Publications 2016 - Groups/ECRG | Te Kura Mātai Pūkaha, Pūrorohiko / School of Engineering and Computer Science | Te Herenga Waka

Hartmann, S., Ma, H., & Vechsamutvaree, P. (2016) "Providing ontology-based privacy-aware data access through web services and service composition". Transactions on Large-Scale Data and Knowledge-Centred Systems, XXX Lecture Notes in Computer Science, vol 10130, 109-131. doi:10.1007/978-3-662-54054-1_5
Iqbal, M., Naqvi, S. S., Browne, W. N., Hollitt, C., & Zhang, M. (2016) "Learning feature fusion strategies for various image types to detect salient objects". Pattern Recognition, 60, 106-120. doi:10.1016/j.patcog.2016.05.020
Chen, G., Douch, C. I. J., & Zhang, M. (2016) "Accuracy-based learning classifier systems for multistep reinforcement learning: A fuzzy logic approach to handling continuous inputs and learning continuous actions". IEEE Transactions on Evolutionary Computation, 20(6), 953-971. doi:10.1109/TEVC.2016.2560139
Barddal, J. P., Gomes, H. M., Enembreck, F., & Barthès, J. P. (2016) "SNCStream⁺: Extending a high quality true anytime data stream clustering algorithm". Information Systems, 62, 60-73. doi:10.1016/j.is.2016.06.007
Xue, B., & Zhang, M. (2016) "Evolutionary computation for feature manipulation: Key challenges and future directions". In 2016 IEEE Congress on Evolutionary Computation, CEC 2016 (pp. 3061-3067). doi:10.1109/CEC.2016.7744176
Tran, C. T., Zhang, M., & Andreae, P. (2016) "Directly evolving classifiers for missing data using genetic programming". In 2016 IEEE Congress on Evolutionary Computation, CEC 2016 (pp. 5278-5285). doi:10.1109/CEC.2016.7748361
Phillips, T., Zhang, M., & Xue, B. (2016) "Genetic programming for evolving programs with recursive structures". In 2016 IEEE Congress on Evolutionary Computation, CEC 2016 (pp. 5044-5051). doi:10.1109/CEC.2016.7748329
Nguyen, S., Zhang, M., & Tan, K. C. (2016) "Maximising total weighted number of activities for reservation with slack". In 2016 IEEE Congress on Evolutionary Computation, CEC 2016 (pp. 3370-3377). doi:10.1109/CEC.2016.7744216
Nekooei, S. M., Chen, G., & Rayudu, R. K. (2016) "Evolutionary design of fuzzy logic controllers for medium access control in WBAN". In 2016 IEEE Congress on Evolutionary Computation, CEC 2016 (pp. 2821-2828). doi:10.1109/CEC.2016.7744145
Liang, Y., Zhang, M., & Browne, W. N. (2016) "Figure-ground image segmentation using genetic programming and feature selection". In 2016 IEEE Congress on Evolutionary Computation, CEC 2016 (pp. 3839-3846). doi:10.1109/CEC.2016.7744276
Koleejan, C., & Gao, X. (2016) "View-based text representation". In 2016 IEEE Congress on Evolutionary Computation, CEC 2016 (pp. 263-270). Vancouver, BC, Canada. doi:10.1109/CEC.2016.7743804
Iqbal, M., Zhang, M., & Xue, B. (2016) "Improving classification on images by extracting and transferring knowledge in genetic programming". In 2016 IEEE Congress on Evolutionary Computation, CEC 2016 (pp. 3582-3589). doi:10.1109/CEC.2016.7744243
Haslam, E., Xue, B., & Zhang, M. (2016) "Further investigation on genetic programming with transfer learning for symbolic regression". In 2016 IEEE Congress on Evolutionary Computation, CEC 2016 (pp. 3598-3605). doi:10.1109/CEC.2016.7744245
Cheng, X., Chen, G., & Zhang, M. (2016) "An XCS-based algorithm for multi-objective reinforcement learning". In 2016 IEEE Congress on Evolutionary Computation, CEC 2016 (pp. 4007-4014). Vancouver, BC, Canada. doi:10.1109/CEC.2016.7744298
Chen, Q., Xue, B., Niu, B., & Zhang, M. (2016) "Improving generalisation of genetic programming for high-dimensional symbolic regression with feature selection". In 2016 IEEE Congress on Evolutionary Computation, CEC 2016 (pp. 3793-3800). doi:10.1109/CEC.2016.7744270
Cagnoni, S., & Zhang, M. (2016) "Evolutionary computer vision and image processing: Some FAQs, current challenges and future perspectives". In 2016 IEEE Congress on Evolutionary Computation, CEC 2016 (pp. 1267-1271). doi:10.1109/CEC.2016.7743933
Burling-Claridge, F., Iqbal, M., & Zhang, M. (2016) "Evolutionary algorithms for classification of mammographie densities using local binary patterns and statistical features". In 2016 IEEE Congress on Evolutionary Computation, CEC 2016 (pp. 3847-3854). doi:10.1109/CEC.2016.7744277
Alvarez, I. M., Browne, W. N., & Zhang, M. (2016) "Compaction for code fragment based learning classifier systems - Redux". In 2016 IEEE Congress on Evolutionary Computation, CEC 2016 (pp. 2217-2224). doi:10.1109/CEC.2016.7744062
Niu, B., Zhang, F., Li, L., & Wu, L. (2016) "Particle Swarm Optimization for Yard Truck Scheduling in Container Terminal with a Cooperative Strategy". __. doi:10.1007/978-3-319-49049-6_24
Huang, Y., Ibrahim, A. M. M., Shi, X., Radwan, A. R., Zhai, W., Yang, K., & Xue, B. (2016) "Tribological Characterization of NiAl Self-Lubricating Composites Containing V2O5 Nanowires". Journal of Materials Engineering and Performance, 25(11), 4941-4951. doi:10.1007/s11665-016-2339-2
Xue, B., Zhu, Q., Shi, X., Zhai, W., Yang, K., & Huang, Y. (2016) "Microstructure and Functional Mechanism of Friction Layer in Ni3Al Matrix Composites with Graphene Nanoplatelets". Journal of Materials Engineering and Performance, 25(10), 4126-4133. doi:10.1007/s11665-016-2264-4
Xue, B., & Chen, G. (2016) "Guest editorial: special issue on evolutionary optimization, feature reduction and learning". Soft Computing, 20(10), 3771-3773. doi:10.1007/s00500-016-2285-9
Nguyen, H. B., Xue, B., Liu, I., Andreae, P., & Zhang, M. (2016) "New mechanism for archive maintenance in PSO-based multi-objective feature selection". Soft Computing, 20(10), 3927-3946. doi:10.1007/s00500-016-2128-8
da Silva, A. S., Ma, H., & Zhang, M. (2016) "Genetic programming for QoS-aware web service composition and selection". Soft Computing, 20(10), 3851-3867. doi:10.1007/s00500-016-2096-z
Tran, C. T., Zhang, M., Andreae, P., & Xue, B. (2016) "Improving performance for classification with incomplete data using wrapper-based feature selection". Evolutionary Intelligence, 9(3), 81-94. doi:10.1007/s12065-016-0141-6
Nguyen, H. B., Xue, B., & Andreae, P. (2016) "Mutual information for feature selection: estimation or counting?". Evolutionary Intelligence, 9(3), 95-110. doi:10.1007/s12065-016-0143-4
Cagnoni, S., & Zhang, M. (2016) "Foreword: special issue on evolutionary computer vision and pattern recognition". Evolutionary Intelligence, 9(3), 53-54. doi:10.1007/s12065-016-0142-5
Limtrairut, P., Marshall, S., & Andreae, P. (2016) "Mobile learning application for computer science students: A transactional distance perspective". In ICER 2016 - Proceedings of the 2016 ACM Conference on International Computing Education Research (pp. 285-286). doi:10.1145/2960310.2960350
Li, X., Liu, J., & Zhang, F. (2016) "Different effects of provider recommendations and consumer reviews on consumers' shopping efficiency for different product types". In 2016 13th International Conference on Service Systems and Service Management, ICSSSM 2016. doi:10.1109/ICSSSM.2016.7538521
Xue, B., Zhang, M., Browne, W. N., & Yao, X. (2016) "A Survey on Evolutionary Computation Approaches to Feature Selection". IEEE Transactions on Evolutionary Computation, 20(4), 606-626. doi:10.1109/TEVC.2015.2504420
Rahman, I., Hollitt, C., & Zhang, M. (2016) "Contextual-based top-down saliency feature weighting for target detection". Machine Vision and Applications, 27(6), 893-914. doi:10.1007/s00138-016-0754-x
Zhang, M., & Xue, B. (2016) "Evolutionary computation for feature selection and feature construction". In GECCO 2016 Companion - Proceedings of the 2016 Genetic and Evolutionary Computation Conference (pp. 861-881). doi:10.1145/2908961.2927002
Tran, C. T., Zhang, M., Andreae, P., & Xue, B. (2016) "Directly constructing multiple features for classification with missing data using genetic programming with interval functions". In GECCO 2016 Companion - Proceedings of the 2016 Genetic and Evolutionary Computation Conference (pp. 69-70). doi:10.1145/2908961.2909002
Sawczuk da Silva, A., Ma, H., & Zhang, M. (2016) "A graph-based QoS-aware method for web service composition with branching". In GECCO 2016 Companion - Proceedings of the 2016 Genetic and Evolutionary Computation Conference (pp. 131-132). doi:10.1145/2908961.2909044
Chen, Q., Xue, B., Shang, L., & Zhang, M. (2016) "Improving generalisation of genetic programming for symbolic regression with structural risk minimisation". In GECCO 2016 - Proceedings of the 2016 Genetic and Evolutionary Computation Conference (pp. 709-716). doi:10.1145/2908812.2908842
Alvarez, I. M., Browne, W. N., & Zhang, M. (2016) "Human-inspired scaling in learning classifier systems: Case study on the N-bit multiplexer problem set". In GECCO 2016 - Proceedings of the 2016 Genetic and Evolutionary Computation Conference (pp. 429-436). doi:10.1145/2908812.2908813
Zhang, F., Li, L., Liu, J., & Chu, X. (2016) "Artificial Bee Colony Optimization for Yard Truck Scheduling and Storage Allocation Problem". __. doi:10.1007/978-3-319-42294-7_81
Niu, B., Liu, J., Zhang, F., & Yi, W. (2016) "A Cooperative Structure-Redesigned-Based Bacterial Foraging Optimization with Guided and Stochastic Movements". __. doi:10.1007/978-3-319-42294-7_82
Ghifary, M., Kleijn, W. B., Zhang, M., Balduzzi, D., & Li, W. (2016) "Deep Reconstruction-Classification Networks for Unsupervised Domain Adaptation". __. doi:10.48550/arxiv.1607.03516
Tan, L., Wang, H., Zhang, F., & Feng, Y. (2016) "A Multiobjective Bacterial Optimization Method Based on Comprehensive Learning Strategy for Environmental/Economic Power Dispatch". __. doi:10.1007/978-3-319-41009-8_43
Koppen, M., & Xue, B. (2016) "Welcome message from program chairs". In Proceedings of the 2015 7th International Conference of Soft Computing and Pattern Recognition, SoCPaR 2015. doi:10.1109/SOCPAR.2015.7492832
Carnegie, D. A., Andreae, P., Watterson, C. A., & Bubendorfer, K. (2016) "The development of postgraduate ICT programmes: For an industry that does not want traditional postgraduate students". In IEEE Global Engineering Education Conference, EDUCON Vol. 10-13-April-2016 (pp. 702-708). doi:10.1109/EDUCON.2016.7474627
Gomes, H. M. (2016) "Student research abstract: Advances in network-based ensemble classifiers for evolving data streams". In Proceedings of the ACM Symposium on Applied Computing Vol. 04-08-April-2016 (pp. 958-959). doi:10.1145/2851613.2852021
Tran, B., Xue, B., & Zhang, M. (2016) "Genetic programming for feature construction and selection in classification on high-dimensional data". Memetic Computing, 8, 3-15.
Fu, W., Johnston, M., & Zhang, M. (2016) "Genetic programming for edge detection: a Gaussian-based approach". Soft Computing, 20(3), 1231-1248. doi:10.1007/s00500-014-1585-1
Yu, Y., Ma, H., & Zhang, M. (2016) "A genetic programming approach to distributed execution of data-intensive web service compositions". In ACM International Conference Proceeding Series Vol. 01-05-February-2016. doi:10.1145/2843043.2843046
Branke, J., Nguyen, S., Pickardt, C. W., & Zhang, M. (2016) "Automated Design of Production Scheduling Heuristics: A Review". IEEE Transactions on Evolutionary Computation, 20(1), 110-124. doi:10.1109/TEVC.2015.2429314
Barddal, J. P., Gomes, H. M., & Enembreck, F. (2016) "A survey on feature drift adaptation". In Proceedings - International Conference on Tools with Artificial Intelligence, ICTAI Vol. 2016-January (pp. 1053-1060). doi:10.1109/ICTAI.2015.150
Zhang, Mengjie., Ma, Hui., & Tan, Boxiong. (2016) "Optimization of Location Allocation of Web Services Using a Modified Non-dominated Sorting Genetic Algorithm". Switzerland: Springer International Publishing Switzerland. Retrieved from http://link.springer.com/chapter/10.
Zhang, Mengjie., Chen, Gang., & Karunakaran, Deepak. (2016) "Parallel Multi-objective Job Shop Scheduling Using Genetic Programming (Vol". 9592). Switzerland: Springer, Cham. Retrieved from http://link.springer.com/chapter/10.
Zhang, M. (2016) "Surrogate-assisted Genetic Programming with Simplified Models for Automated Design of Dispatching Rules". IEEE Transactions on Cybernetics. doi:10.1109/TCYB.2016.2562674
Yan, L., Mei, Y., Ma, H., & Zhang, M. (2016) "Evolutionary web service composition: A graph-based memetic algorithm". In Proceedings of the IEEE Congress on Evolutionary Computation (CEC) (pp. 201-208). IEEE. doi:10.1109/CEC.2016.7743796
Wang, J., Xue, B., Gao, X., & Zhang, M. (2016) "A differential evolution approach to feature selection and instance selection". In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 9810 LNCS (pp. 588-602). Phuket, THAILAND. doi:10.1007/978-3-319-42911-3_49
Tran, C. T., Zhang, M., & Andreae, P. (2016) "A Genetic Programming-Based Imputation Method for Classification with Missing Data". In M. Heywood, J. McDermott, M. Castelli, E. Costa, & K. Sim (Eds.), Genetic Programming. EuroGP 2016. Lecture Notes in Computer Science Vol. 9594 (pp. 149-163). Springer. doi:10.1007/978-3-319-30668-1_10
Tran, B. N., Zhang, M., & Xue, B. (2016) "A PSO Based Hybrid Feature Selection Algorithm For High-Dimensional Classification". In Proceedings of the 2016 IEEE Congress on Evolutionary Computation (CEC). Vancouver, BC, Canada: IEEE. doi:10.1109/CEC.2016.7744271
Tran, B., Zhang, M., & Xue, B. (2016) "Multiple feature construction in classification on high-dimensional data using GP". In IEEE Symposium Series on Computational Intelligence (SSCI) (pp. 1-8). Athens, Greece.
Tran, B., Xue, B., Zhang, M., & Nguyen, S. (2016) "Investigation on Particle Swarm Optimisation for Feature Selection on High-dimensional Data: Local Search and Selection Bias". Connection Science, 28(3), 270-294. doi:10.1080/09540091.2016.1185392
Tran, B., Xue, B., & Zhang, M. (2016) "Bare-Bone Particle Swarm Optimisation for Simultaneously Discretising and Selecting Features for High-Dimensional Classification". In Applications of Evolutionary Computation 19th European Conference, EvoApplications 2016 Porto, Portugal, March 30 – April 1, 2016 Proceedings, Part I (pp. 701-718). Springer. doi:10.1007/978-3-319-31204-0_45
Tran, B., Xue, B., & Zhang, M. (2016) "A PSO Based Hybrid Feature Selection Algorithm For High-Dimensional Classification". In Unknown Conference (pp. 3801-3808).
Tan, B., Mei, Y., Ma, H., & Zhang, M. (2016) "Particle Swarm Optimization for Multi-Objective Web Service Location Allocation". Evolutionary Computation in Combinatorial Optimization. EvoCOP 2016. Lecture Notes in Computer Science, 9595. Retrieved from http://homepages.ecs.vuw.ac.nz/~yimei/papers/EvoStar2016-boxiong.
Tan, B., Mei, Y., Ma, H., & Zhang, M. (2016) "Particle swarm optimization for multi-objective web service location allocation". In Proceedings of the European Conference on Evolutionary Computation in Combinatorial Optimization (EvoCOP) (pp. 219-234). Springer. doi:10.1007/978-3-319-30698-8_15
Tan, B., Ma, H., & Zhang, M. (2016) "Optimization of location allocation of web services using a modified non-dominated sorting genetic algorithm". In Artificial Life and Computational Intelligence Second Australasian Conference, ACALCI 2016 (pp. 246-257). Canberra: Springer. doi:10.1007/978-3-319-28270-1_21
Tan, B., Ma, H., & Zhang, M. (2016) "Optimization of Location Allocation of Web Services Using a Modified Non-dominated Sorting Genetic Algorithm". In T. Ray, R. Sarker, & X. Li (Eds.), Artificial Life and Computational Intelligence. Lecture Notes in Computer Science Vol. 9592. Springer.
Squillero, G., Burelli, P., Bacardit, J., Brabazon, A., Cagnoni, S., Cotta, C., . . . Zhang, M. (2016) "Applications of evolutionary computation: 19th European conference, Evoapplications 2016 Porto, Portugal, March 30 – April 1, 2016 proceedings, part II". In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 9598.
Squillero, G., Burelli, P., Bacardit, J., Brabazon, A., Cagnoni, S., Cotta, C., . . . Zhang, M. (2016) "Applications of evolutionary computation: 19th European conference, evoapplications 2016 Porto, Portugal, march 30 – april 1, 2016 proceedings, part I". In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 9597.
Squillero, G., Bacardit, J., Cagnoni, S., De Falco, I., Divina, F., Esparcia-Alcázar, A. I., . . . Zhang, M. (2016) "Preface (Vol". 9597).
Sabar, N. R., Song, A., & Zhang, M. (2016) "A variable local search based memetic algorithm for the load balancing problem in cloud computing". In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 9597 (pp. 267-282). doi:10.1007/978-3-319-31204-0_18
Riley, M., Mei, Y., & Zhang, M. (2016) "Improving job shop dispatching rules via terminal weighting and adaptive mutation in genetic programming". In Proceedings of the IEEE Congress on Evolutionary Computation (CEC) (pp. 3362-3369). IEEE. doi:10.1109/CEC.2016.7744215
Poaka, V., Hartmann, S., Ma, H., & Steinmetz, D. (2016) "A link-density-based algorithm for finding communities in social networks". In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 9975 LNCS (pp. 76-85). doi:10.1007/978-3-319-47717-6_7
Peng, Y., Chen, G., Zhang, M., & Pang, S. (2016) "Generalized compatible function approximation for policy gradient search". In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 9947 LNCS (pp. 615-622). Kyoto, Japan. doi:10.1007/978-3-319-46687-3_68
Park, J., Mei, Y., Nguyen, S., Chen, G., Johnston, M., & Zhang, M. (2016) "Genetic programming based hyper-heuristics for dynamic job shop scheduling: cooperative coevolutionary approaches". In Proceedings of the European Conference on Genetic Programming (EuroGP) (pp. 115-132). Springer. doi:10.1007/978-3-319-30668-1_8
Park, J., Mei, Y., Chen, G., & Zhang, M. (2016) "Niching genetic programming based hyper-heuristic approach to dynamic job shop scheduling: an investigation into distance metrics". In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO) (pp. 109-110). ACM. doi:10.1145/2908961.2908985
Nguyen, S., Mei, Y., & Zhang, M. (2016) "Special Issue on Automated Design and Adaptation of Heuristics for Scheduling and Combinatorial Optimisation". Genetic Programming and Evolvable Machines.
Nguyen, S., Mei, Y., Ma, H., Chen, A., & Zhang, M. (2016) "Evolutionary scheduling and combinatorial optimisation: Applications, challenges, and future directions". In Proceedings of the IEEE Congress on Evolutionary Computation (CEC) (pp. 3053-3060). IEEE. doi:10.1109/CEC.2016.7744175
Nguyen, H. B., Xue, B., & Zhang, M. (2016) "A subset similarity guided method for multi-objective feature selection". In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 9592 (pp. 298-310). doi:10.1007/978-3-319-28270-1_25
Nguyen, H. B., Xue, B., & Andreae, P. (2016) "Mutual information estimation for filter based feature selection using particle swarm optimization". In Lecture Notes in Computer Science : Applications of Evolutionary Computation 19th European Conference, EvoApplications 2016 Vol. 9597 (pp. 719-736). doi:10.1007/978-3-319-31204-0_46
Mirghasemi, S., Rayudu, R., & Zhang, M. (2016) "A new modification of fuzzy C-means via particle swarm optimization for noisy image segmentation". In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 9592 (pp. 147-159). doi:10.1007/978-3-319-28270-1_13
Mei, Y., Zhang, M., & Nyugen, S. (2016) "Feature selection in evolving job shop dispatching rules with genetic programming". In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO) (pp. 365-372). ACM. doi:10.1145/2908812.2908822
Mei, Y., & Zhang, M. (2016) "A comprehensive analysis on reusability of GP-evolved job shop dispatching rules". In Proceedings of the IEEE Congress on Evolutionary Computation (CEC) (pp. 3590-3597). IEEE. doi:10.1109/CEC.2016.7744244
Mei, Y., Xue, B., & Zhang, M. (2016) "Fast bi-objective feature selection using entropy measures and bayesian inference". In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO) (pp. 469-476). ACM. doi:10.1145/2908812.2908823
Mei, Y., Salim, F. D., & Li, X. (2016) "Efficient meta-heuristics for the multi-objective time-dependent orienteering problem". European Journal of Operational Research, 254, 443-457. doi:10.1016/j.ejor.2016.03.053
Mei, Y., Omidvar, M. N., Li, X., & Yao, X. (2016) "A competitive divide-and-conquer algorithm for unconstrained large-scale black-box optimization". ACM Transactions on Mathematical Software (TOMS), 42, 13:1-13:24.
Mei, Y., Omidvar, M. N., Li, X., & Yao, X. (2016) "A competitive divide-and-conquer algorithm for unconstrained large-scale black-box optimization". ACM Transactions on Mathematical Software, 42, 13:1-24. doi:10.1145/2791291
Mei, Y., Li, X., & Yao, X. (2016) "On investigation of interdependence between sub-problems of the travelling thief problem". Soft Computing, 20, 157-172. doi:10.1007/s00500-014-1487-2
Masood, A., Mei, Y., Chen, G., & Zhang, M. (2016) "Many-objective genetic programming for job-shop scheduling". In Proceedings of the IEEE Congress on Evolutionary Computation (CEC) (pp. 209-216). IEEE. doi:10.1109/CEC.2016.7743797
Ma, J., Xue, B., & Zhang, M. (2016) "A profile-based authorship attribution approach to forensic identification in Chinese online messages". In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 9650 (pp. 33-52). doi:10.1007/978-3-319-31863-9_3
Liu, J., Mei, Y., & Li, X. (2016) "An Analysis of the Inertia Weight Parameter for Binary Particle Swarm Optimization". IEEE Transactions on Evolutionary Computation, 20, 666-681. doi:10.1109/TEVC.2015.2503422
Limtrairut, P., Marshall, S., & Andreae, P. (2016) "Know the mobile learning application users: Transactional distance perspective". In CSEDU 2016 - Proceedings of the 8th International Conference on Computer Supported Education Vol. 2 (pp. 378-387). doi:10.5220/0005791303780387
Liang, Y., Zhang, M., & Browne, W. N. (2016) "Multi-objective genetic programming for figure-ground image segmentation". In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 9592 (pp. 134-146). doi:10.1007/978-3-319-28270-1_12
Li, L., Zhang, F. F., Chu, X., & Niu, B. (2016) "Modified brain storm optimization algorithms based on topology structures". In Unknown Conference Vol. 9713 LNCS (pp. 408-415). doi:10.1007/978-3-319-41009-8_44
Lensen, A., Al-Sahaf, H., Zhang, M., & Xue, B. (2016) "Genetic Programming for Region Detection, Feature Extraction, Feature Construction and Classification in Image Data". In Proceedings of the 19th European Conference on Genetic Programming (EuroGP 2016) (Vol. 9594, pp. 51-67). Springer. doi:10.1007/978-3-319-30668-1_4
Kumar, S., Gao, X., Welch, I., & Mansoori, M. (2016) "A machine learning based web spam filtering approach". In 2016 IEEE 30th International Conference on Advanced Information Networking and Applications (AINA) (pp. 973-980). IEEE.
Kumar, S., Gao, X., & Welch, I. (2016) "RETRACTED CHAPTER: Co-clustering for Dual Topic Models". In Australasian Joint Conference on Artificial Intelligence (pp. 390-402). Springer, Cham.
Kumar, S., Gao, X., & Welch, I. (2016) "Novel features for web spam detection". In 2016 IEEE 28th International Conference on Tools with Artificial Intelligence (ICTAI) (pp. 593-597). IEEE.
Kumar, S., Gao, X., & Welch, I. (2016) "Learning under data shift for domain adaptation: A model-based co-clustering transfer learning solution". In Pacific Rim Knowledge Acquisition Workshop (pp. 43-54). Springer, Cham.
Karunakaran, D., Chen, G., & Zhang, M. (2016) "Parallel multi-objective job shop scheduling using genetic programming". In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 9592 (pp. 234-245). doi:10.1007/978-3-319-28270-1_20
Iqbal, M., Xue, B., & Zhang, M. (2016) "Reusing extracted knowledge in genetic programming to solve complex texture image classification problems". In J. Baily, L. Khan, T. Washio, G. Dobbie, J. Z. Huang, & R. Wang (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 9652 LNAI (pp. 117-129). Auckland: Springer. doi:10.1007/978-3-319-31750-2_10
Hartmann, S., & Ma, H. (2016) "Preface". In Unknown Book (Vol. 9827 LNCS, pp. V-VI). doi:10.1007/978-3-319-44403-1
Ghifary, M., Kleijn, W. B., Zhang, M., Balduzzi, D., & Li, W. (2016) "Deep reconstruction-classification networks for unsupervised domain adaptation". In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9908 LNCS, pp. 597-613). doi:10.1007/978-3-319-46493-0_36
Ghifary, M., Balduzzi, D., Kleijn, B., & Zhang, M. (2016) "Scatter Component Analysis: A Unified Framework for Domain Adaptation and Domain Generalization". IEEE Transactions on Pattern Analysis and Machine Intelligence, 15 pages. doi:10.1109/TPAMI.2016.2599532
da Silva, A. S., Mei, Y., Ma, H., & Zhang, M. (2016) "Particle swarm optimisation with sequence-like indirect representation for web service composition". In Proceedings of the European Conference on Evolutionary Computation in Combinatorial Optimization (EvoCOP) (pp. 202-218). Springer. doi:10.1007/978-3-319-30698-8_14
da Silva, A. S., Mei, Y., Ma, H., & Zhang, M. (2016) "A memetic algorithm-based indirect approach to web service composition". In Proceedings of the IEEE Congress on Evolutionary Computation (CEC). doi:10.1109/CEC.2016.7744218
Crabtree, D., Gao, X., & Andreae, P. (2016) "Query aspects approach to web search". Web Intelligence, 14(3), 173-197. doi:10.3233/WEB-160338
Consoli, P. A., Mei, Y., Minku, L. L., & Yao, X. (2016) "Dynamic selection of evolutionary operators based on online learning and fitness landscape analysis". Soft Computing, 20, 3889-3914. doi:10.1007/s00500-016-2126-x
Barddal, J. P., Gomes, H. M., Granatyr, J., De Souza Britto, A., & Enembreck, F. (2016) "Overcoming feature drifts via dynamic feature weighted k-nearest neighbor learning". In Proceedings - International Conference on Pattern Recognition Vol. 0 (pp. 2186-2191). doi:10.1109/ICPR.2016.7899960
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