, T., Ma, H., & Chen, G. (2019) "A Seeding-based GA for Location-Aware Workflow Deployment in Multi-cloud Environment". In 2019 IEEE Congress on Evolutionary Computation, CEC 2019 - Proceedings (pp. 3364-3371). doi:10.1109/CEC.2019.8790110
  • Shi, S., Chen, Y., Yao, X., & Zhang, M. (2019) "Lightweight Evolution Strategies for Nanoswimmers-oriented in Vivo Computation". In 2019 IEEE Congress on Evolutionary Computation, CEC 2019 - Proceedings (pp. 866-872). doi:10.1109/CEC.2019.8790356
  • Sadeghiram, S., Ma, H., & Chen, G. (2019) "Composing Distributed Data-intensive Web Services Using a Flexible Memetic Algorithm". 2019 IEEE Congress on Evolutionary Computation, CEC 2019 - Proceedings, 2832-2839. doi:10.1109/CEC.2019.8790132
  • Ribeiro, R., Casanova, D., Teixeira, M., Wirth, A., Gomes, H. M., Borges, A. P., & Enembreck, F. (2019) "Generating action plans for poultry management using artificial neural networks". Computers and Electronics in Agriculture, 161, 131-140. doi:10.1016/j.compag.2018.02.017
  • Raymond, C., Chen, Q., Xue, B., & Zhang, M. (2019) "Genetic Programming with Rademacher Complexity for Symbolic Regression". In 2019 IEEE Congress on Evolutionary Computation, CEC 2019 - Proceedings (pp. 2657-2664). doi:10.1109/CEC.2019.8790341
  • Pei, W., Xue, B., Shang, L., & Zhang, M. (2019) "New Fitness Functions in Genetic Programming for Classification with High-dimensional Unbalanced Data". In 2019 IEEE Congress on Evolutionary Computation, CEC 2019 - Proceedings (pp. 2779-2786). doi:10.1109/CEC.2019.8789974
  • Pearson, W., Tran, C. T., Zhang, M., & Xue, B. (2019) "Multi-Round Random Subspace Feature Selection for Incomplete Gene Expression Data". In 2019 IEEE Congress on Evolutionary Computation, CEC 2019 - Proceedings (pp. 2544-2551). doi:10.1109/CEC.2019.8790237
  • Nguyen, T. B., Browne, W. N., & Zhang, M. (2019) "Online Feature-Generation of Code Fragments for XCS to Guide Feature Construction". In 2019 IEEE Congress on Evolutionary Computation, CEC 2019 - Proceedings (pp. 3308-3315). doi:10.1109/CEC.2019.8789950
  • Ma, H., Da Silva, A. S., & Kuang, W. (2019) "NSGA-II with Local Search for Multi-objective Application Deployment in Multi-Cloud". In 2019 IEEE Congress on Evolutionary Computation, CEC 2019 - Proceedings (pp. 2800-2807). doi:10.1109/CEC.2019.8790006
  • Karunakaran, D., Mei, Y., Chen, G., & Zhang, M. (2019) "Active Sampling for Dynamic Job Shop Scheduling using Genetic Programming". In 2019 IEEE Congress on Evolutionary Computation, CEC 2019 - Proceedings (pp. 434-441). doi:10.1109/CEC.2019.8789923
  • Jiao, R., Zeng, S., Li, C., & Pedrycz, W. (2019) "Evolutionary Constrained Multi-objective Optimization using NSGA-II with Dynamic Constraint Handling". In 2019 IEEE Congress on Evolutionary Computation (CEC). IEEE. doi:10.1109/cec.2019.8790172
  • Irwin-Harris, W., Sun, Y., Xue, B., & Zhang, M. (2019) "A Graph-Based Encoding for Evolutionary Convolutional Neural Network Architecture Design". In 2019 IEEE Congress on Evolutionary Computation, CEC 2019 - Proceedings (pp. 546-553). doi:10.1109/CEC.2019.8790093
  • Fu, W., Zhang, M., & Johnston, M. (2019) "Bayesian genetic programming for edge detection". Soft Computing, 23(12), 4097-4112. doi:10.1007/s00500-018-3059-3
  • Fu, W., Xue, B., Gao, X., & Zhang, M. (2019) "Genetic Programming based Transfer Learning for Document Classification with Self-taught and Ensemble Learning". In 2019 IEEE Congress on Evolutionary Computation, CEC 2019 - Proceedings (pp. 2260-2267). doi:10.1109/CEC.2019.8790318
  • Chen, Q., Xue, B., & Zhang, M. (2019) "Instance based Transfer Learning for Genetic Programming for Symbolic Regression". In 2019 IEEE Congress on Evolutionary Computation, CEC 2019 - Proceedings (pp. 3006-3013). doi:10.1109/CEC.2019.8790217
  • Chen, Q., Xue, B., & Zhang, M. (2019) "Improving Generalization of Genetic Programming for Symbolic Regression with Angle-Driven Geometric Semantic Operators". IEEE Transactions on Evolutionary Computation, 23(3), 488-502. doi:10.1109/TEVC.2018.2869621
  • Bi, Y., Xue, B., & Zhang, M. (2019) "An Evolutionary Deep Learning Approach Using Genetic Programming with Convolution Operators for Image Classification". In 2019 IEEE Congress on Evolutionary Computation, CEC 2019 - Proceedings (pp. 3197-3204). doi:10.1109/CEC.2019.8790151
  • Azari, S., Zhang, M., Xue, B., & Peng, L. (2019) "Learning to Rank Peptide-Spectrum Matches Using Genetic Programming". In 2019 IEEE Congress on Evolutionary Computation, CEC 2019 - Proceedings (pp. 3244-3251). doi:10.1109/CEC.2019.8790049
  • Ardeh, M. A., Mei, Y., & Zhang, M. (2019) "Transfer Learning in Genetic Programming Hyper-heuristic for Solving Uncertain Capacitated Arc Routing Problem". In 2019 IEEE Congress on Evolutionary Computation, CEC 2019 - Proceedings (pp. 49-56). doi:10.1109/CEC.2019.8789920
  • Abdollahi, M., Gao, X., Mei, Y., Ghosh, S., & Li, J. (2019) "An Ontology-based Two-Stage Approach to Medical Text Classification with Feature Selection by Particle Swarm Optimisation". In 2019 IEEE Congress on Evolutionary Computation, CEC 2019 - Proceedings (pp. 119-126). doi:10.1109/CEC.2019.8790259
  • Huang, V., Chen, G., Fu, Q., & Wen, E. (2019) "Optimizing controller placement for software-defined networks". In 2019 IFIP/IEEE Symposium on Integrated Network and Service Management, IM 2019 (pp. 224-232).
  • Huang, V., Chen, G., & Fu, Q. (2019) "Effective Scheduling Function Design in SDN Through Deep Reinforcement Learning". In IEEE International Conference on Communications Vol. 2019-May. doi:10.1109/ICC.2019.8761938
  • Zhang, F., Mei, Y., & Zhang, M. (2019) "A New Representation in Genetic Programming for Evolving Dispatching Rules for Dynamic Flexible Job Shop Scheduling". In Proceedings of the European Conference on Evolutionary Computation in Combinatorial Optimization (EvoCOP) (pp. 33-49). Springer. doi:10.1007/978-3-030-16711-0_3
  • Liu, Y., Mei, Y., Zhang, M., & Zhang, Z. (2019) "A Predictive-Reactive Approach with Genetic Programming and Cooperative Co-evolution for Uncertain Capacitated Arc Routing Problem". Evolutionary Computation. doi:10.1162/evco_a_00256
  • Wang, B., Sun, Y., Xue, B., & Zhang, M. (2019) "Evolving Deep Neural Networks by Multi-objective Particle Swarm Optimization for Image Classification". __. doi:10.48550/arxiv.1904.09035
  • Liu, X., Shi, X., Lu, G., Deng, X., Zhou, H., Yan, Z., . . . Xue, B. (2019) "The synergistic lubricating mechanism of Sn-Ag-Cu and C60 on the worn surface of M50 self-lubricating material at elevated loads". Journal of Alloys and Compounds, 777, 271-284. doi:10.1016/j.jallcom.2018.11.021
  • Wang, B., Sun, Y., Xue, B., & Zhang, M. (2019) "A Hybrid GA-PSO Method for Evolving Architecture and Short Connections of Deep Convolutional Neural Networks". __. doi:10.48550/arxiv.1903.03893
  • Lin, Y., Andreae, P., Li, Z., Cai, J., & Li, H. (2019) "Real-time co-registered photoacoustic and ultrasonic imaging for early endometrial cancer detection driven by cylindrical diffuser". Journal of Innovative Optical Health Sciences, 12(2). doi:10.1142/S1793545819500020
  • Huang, V., Chen, G., Fu, Q., & Wen, E. (2019) "Optimizing Controller Placement for Software-Defined Networks". __. doi:10.48550/arxiv.1902.09451
  • Chen, G., & Peng, Y. (2019) "Off-Policy Actor-Critic in an Ensemble: Achieving Maximum General Entropy and Effective Environment Exploration in Deep Reinforcement Learning". arXiv.
  • Lensen, A., Xue, B., & Zhang, M. (2019) "Can Genetic Programming Do Manifold Learning Too?". __. doi:10.48550/arxiv.1902.02949
  • Azari, S., Xue, B., Zhang, M., & Peng, L. (2019) "GA-Novo: De Novo Peptide Sequencing via Tandem Mass Spectrometry using Genetic Algorithm". __. doi:10.48550/arxiv.1902.00845
  • Barddal, J. P., Enembreck, F., Gomes, H. M., Bifet, A., & Pfahringer, B. (2019) "Merit-guided dynamic feature selection filter for data streams". Expert Systems with Applications, 116, 227-242. doi:10.1016/j.eswa.2018.09.031
  • Sadeghiram, S., Ma, H., & Chen, G. (2019) "Composing Distributed Data-intensive Web Services Using a Flexible Memetic Algorithm". __. doi:10.48550/arxiv.1901.09894
  • Sadeghiram, S., Hui, M. A., & Chen, G. (2019) "Distance-Guided GA-Based Approach to Distributed Data-Intensive Web Service Composition". Retrieved from http://arxiv.org/abs/1901.
  • Sadeghiram, S., MA, H., & Chen, G. (2019) "Distance-Guided GA-Based Approach to Distributed Data-Intensive Web Service Composition". __. doi:10.48550/arxiv.1901.05564
  • Xue, B., Xu, Z., Liu, Y., & Ma, W. (2019) "Enhanced Mechanical and Tribological Properties of Graphene-Reinforced TiAl Matrix Composites". Tribology Transactions, 62(1), 117-126. doi:10.1080/10402004.2018.1523513
  • Zeng, S., Jiao, R., Li, C., & Wang, R. (2019) "Constrained optimisation by solving equivalent dynamic loosely-constrained multiobjective optimisation problem". International Journal of Bio-Inspired Computation, 13(2), 86. doi:10.1504/ijbic.2019.098406
  • Wang, C., Ma, H., Chen, G., & Hartmann, S. (2019) "Towards Robust Web Service Composition with Stochastic Service Failures Based on a Genetic Algorithm". In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 11919 LNAI (pp. 445-459). doi:10.1007/978-3-030-35288-2_36
  • Wang, C., Ma, H., & Chen, G. (2019) "Using EDA-Based Local Search to Improve the Performance of NSGA-II for Multiobjective Semantic Web Service Composition". In Unknown Book (Vol. 11707 LNCS, pp. 434-451). doi:10.1007/978-3-030-27618-8_32
  • Wang, B., Sun, Y., Xue, B., & Zhang, M. (2019) "A Hybrid GA-PSO Method for Evolving Architecture and Short Connections of Deep Convolutional Neural Networks". In Unknown Book (Vol. 11672 LNAI, pp. 650-663). doi:10.1007/978-3-030-29894-4_52
  • Tariq, H., Al-Sahaf, H., & Welch, I. (2019) "Modelling and prediction of resource utilization of hadoop clusters: A machine learning approach". In Proceedings of the 12th IEEE/ACM international conference on utility and cloud computing (pp. 93-100).
  • Steinmetz, D., Merz, F., Ma, H., & Hartmann, S. (2019) "A graph model for taxi ride sharing supported by graph databases". In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 11788 LNCS (pp. 108-116). doi:10.1007/978-3-030-33223-5_10
  • Sadeghiram, S., Ma, H., & Chen, G. (2019) "Composing Distributed Data-Intensive Web Services Using Distance-Guided Memetic Algorithm". In Unknown Book (Vol. 11707 LNCS, pp. 411-422). doi:10.1007/978-3-030-27618-8_30
  • Nguyen, S., Zhang, M., Johnston, M., & Tan, K. C. (2019) "Genetic programming for job shop scheduling". In Studies in Computational Intelligence (Vol. 779, pp. 143-167). doi:10.1007/978-3-319-91341-4_8
  • Muller, B., Al-Sahaf, H., Xue, B., & Zhang, M. (2019) "Transfer Learning: A Building Block Selection in Genetic Programming for Symbolic Regression". In Proceedings of the 2019 Genetic and Evolutionary Computation Conference (GECCO 2019) (pp. 350-351). ACM. doi:10.1145/3319619.3322072
  • Masood, A., Chen, G., Mei, Y., Al-Sahaf, H., & Zhang, M. (2019) "Genetic Programming with Pareto Local Search for Many-Objective Job Shop Scheduling". In Unknown Conference Vol. 11919 (pp. 536-548). Springer. doi:10.1007/978-3-030-35288-2_43
  • Madukwe, K. J., & Gao, X. (2019) "The Thin Line Between Hate and Profanity". In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 11919 LNAI (pp. 344-356). doi:10.1007/978-3-030-35288-2_28
  • Maclachlan, J., Mei, Y., Branke, J., & Zhang, M. (2019) "Genetic programming hyper-heuristics with vehicle collaboration for uncertain capacitated arc routing problems". Evolutionary Computation, 28(4), 563-593. doi:10.1162/evco_a_00267
  • Liu, X., Shi, X., Lu, G., Zhou, H., Deng, X., Yan, Z., . . . Xue, B. (2019) "Effect of different microporous parameters on mechanical and frictional properties of M50 self-lubricating materials: Simulation analysis and experimental study". Materials Research Express, 6(5). doi:10.1088/2053-1591/ab00b3
  • Lensen, A., Xue, B., & Zhang, M. (2019) "Genetic programming for evolving similarity functions for clustering: Representations and analysis". Evolutionary Computation, 28(4), 531-561. doi:10.1162/evco_a_00264
  • Lensen, A., Xue, B., & Zhang, M. (2019) "Can Genetic Programming Do Manifold Learning Too?". In GENETIC PROGRAMMING, EUROGP 2019 Vol. 11451 (pp. 114-130). doi:10.1007/978-3-030-16670-0_8
  • Lensen, A., Xue, B., & Zhang, M. (2019) "Can Genetic Programming Do Manifold Learning Too?". In Unknown Book (Vol. 11451 LNCS, pp. 114-130). doi:10.1007/978-3-030-16670-0_8
  • Lensen, A. (2019) "Evolutionary Feature Manipulation in Unsupervised Learning". (PhD Thesis).
  • Jiao, R., Zeng, S., Li, C., Jiang, Y., & Jin, Y. (2019) "A complete expected improvement criterion for Gaussian process assisted highly constrained expensive optimization". Information Sciences, 471, 80-96. doi:10.1016/j.ins.2018.09.003
  • Iqbal, M., Al-Sahaf, H., Xue, B., & Zhang, M. (2019) "Genetic Programming with Transfer Learning for Texture Image Classification". Soft Computing, 23, 12859-12871. doi:10.1007/s00500-019-03843-5
  • Gomes, H. M., Bifet, A., Fournier-Viger, P., Granatyr, J., & Read, J. (2019) "Network of experts: Learning from evolving data streams through network-based ensembles". In Unknown Book (Vol. 11953 LNCS, pp. 704-716). doi:10.1007/978-3-030-36708-4_58
  • Desai, J., Nguyen, B. H., & Xue, B. (2019) "Multi-label Feature Selection Using Particle Swarm Optimization: Novel Initialization Mechanisms". In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 11919 LNAI (pp. 510-522). doi:10.1007/978-3-030-35288-2_41
  • Deng, X., Shi, X., Liu, X., Liu, Y., & Xue, B. (2019) "Study on the thickness of lubricating film of M50-Ag self-lubricating composites". Lubrication Science, 31(1-2), 11-20. doi:10.1002/ls.1442
  • Barddal, J. P., Gomes, H. M., & Enembreck, F. (2019) "On Social Network-Based Algorithms for Data Stream Clustering". In Studies in Big Data (Vol. 41, pp. 297-317). doi:10.1007/978-3-319-89803-2_13
  • Azari, S., Xue, B., Zhang, M., & Peng, L. (2019) "Improving the Results of De novo Peptide Identification via Tandem Mass Spectrometry Using a Genetic Programming-Based Scoring Function for Re-ranking Peptide-Spectrum Matches". In Unknown Book (Vol. 11672 LNAI, pp. 474-487). doi:10.1007/978-3-030-29894-4_38
  • Azari, S., Xue, B., Zhang, M., & Peng, L. (2019) "GA-novo: De novo peptide sequencing via tandem mass spectrometry using genetic algorithm". In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 11454 LNCS (pp. 72-89). doi:10.1007/978-3-030-16692-2_6
  • Ansari Ardeh, M., Mei, Y., & Zhang, M. (2019) "A novel genetic programming algorithm with knowledge transfer for uncertain capacitated arc routing problem". In Unknown Book (Vol. 11670 LNAI, pp. 196-200). doi:10.1007/978-3-030-29908-8_16
  • Al-Shaboti, M., Welch, I., & Chen, A. (2019) "Iot application-centric access control (acac)". In Proceedings of the 2019 ACM Asia Conference on Computer and Communications Security (pp. 685-687).
  • Al-Shaboti, M., Chen, A., & Welch, I. (2019) "Automatic device selection and access policy generation based on user preference for iot activity workflow". In 2019 18th IEEE International Conference On Trust, Security And Privacy In Computing And Communications/13th IEEE International Conference On Big Data Science And Engineering (TrustCom/BigDataSE) (pp. 769-774). IEEE.
  • Al-Sahaf, H., & Welch, I. (2019) "A genetic programming approach to feature selection and construction for ransomware, phishing and spam detection". In Proceedings of the Genetic and Evolutionary Computation Conference Companion (pp. 332-333).
  • Al-Sahaf, H., Bi, Y., Chen, Q., Lensen, A., Mei, Y., Sun, Y., . . . Zhang, M. (2019) "A survey on evolutionary machine learning". Journal of the Royal Society of New Zealand (TNZR), 49, 205-228. doi:10.1080/03036758.2019.1609052
  • Al-Helali, B., Chen, Q., Xue, B., & Zhang, M. (2019) "Genetic Programming for Imputation Predictor Selection and Ranking in Symbolic Regression with High-Dimensional Incomplete Data". In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 11919 LNAI (pp. 523-535). doi:10.1007/978-3-030-35288-2_42
  • Ain, Q. U., Xue, B., Al-Sahaf, H., & Zhang, M. (2019) "Multi-tree Genetic Programming with a New Fitness Function for Melanoma Detection". In Proceedings of 2019 IEEE Congress on Evolutionary Computation (CEC 2019) (pp. 880-887). IEEE. doi:10.1109/CEC.2019.8790282
  • Ain, Q. U., Xue, B., Al-Sahaf, H., & Zhang, M. (2019) "Genetic Programming for Multiple Feature Construction in Skin Cancer Image Classification". In Proceedings of the 34th International Conference on Image and Vision Computing New Zealand (IVCNZ 2019) (pp. 1-6). IEEE. doi:10.1109/IVCNZ48456.2019.8961001
  • Afzali, S., Al-Sahaf, H., Xue, B., Hollitt, C., & Zhang, M. (2019) "Genetic Programming for Feature Selection and Feature Combination in Salient Object Detection". In Unknown Conference Vol. 11454 (pp. 308-324). Springer. doi:10.1007/978-3-030-16692-2_21
  • Abdollahi, M., Gao, X., Mei, Y., Ghosh, S., & Li, J. (2019) "Stratifying Risk of Coronary Artery Disease Using Discriminative Knowledge-Guided Medical Concept Pairings from Clinical Notes". In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 11672 LNAI (pp. 457-473). doi:10.1007/978-3-030-29894-4_37
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