Publications 2019 - Groups/ECRG | Te Kura Mātai Pūkaha, Pūrorohiko / School of Engineering and Computer Science | Te Herenga Waka

Zhang, Y., Mei, Y., Zhang, B., & Jiang, K. (2019) "Divide-and-Conquer Large Scale Capacitated Arc Routing Problems with Route Cutting Off Decomposition". __. doi:10.48550/arxiv.1912.12667
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 (pp. 1-9). 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
Wang, C., Ma, H., Chen, G., & Hartmann, S. (2019) "Memetic EDA-Based Approaches to Comprehensive Quality-Aware Automated Semantic Web Service Composition". __. doi:10.48550/arxiv.1906.07900
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) (pp. 1634-1641). 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
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