Publications 2014 - Groups/ECRG | Te Kura Mātai Pūkaha, Pūrorohiko / School of Engineering and Computer Science | Te Herenga Waka

Bhowan, U., Johnston, M., Zhang, M., & Yao, X. (2014) "Reusing Genetic Programming for Ensemble Selection in Classification of Unbalanced Data". IEEE Transactions on Evolutionary Computation, 18(6), 893-908. doi:10.1109/TEVC.2013.2293393
Ghifary, M., Kleijn, W. B., & Zhang, M. (2014) "Domain Adaptive Neural Networks for Object Recognition". __. doi:10.48550/arxiv.1409.6041
Fu, W., Johnston, M., & Zhang, M. (2014) "Distribution-based invariant feature construction using genetic programming for edge detection". Soft Computing. doi:10.1007/s00500-014-1432-4
Iqbal, M., Browne, W., & Zhang, M. (2014) "Reusing Building Blocks of Extracted Knowledge to Solve Complex, Large-Scale Boolean Problems". IEEE Transactions on Evolutionary Computation, 18(4), 465-480. doi:10.1109/TEVC.2013.2281537
Fu, W., Johnston, M., & Zhang, M. (2014) "Low-Level Feature Extraction for Edge Detection Using Genetic Programming". IEEE Transactions on Cybernetics, 44(8), 1459-1472. doi:10.1109/TCYB.2013.2286611
Bell, T., Andreae, P., & Robins, A. (2014) "A Case Study of the Introduction of Computer Science in NZ Schools". ACM Transactions on Computing Education, 14(2), 31 pages. doi:10.1145/2602485
Nguyen, S., Zhang, M., Johnston, M., & Chen Tan, K. (2014) "Automatic Design of Scheduling Policies for Dynamic Multi-objective Job Shop Scheduling via Cooperative Coevolution Genetic Programming". IEEE Transactions on Evolutionary Computation, 18(2), 193-208. doi:10.1109/TEVC.2013.2248159
Yu, Y., Ma, H., & Zhang, M. (2014) "A Hybrid GP-Tabu Approach to QoS-aware Data Intensive Web Service Composition". In Proceedings of the 10th International Conference on Simulated Evolution and Learning (SEAL 2014) (pp. 106-118). Dunedin: Springer.
Yu, Y., Ma, H., & Zhang, M. (2014) "A Genetic Programming Approach to Distributed QoS-aware Web Service Composition". In Proceedings of 2014 IEEE Congress on Evolutionary Computation (pp. 1840-1846). Beijing, China: IEEE Press.
Xue, B., Zhang, M., & Browne, W. (2014) "Particle Swarm Optimisation for Feature Selection in Classification: Novel Initialisation and Updating Mechanisms". Applied Soft Computing, 18, 261-276. doi:10.1016/j.asoc.2013.09.018
Xue, B., Xu, Z., Zhang, Q., Shi, X., Wang, M., Zhai, W., . . . Song, S. (2014) "Tribological properties of TiAl-Ti3SiC2 composites". Journal Wuhan University of Technology, Materials Science Edition, 29(2), 256-263. doi:10.1007/s11595-014-0904-9
Xue, B., Tong, B., & Jia, Q. (2014) "The influence of different thermo-mechanical histories on the crystalline morphology of PET Fiber/iPP composites". In Proceedings - 2014 6th International Conference on Measuring Technology and Mechatronics Automation, ICMTMA 2014 (pp. 708-711). doi:10.1109/ICMTMA.2014.175
Xue, B., Qin, A., & Zhang, M. (2014) "An Archive based Particle Swarm Optimisation for Feature Selection in Classification". In Proceedings of 2014 IEEE Congress on Evolutionary Computation (pp. 3119-3126). Beijing: IEEE Press.
Xue, B., Nguyen, S., & Zhang, M. (2014) "A New Binary Particle Swarm Optimisation Algorithm for Feature Selection". In Proceedings of the 16th European Conference on the Applications of Evolutionary Computation (EvoApplications 2014) (pp. 501-513). Berlin: Springer.
Xue, B., Fu, W., & Zhang, M. (2014) "Multi-Objective Feature Selection in Classification: A Differential Evolution Approach". In Proceedings of the 10th International Conference on Simulated Evolution and Learning (SEAL 2014) (pp. 516-528). Berlin: Springer.
Xue, B., Fu, W., & Zhang, M. (2014) "Differential evolution (DE) for Multi-objective Feature Selection in Classification". In Proceedings of 2014 Genetic and Evolutionary Computation Conference (GECCO 2014 Companion) (pp. 83-84). Vancouver, Canada: ACM Press.
Xue, B., Cervante, L., Shang, L., Browne, W., & Zhang, M. (2014) "Binary PSO and rough set theory for feature selection: a multi-objective filter based approach". International Journal of Computational Intelligence and Applications, 13(2), 1450009-1-1450009-34. doi:10.1142/S1469026814500096
Xie, J., Mei, Y., Ernst, A. T., Li, X., & Song, A. (2014) "Scaling up solutions to storage location assignment problems by genetic programming". In Proceedings of the Asia-Pacific Conference on Simulated Evolution and Learning (SEAL) (pp. 691-702). Springer. doi:10.1007/978-3-319-13563-2_58
Xie, J., Mei, Y., Ernst, A. T., Li, X., & Song, A. (2014) "A genetic programming-based hyper-heuristic approach for storage location assignment problem". In Proceedings of the IEEE Congress on Evolutionary Computation (CEC) (pp. 3000-3007). IEEE. doi:10.1109/CEC.2014.6900604
Wahid, A., Gao, X., & Andreae, P. (2014) "Multi-view clustering of web documents using multi-objective genetic algorithm". In 2014 IEEE Congress on Evolutionary Computation (CEC 2014) (pp. 2625-2632). Beijing, China: IEEE. doi:10.1109/CEC.2014.6900586
Tran, B., Xue, B., & Zhang, M. (2014) "Overview of Particle Swarm Optimisation for Feature Selection in Classification". In Proceedings of the 10th International Conference on Simulated Evolution and Learning (SEAL), Dunedin, New Zealand (pp. 605-617). Springer International Publishing. doi:10.1007/978-3-319-13563-2_51
Tran, B., Xue, B., & Zhang, M. (2014) "Improved PSO for Feature Selection on High-Dimensional Datasets". In Proceedings of the 10th International Conference on Simulated Evolution and Learning (SEAL), Dunedin, New Zealand (pp. 503-515). Springer International Publishing. doi:10.1007/978-3-319-13563-2_43
Tirumala, S. S., Pang, S., & Chen, G. (2014) "Quantum inspired evolutionary algorithm by representing candidate solution as normal distribution". In C. K. Loo, K. S. Yap, K. W. Wong, A. Teoh, & K. Huang (Eds.), Neural Information Processing 21st International Conference, ICONIP 2014 Kuching, Malaysia, November 3–6, 2014 Proceedings, Part III Vol. 8836 (pp. 308-316). Berlin: Springer. doi:10.1007/978-3-319-12643-2_38
Tirumala, S. S., Chen, G., & Pang, S. (2014) "Quantum Inspired Evolutionary Algorithm by Representing Candidate Solution as Normal Distribution". In C. K. Loo, K. S. Yap, K. W. Wong, A. Teoh, & K. Huang (Eds.), NEURAL INFORMATION PROCESSING, ICONIP 2014, PT III Vol. 8836 (pp. 308-316). Kuching, MALAYSIA: SPRINGER-VERLAG BERLIN. Retrieved from http://gateway.webofknowledge.
Sawczuk da Silva, A., Ma, H., & Zhang, M. (2014) "A Graph-Based Particle Swarm Optimisation Approach to QoS-Aware Web Service Composition and Selection". In Proceedings of 2014 IEEE Congress on Evolutionary Computation (pp. 3127-3134). Beijing, China: IEEE Press.
Sawczuk da Silva, A., Ma, H., & Zhang, M. (2014) "A GP Approach to QoS-Aware Web Service Composition and Selection". In Simulated Evolution and Learning 10th International Conference, SEAL 2014 Dunedin, New Zealand, December 15-18, 2014 Proceedings (pp. 180-191). Dunedin: Springer.
Sawczuk da Silva, A., Gao, X., & Andreae, P. (2014) "Wallace: Incorporating Search into Chatting". In Proceedings of 13th Pacific Rim International Conference on Artificial Intelligence, PRICAI 2014, Gold Coast, QLD, Australia, 2014, Trends in Artificial Intelligence (pp. 842-848).
Rahman, I., Hollitt, C., & Zhang, M. (2014) "Information Divergence Based Saliency Detection with a Global Center-Surround Mechanism". In Proceedings of 22nd International Conference on Pattern Recognition (ICPR 2014) (pp. 3428-3433). Stockholm: IEEE Press. doi:10.1109/ICPR.2014.590
Rada-Vilela, J., Johnston, M., & Zhang, M. (2014) "Deception, blindness and disorientation in particle swarm optimization applied to noisy problems". Swarm Intelligence, 8, 247-273.
Rada-Velila, J., Johnston, M., & Zhang, M. (2014) "Population Statistics for Particle Swarm Optimization: Resampling Methods in Noisy Optimization Problems". Swarm and Evolutionary Computation, 17, 37-59. doi:10.1016/j.swevo.2014.02.004
Park, J., Nguyen, S., Zhang, M., & Johnston, M. (2014) "Enhancing Heuristics for Order Acceptance and Scheduling using Genetic Programming". In Proceedings of the 10th International Conference on Simulated Evolution and Learning (SEAL 2014) (pp. 723-734). Berlin: Springer.
Omidvar, M. N., Mei, Y., & Li, X. (2014) "Optimal Decomposition of Large-Scale Separable Continuous Functions for Cooperative Co-evolutionary Algorithms". In Proceedings of the 2014 IEEE Congress on Evolutionary Computation (CEC2014) (pp. 1305-1312). IEEE.
Omidvar, M. N., Mei, Y., & Li, X. (2014) "Effective decomposition of large-scale separable continuous functions for cooperative co-evolutionary algorithms". In Proceedings of the IEEE Congress on Evolutionary Computation (CEC) (pp. 1305-1312). IEEE. doi:10.1109/CEC.2014.6900420
Omidvar, M. N., Li, X., Mei, Y., & Yao, X. (2014) "Cooperative co-evolution with differential grouping for large scale optimization". IEEE Transactions on Evolutionary Computation, 18, 378-393. doi:10.1109/TEVC.2013.2281543
Nguyen, S., Zhang, M., Johnston, M., & Tan, K. (2014) "Selection Schemes in Surrogate-assisted Genetic Programming for Job Shop Scheduling". In Proceedings of the 10th International Conference on Simulated Evolution and Learning (SEAL 2014) (pp. 656-667). Berlin: Springer.
Nguyen, S., Zhang, M., Johnston, M., & Tan, K. (2014) "Genetic Programming for Evolving Due-Date Assignment Models in Job Shop Environments". Evolutionary Computation, 22(1), 105-138. doi:10.1162/EVCO_a_00105
Nguyen, S., Zhang, M., Johnston, M., & Tan, K. (2014) "Automatic Programming via Iterated Local Search for Dynamic Job Shop Scheduling". IEEE Transactions on Cybernetics. doi:10.1109/TCYB.2014.2317488
Nguyen, S., Zhang, M., Johnston, M., & Tan, K. (2014) "Automatic Design of Scheduling Policies for Dynamic Multi-objective Job Shop Scheduling via Cooperative Coevolution Genetic Programming". IEEE Transactions on Evolutionary Computation, 18, 193-208. doi:10.1109/TEVC.2013.2248159
Nguyen, S., Zhang, M., & Johnston, M. (2014) "Enhancing Branch-and-Bound Algorithms for Order Acceptance and Scheduling with Genetic Programming". In Proceedings of the 17th European Conference on Genetic Programming (EuroGP 2014) (pp. 124-136). Berlin: Springer.
Nguyen, S., Zhang, M., & Johnston, M. (2014) "A Sequential Genetic Programming Method to Learn Forward Construction Heuristics for Order Acceptance and Scheduling". In Proceedings of 2014 IEEE Congress on Evolutionary Computation (pp. 1824-1831). Beijing, China: IEEE Press.
Nguyen, H., Xue, B., Liu, I., & Zhang, M. (2014) "PSO and Statistical Clustering for Feature Selection: A New Representation". In Proceedings of the 10th International Conference on Simulated Evolution and Learning (SEAL 2014) (pp. 569-581). Berlin: Springer.
Nguyen, H., Xue, B., Liu, I., & Zhang, M. (2014) "PSO and Statistical Clustering for Feature Selection: A New Representation". In Simulated Evolution and Learning (pp. 569-581).
Nguyen, H., Xue, B., Liu, I., & Zhang, M. (2014) "Filter Based Backward Elimination in Wrapper Based PSO for Feature Selection in Classification". In Evolutionary Computation (CEC), 2014 IEEE Congress on (pp. 3111-3118).
Nguyen, H., Xue, B., Liu, I., & Zhang, M. (2014) "Filter based Backward Elimination in Wrapper based PSO for Feature Selection in Classification". In Proceedings of 2014 IEEE Congress on Evolutionary Computation (pp. 3111-3118). Beijing: IEEE Press.
Mei, Y., Li, X., & Yao, X. (2014) "Variable neighborhood decomposition for large scale capacitated arc routing problem". In Evolutionary Computation (CEC), 2014 IEEE Congress on (pp. 1313-1320). IEEE.
Mei, Y., Li, X., & Yao, X. (2014) "Variable neighborhood decomposition for large scale capacitated arc routing problem". In Proceedings of the IEEE Congress on Evolutionary Computation (CEC) (pp. 1313-1320). IEEE. doi:10.1109/CEC.2014.6900305
Mei, Y., Li, X., & Yao, X. (2014) "Improving efficiency of heuristics for the large scale traveling thief problem". In Asia-Pacific Conference on Simulated Evolution and Learning (pp. 631-643). Springer.
Mei, Y., Li, X., & Yao, X. (2014) "Improving efficiency of heuristics for the large scale traveling thief problem". In Unknown Book (pp. 631-643). doi:10.1007/978-3-319-13563-2_53
Mei, Y., Li, X., & Yao, X. (2014) "Cooperative coevolution with route distance grouping for large-scale capacitated arc routing problems". IEEE Transactions on Evolutionary Computation, 18, 435-449. doi:10.1109/TEVC.2013.2281503
McLeod, P., Verma, B., & Zhang, M. (2014) "Optimizing configuration of neural ensemble network for breast cancer diagnosis". In Proceedgins of the 2014 International Joint Conference on Neural Networks (IJCNN 2014) (pp. 1087-1092). Beijing: IEEE.
Marzukhi, S., Browne, W., & Zhang, M. (2014) "Three-Cornered Coevolution Learning Classifier Systems for Classification Tasks". In Proceedings of 2014 Genetic and Evolutionary Computation Conference (GECCO 2014) (pp. 549-556). Vancouver, Canada: ACM Press.
Marzukhi, S. (2014) "Three-cornered coevolution learning classifier systems for classification". (PhD Thesis).
Marshall, R., Johnston, M., & Zhang, M. (2014) "Hyper-Heuristics, Grammatical Evolution and the Capacitated Vehicle Routing Problem". In Proceedings of 2014 Genetic and Evolutionary Computation Conference (GECCO 2014 Companion) (pp. 71-72). Vancouver, Canada: ACM Press.
Marshall, R., Johnston, M., & Zhang, M. (2014) "Developing a Hyper-heuristic using Grammatical Evolution and the Capacitated Vehicle Routing Problem". In Proceedings of the 10th International Conference on Simulated Evolution and Learning (SEAL 2014) (pp. 668-679). Berlin: Springer.
Marshall, R., Johnston, M., & Zhang, M. (2014) "A Comparison between Two Evolutionary Hyper-heuristics for Combinatorial Optimisation". In Proceedings of the 10th International Conference on Simulated Evolution and Learning (SEAL 2014) (pp. 618-630). Berlin: Springer.
Ma, H., & Schewe, K. D. (2014) "Query handling in geometric conceptual modelling". In T. Tokuda, Y. Kiyoki, H. Jaakkola, & N. Yoshida (Eds.), Information Modelling and Knowledge Bases XXV (Vol. 260, pp. 174-189). IOP. doi:10.3233/978-1-61499-361-2-174
Liang, Y., Zhang, M., & Browne, W. (2014) "Image Segmentation: A Survey of Methods based on Evolutionary Computation". In Proceedings of the 10th International Conference on Simulated Evolution and Learning (SEAL 2014) (pp. 847-859). Berlln: Springer.
Lewis, J. P., Anjyo, K., Rhee, T., Zhang, M., Pighin, F., & Deng, Z. (2014) "Practice and Theory of Blendshape Facial Models". In State of the Art Reports (pp. 20 pages). Strasbourg/France. doi:10.2312/egst.20141042
Lewis, J., Anjyo, K., Rhee, T., Zhang, M., Pighin, F., & Deng, Z. (2014) "Practice and Theory of Blendshape Facial Models". In S. Lefebvre, & M. Spagnuolo (Eds.), Eurographics 2014 - State of the Art Reports (pp. 119-218). Strasbourg, France: The Eurographics Association. doi:10.2312/egst.20141042
Lewis, J., Anjyo, K., Rhee, T., Zhang, M., Pighin, F., & Deng, Z. (2014) "Practice and Theory of Blendshape Facial Models". In S. Lefebvre, & M. Spagnuolo (Eds.), Eurographics 2014 - State of the Art Reports. Strasbourg, France: The Eurographics Association. doi:10.2312/egst.20141042
Lane, M., Xue, B., Liu, I., & Zhang, M. (2014) "Gaussian Based Particle Swarm Optimisation and Statistical Clustering for Feature Selection". In Evolutionary Computation in Combinatorial Optimisation (pp. 133-144). Springer Berlin Heidelberg.
Lane, M., Xue, B., Liu, I., & Zhang, M. (2014) "Gaussian Based Particle Swarm Optimisation and Statistical Clustering for Feature Selection". In Proceedings of the 14th European Conference on Evolutionary Computation in Combinatorial Optimisation (EvoCOP2014) (pp. 133-144). Berlin: Springer.
Jabeen, S., Gao, X., & Andreae, P. (2014) "Using Asymmetric Associations for Commonsense Causality Detection". In Lecture Notes in Computer Science (pp. 877-883). Springer International Publishing. doi:10.1007/978-3-319-13560-1_73
Jabeen, S., Gao, X., & Andreae, P. (2014) "Using Asymmetric Associations for Commonsense Causality Detection". In PRICAI 2014.
Jabeen, S., Gao, X., & Andreae, P. (2014) "Probabilistic Associations as a Proxy for Semantic Relatedness". Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 8786, 512-522. doi:10.1007/978-3-319-11749-2_38
Jabeen, S., Gao, X., & Andreae, P. (2014) "Probabilistic Associations as a Proxy for Semantic Relatedness". In WISE 2014 Vol. 8786 (pp. 512-522). the proceedings of the 15th International Conference on Web Information Systems Engineering: Springer. doi:10.1007/978-3-319-11746-1
Jabeen, S., Gao, X., & Andreae, P. (2014) "A Hybrid Model for Learning Semantic Relatedness Using Wikipedia-Based Features". In B. Benatallah, A. Bestavros, Y. Manolopoulos, A. Vakali, & Y. Zhang (Eds.), Web Information Systems Engineering – WISE 2014 15th International Conference Thessaloniki, Greece, October 12-14, 2014 Proceedings, Part I Vol. 8786 (pp. 523-533). Cham Heidelberg New York Dordrecht London. doi:10.1007/978-3-319-11749-2_39
Iqbal, M., Naqvi, S., Browne, W., Hollitt, C., & Zhang, M. (2014) "Salient Object Detection Using Learning Classifier Systems that Compute Action Mappings". In C. Igel (Ed.), GECCO’14, Proceedings of the 2014 Genetic and Evolutionary Computation Conference (pp. 525-532). New York, NY: The Association for Computing Machinery, Inc. (ACM). Retrieved from https://dl.acm.org/citation.
Hunt, R., Johnston, M., & Zhang, M. (2014) "Evolving Machine-Specific Dispatching Rules for a Two-Machine Job Shop using Genetic Programming". In Proceedings of 2014 IEEE Congress on Evolutionary Computation (pp. 618-625). Beijing: IEEE Press.
Hunt, R., Johnston, M., & Zhang, M. (2014) "Evolving 'Less-Myopic' Scheduling Rules for Dynamic Job Shop Scheduling with Genetic Programming". In Proceedings of 2014 Genetic and Evolutionary Computation Conference (GECCO 2014) (pp. 927-934). Vancouver, Canada: ACM Press.
Huang, H., Ma, H., & Zhang, M. (2014) "An enhanced genetic algorithm for web service location-allocation". In Database and Expert Systems Applications 25th International Conference, DEXA 2014 (pp. 223-230). Munich, Germany: Springer. doi:10.1007/978-3-319-10085-2_20
Huang, H., Ma, H., & Zhang, M. (2014) "An enhanced genetic algorithm for web service location-allocation". In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 8645 LNCS (pp. 223-230). doi:10.1007/978-3-319-10085-2_20
Hoda, R., & Andreae, P. (2014) "It's Not Them, It's Us! Why Computer Science Fails to Impress Many First Years". In Proceedings of the Sixteenth Australasian Computing Education Conference (ACE2014) (pp. 159-162).
Gomes, H. M., & Enembreck, F. (2014) "SAE2: Advances on the social adaptive ensemble classifier for data streams". In Proceedings of the ACM Symposium on Applied Computing (pp. 798-804). doi:10.1145/2554850.2554905
Ghifary, M., Kleijn, W. B., & Zhang, M. (2014) "Domain Adaptive Neural Networks for Object Recognition". Unknown Journal, 898-904. doi:10.1007/978-3-319-13560-1_76
Ghifary, M., Kleijn, W., & Zhang, M. (2014) "Domain Adaptive Neural Networks for Object Recognition". In Proceedings of the 13th Pacific Rim International Conference on Artificial Intelligence (PRICAI 2014) (pp. 898-904). Berlin: Springer.
Ghifary, M., Kleijn, W., & Zhang, M. (2014) "Deep Hybrid Networks with good out-of-sample object recognition". In 2014 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2014) (pp. 5437-5441). Florence, Italy: IEEE Press.
Fu, W., Johnston, M., & Zhang, M. (2014) "Unsupervised Learning for Edge Detection using Genetic Programming". In Proceedings of 2014 IEEE Congress on Evolutionary Computation (pp. 117-124). Beijing: IEEE Press.
Fu, W., Johnston, M., & Zhang, M. (2014) "Is a Single Image Sufficient for Evolving Edge Features by Genetic Programming?". In Proceedings of the 16th European Conference on the Applications of Evolutionary Computation (EvoApplications 2014), Lecture Notes in Computer Science. Granada, Spain. April 23-25, 2014.
Fu, W., Johnston, M., & Zhang, M. (2014) "Automatic Resolution Selection for Edge Detection using Genetic Programming". In Proceedings of the 10th International Conference on Simulated Evolution and Learning (SEAL 2014) (pp. 810-821). Berlin: Springer.
Esparcia-Alcázar, A. I., Mora, A. M., Agapitos, A., Burelli, P., Bush, W. S., Cagnoni, S., . . . Zincir-Heywood, N. (2014) "Preface (Vol". 8602). doi:10.1007/978-3-662-45523-4
Esparcia-Alcazar, A., Mora, A., Burelli, P., Bush, W., et al., Zhang, M., & Zincir-Heywood, N. (2014) "EvoApplications 2014: Proceedings of the 17th European Conference on Applications of Evolutionary Computation". Berlin: Springer.
Ebadi, T., Kukenys, I., Browne, W., & Zhang, M. (2014) "Human-Interpretable Feature Pattern Classification System Using Learning Classifier Systems". Evolutionary Computation, 22(4), 629-650. doi:10.1162/EVCO_a_00127
Dick, G., Browne, W., Whigham, P., Zhang, M., Bui, L., Ishibuchi, H., . . . Tang, K. (2014) "Simulated Evolution and Learning - 10th International Conference (SEAL 2014)". Berlin: Springer.
Dick, G., Browne, W., Whigham, P., & Zhang, M. (2014) "Preface (Vol". 8886 LNCS).
Dai, Y., Xue, B., & Zhang, M. (2014) "New Representations in PSO for Feature Construction in Classification". In Proceedings of the 16th European Conference on the Applications of Evolutionary Computation (EvoApplications 2014) (pp. 476-488). Berlin: Springer.
da Silva, A. S., Gao, X., & Andreae, P. (2014) "Wallace: Incorporating Search into Chatting". In Lecture Notes in Computer Science (pp. 842-848). Springer International Publishing. doi:10.1007/978-3-319-13560-1_68
Chen, G., Zhang, M., Pang, S., & Douch, C. (2014) "Stochastic Decision Making in Learning Classifier Systems through a Natural Policy Gradient Method". In C. K. Loo, K. S. Yap, K. W. Wong, A. Teoh, & K. Huang (Eds.), Neural Information Processing 21st International Conference, ICONIP 2014 Kuching, Malaysia, November 3–6, 2014 Proceedings, Part III Vol. 8836 (pp. 300-307). Berlin: Springer. doi:10.1007/978-3-319-12643-2_37
Bennett, S., Nguyen, S., & Zhang, M. (2014) "A Hybrid Discrete Particle Swarm Optimisation Method for Grid Computation Scheduling". In Proceedings of 2014 IEEE Congress on Evolutionary Computation (pp. 483-490). Beijing: IEEE Press.
Barddal, J. P., Gomes, H. M., & Enembreck, F. (2014) "SFNClassifier: A scale-free social network method to handle concept drift". In Proceedings of the ACM Symposium on Applied Computing (pp. 786-791). doi:10.1145/2554850.2554855
Arnold, D., Zhang, M., Urbanowicz, R., Iqbal, M., Shafi, K., Stonedahl, F., . . . Auger, A. (2014) "GECCO Comp '14: Proceedings of the 2014 conference companion on Genetic and evolutionary computation companion". Berlin: Springer.
Andreae, H., Andreae, P., Low, J., & Brown, D. (2014) "A Study Of Auti: A Socially Assistive Robotic Toy". In O. S. Iversen, P. Markopoulos, C. Dindler, F. Garzotto, & C. Frauenberger (Eds.), IDC ’14 - Proceedings of the 2014 Conference on Interaction Design and Children (pp. 245-248). New York: Association for Computing Machinery.
Alvarez, I. M., Browne, W. N., & Zhang, M. (2014) "Reusing learned functionality to address complex boolean functions". Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 8886, 383-394. doi:10.1007/978-3-319-13563-2_33
Alvarez, I. M., Browne, W. N., & Zhang, M. (2014) "Reusing learned functionality in XCS: Code fragments with constructed functionality and constructed features". In GECCO 2014 - Companion Publication of the 2014 Genetic and Evolutionary Computation Conference (pp. 969-976). doi:10.1145/2598394.2611383
Alvarez, I., Browne, W., & Zhang, M. (2014) "On Learning the Hidden Multiplexer by Reusing Learned Functionality". In Proceedings of the 10th International Conference on Simulated Evolution and Learning (SEAL 2014) (pp. 383-394). Berlin: Springer.
Alvarez, I., Browne, W., & Zhang, M. (2014) "eusing learned functionality in XCS: code fragments with constructed functionality and constructed features". In Proceedings of 2014 Genetic and Evolutionary Computation Conference (GECCO 2014 Companion, IWLCS 2014) (pp. 969-976). Vancouver, Canada: ACM Press.
Al-Sahaf, H., Zhang, M., & Johnston, M. (2014) "Genetic Programming for Multiclass Texture Classification Using a Small Number of Instances". In Unknown Conference Vol. 8886 (pp. 335-346). Springer. doi:10.1007/978-3-319-13563-2_29
Al-Sahaf, H., Zhang, M., & Johnston, M. (2014) "Genetic Programming Evolved Filters from a Small Number of Instances for Multiclass Texture Classification". In Proceedings of the 29th International Conference on Image and Vision Computing New Zealand (IVCNZ 2014) (pp. 84-89). ACM. doi:10.1145/2683405.2683418
Ahmed, S., Zhang, M., Peng, L., & Xue, B. (2014) "Multiple Feature Construction for Effective Biomarker Identification and Classification using Genetic Programming". In Proceedings of 2014 Genetic and Evolutionary Computation Conference (GECCO 2014) (pp. 249-256). Vancouver, Canada: ACM Press. doi:10.1145/2576768.2598292
Ahmed, S., Zhang, M., Peng, L., & Xue, B. (2014) "Genetic Programming for Measuring Peptide Detectability". In Proceedings of the 10th International Conference on Simulated Evolution and Learning (SEAL 2014) (pp. 593-604). Berlin: Springer.
Ahmed, S., Zhang, M., & Peng, L. (2014) "Prediction of detectable peptides in ms data using genetic programming". In GECCO 2014 - Companion Publication of the 2014 Genetic and Evolutionary Computation Conference (pp. 37-38). doi:10.1145/2598394.2598421
Ahmed, S., Zhang, M., & Peng, L. (2014) "Peptide Detection Prediction of MS data using Genetic Programming". In Proceedings of 2014 Genetic and Evolutionary Computation Conference (GECCO 2014 Companion) (pp. 37-38). Vancouver, Canada: ACM Press.
Ahmed, S., Zhang, M., & Peng, L. (2014) "Improving Feature Ranking for Biomarker Discovery in Proteomics Mass Spectrometry Data using Genetic Programming". Connection Science, 26(3), 215-243. doi:10.1080/09540091.2014.906388
Ahmed, S., Zhang, M., & Peng, L. (2014) "GPMS: A Genetic Programming Based Approach to Multiple Alignment of Liquid Chromatography-Mass Spectrometry Data". In Proceedings of the 16th European Conference on the Applications of Evolutionary Computation (EvoApplications 2014) (pp. 915-927). Berlin: Springer.
Ahmed, S., Zhang, M., & Peng, L. (2014) "A New GP-based Wrapper Feature Construction Approach to Classification and Biomarker Identification". In 2014 IEEE Congress on Evolutionary Computation (pp. 2756-2763). Beijing, China: IEEE Press.

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