Publications

  • Journal Papers

Selected Recent Publications

  1. C. Huang, Y. Li, X. Yao (2020), A Survey of Automatic Parameter Tuning Methods for Metaheuristics, IEEE Transactions on Evolutionary Computation. 24(2):201-216, April 2020.
  2. B. Yuan, H. Chen, X. Yao (2020), Toward Efficient Design Space Exploration for Fault-tolerant Multiprocessor Systems, IEEE Transactions on Evolutionary Computation, 24(1):1-15, Feb. 2020.
  3. D. Yazdani, M. N. Omidvar, T. T. Nguyen, J. Branke, X. Yao (2020). Scaling Up Dynamic Optimization Problems: A Divide-and-Conquer Approach. IEEE Transactions on Evolutionary Computation. 24(1):157-169, Feb. 2020.
  4. C. He, L. Li, Y. Tian, X. Zhang, R. Cheng, Y. Jin, X. Yao(2019). Accelerating Large-scale Multi-objective Optimization via Problem Reformulation. IEEE Transactions on Evolutionary Computation. 23(6):949-961.
  5. L. Song, L.L. Minku and X. Yao(2019). Software Effort Interval Prediction via Bayesian Inference and Synthetic Bootstrap Resampling. ACM Transactions on Software Engineering and Methodology (TOSEM), 28(1), 5.
  6. P Yang, K Tang, X Yao (2019), A Parallel Divide-and-Conquer-Based Evolutionary Algorithm for Large-Scale Optimization, IEEE Access, 7:163105-163118.
  7. L Zhang, K Tang, X Yao (2019), Explicit Planning for Efficient Exploration in Reinforcement Learning, Advances in Neural Information Processing Systems (NeurIPS’2019), 7486-7495.
  8. S Liu, K Tang, X Yao (2019), Automatic Construction of Parallel Portfolios via Explicit Instance Grouping, Proceedings of the AAAI Conference on Artificial Intelligence 33 (AAAI’2019), 1560-1567.
  9. W Hong, K Tang, A Zhou, H Ishibuchi, X Yao (2018), A Scalable Indicator-Based Evolutionary Algorithm for Large-Scale Multiobjective Optimization, IEEE Transactions on Evolutionary Computation 23 (3), 525-537.
  10. L. Song, L. L. Minku, X. Yao(2018, October). A novel automated approach for software effort estimation based on data augmentation. In Proceedings of the 26th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE’2018) (pp. 468-479). ACM.
  11. Y. Sun, K. Tang, Z. Zhu, X. Yao(2018). Concept drift adaptation by exploiting historical knowledge. IEEE Transactions on Neural Networks and Learning Systems, 29(10):4822-4832.
  12. X. Lu, S. Menzel, K. Tang, X. Yao(2018). Cooperative co-evolution-based design optimization: a concurrent engineering perspective. IEEE Transactions on Evolutionary Computation, 22(2), 173-188.
  13. B. Yuan, H. Chen, X. Yao(2017). Optimal relay placement for lifetime maximization in wireless underground sensor networks. Information Sciences, 418, 463-479. 

 

More Publications (since 2017)

  1. M. Li, X. Yao (2019). Quality Evaluation of Solution Sets in Multiobjective Optimisation: A Survey. ACM Computing Surveys (CSUR), 52(2), 26.
  2. E. Fernandes, A. {de Carvalho}, X. Yao (2020). Ensemble of Classifiers based on MultiObjective Genetic Sampling for Imbalanced Data. IEEE Transactions on Knowledge and Data Engineering. 32(6):1104-1115, June 2020.
  3. C. Wang, C. Xu, X. Yao, D. Tao (2019). Evolutionary generative adversarial networks. IEEE Transactions on Evolutionary Computation. 23(6):921-934.
  4. C. He, L. Li, Y. Tian, X. Zhang, R. Cheng, Y. Jin, X. Yao(2019). Accelerating Large-scale Multi-objective Optimization via Problem Reformulation. IEEE Transactions on Evolutionary Computation. 23(6):949-961.
  5. B. Kazimipour, M.N. Omidvar, A.K. Qin, X. Li, X. Yao(2019). Bandit-based cooperative coevolution for tackling contribution imbalance in large-scale optimization problems. Applied Soft Computing, 76, 265-281.
  6. S. Wang, L. L. Minku, N. Chawla, X. Yao(2019). Learning in the Presence of Class Imbalance and Concept Drift. Neurocomputing.
  7. L. Song, L.L. Minku and X. Yao(2019). Software Effort Interval Prediction via Bayesian Inference and Synthetic Bootstrap Resampling. ACM Transactions on Software Engineering and Methodology (TOSEM), 28(1), 5.
  8. M. Li,X. Yao(2019, March). An empirical investigation of the optimality and monotonicity properties of multiobjective archiving methods. In International Conference on Evolutionary Multi-Criterion Optimization (pp. 15-26). Springer, Cham.
  9. Y. Sun, K. Tang, Z. Zhu, X. Yao(2018). Concept drift adaptation by exploiting historical knowledge. IEEE Transactions on Neural Networks and Learning Systems, (99), 1-11.
  10. X. Lu, S. Menzel, K. Tang, X. Yao(2018). Cooperative co-evolution-based design optimization: a concurrent engineering perspective. IEEE Transactions on Evolutionary Computation, 22(2), 173-188.
  11. R. Cheng, M. Li, K. Li, X. Yao(2018). Evolutionary Multiobjective Optimization-Based Multimodal Optimization: Fitness Landscape Approximation and Peak Detection. IEEE Transactions on Evolutionary Computation, 22(5), 692-706.
  12. K. Li, R. Chen, G. Min, X. Yao(2018). Integration of preferences in decomposition multiobjective optimization. IEEE Transactions on Cybernetics, 48(12):3359-3370.
  13. T. Chen, K. Li, R. Bahsoon, X. Yao(2018). FEMOSAA: Feature-Guided and Knee-Driven Multi-Objective Optimization for Self-Adaptive Software. ACM Transactions on Software Engineering and Methodology (TOSEM), 27(2), 5.
  14. T. Chen, R. Bahsoon, X. Yao(2018). A survey and taxonomy of self-aware and self-adaptive cloud autoscaling systems. ACM Computing Surveys (CSUR), 51(3), 61.
  15. R. G. F. Soares, H. Chen, X. Yao(2018). Efficient cluster-based boosting for semisupervised classification. IEEE Transactions on Neural Networks and Learning Systems, 29(11):5667-5680.
  16. Y. Li, B. Jiang, H. Chen, X. Yao(2018). Symbolic Sequence Classification in the Fractal Space. IEEE Transactions on Emerging Topics in Computational Intelligence. Published online on 5 November 2018. DOI: 10.1109/TETCI.2018.2876528
  17. K. Li, R. Chen, G. Fu, X. Yao(2019). Two-archive evolutionary algorithm for constrained multi-objective optimization. IEEE Transactions on Evolutionary Computation. 23(2): 303-315.
  18. K. Li, R. Chen, D. Savic, X. Yao(2019). Interactive Decomposition Multi-Objective Optimisation via Progressively Learned Value Functions. IEEE Transactions on Fuzzy Systems. 27(5): 849–860.
  19. R. Cheng, M. N. Omidvar, A. H. Gandomi, B. Sendhoff, S. Menzel, X. Yao(2019). Solving Incremental Optimization Problems via Cooperative Coevolution. IEEE Transactions on Evolutionary Computation. 23(5):762-775.
  20. Z. Su, G. Zhang, F. Yue, L. Chang, J. Jiang, X. Yao(2018). SNR-Constrained Heuristics for Optimizing the Scaling Parameter of Robust Audio Watermarking. IEEE Transactions on Multimedia, 20(10), 2631-2644.
  21. H. Chen, B. Jiang, X. Yao(2018). Semisupervised Negative Correlation Learning. IEEE Transactions on Neural Networks and Learning Systems, 29(11):5366-5379.
  22. M. Wang, B. Li, G. Zhang, X. Yao(2018). Population Evolvability: Dynamic Fitness Landscape Analysis for Population-Based Metaheuristic Algorithms. IEEE Transactions on Evolutionary Computation, 22(4), 550-563.
  23. P. Yang, K. Tang, X. Yao(2018). Turning high-dimensional optimization into computationally expensive optimization. IEEE Transactions on Evolutionary Computation, 22(1), 143-156.
  24. S. Wang, L. L. Minku, X. Yao(2018). A systematic study of online class imbalance learning with concept drift. IEEE Transactions on Neural Networks and Learning Systems, 29(10):4802-4821.
  25. Z. Gong, H. Chen, B. Yuan, X. Yao(2019). Multiobjective Learning in the Model Space for Time Series Classification. IEEE Transactions on Cybernetics, 49(3):918-932.
  26. R. Cheng, C. He, Y. Jin, X. Yao(2018). Model-based evolutionary algorithms: a short survey. Complex & Intelligent Systems, 4(4), 283-292.
  27. L. Song, L. L. Minku, X. Yao(2018, October). A novel automated approach for software effort estimation based on data augmentation. In Proceedings of the 2018 26th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering(pp. 468-479). ACM.
  28. C. Qian, C. Bian, Y. Yu, K. Tang, X. Yao(2018, July). Analysis of noisy evolutionary optimization when sampling fails. In Proceedings of the Genetic and Evolutionary Computation Conference(pp. 1507-1514). ACM.
  29. D. Yazdani, J. Branke, M. N. Omidvar, T. T. Nguyen, X. Yao(2018, July). Changing or keeping solutions in dynamic optimization problems with switching costs. In Proceedings of the Genetic and Evolutionary Computation Conference(pp. 1095-1102). ACM.
  30. T. Chen, M. Li, X. Yao(2018, July). On the effects of seeding strategies: A case for search-based multi-objective service composition. In Proceedings of the Genetic and Evolutionary Computation Conference(pp. 1419-1426). ACM.
  31. M. Li, T. Chen, X. Yao(2018, May). A Critical Review of" A Practical Guide to Select Quality Indicators for Assessing Pareto-Based Search Algorithms in Search-Based Software Engineering": Essay on Quality Indicator Selection for SBSE. In 2018 IEEE/ACM 40th International Conference on Software Engineering: New Ideas and Emerging Technologies Results (ICSE-NIER)(pp. 17-20). IEEE.
  32. S. Shi, Y. Chen, X. Yao(2018, May). Computing-Inspired Detection of Multiple Cancers. In 2018 IEEE International Conference on Communications (ICC)(pp. 1-6). IEEE.
  33. C. Qian, Y. Zhang, K. Tang,X. Yao(2018, April). On multiset selection with size constraints. In Thirty-Second AAAI Conference on Artificial Intelligence.
  34. T. Chen, R. Bahsoon, S. Wang, X. Yao(2018, March). To Adapt or Not to Adapt?: Technical Debt and Learning Driven Self-Adaptation for Managing Runtime Performance. In Proceedings of the 2018 ACM/SPEC International Conference on Performance Engineering(pp. 48-55). ACM.
  35. M. Li, L. Zhen, X. Yao(2017). How to read many-objective solution sets in parallel coordinates. IEEE Computational Intelligence Magazine, 12(4), 88-100.
  36. M. N. Omidvar, M. Yang Y. Mei, X. Li and X. Yao(2017). DG2: A faster and more accurate differential grouping for large-scale black-box optimization. IEEE Transactions on Evolutionary Computation, 21(6), 929-942.
  37. Y. Chen, S. Shi, X. Yao, T. Nakano (2017). Touchable computing: Computing-inspired bio-detection. IEEE Transactions on Nanobioscience, 16(8), 810-821.
  38. M. Yang, M. N. Omidvar, C. Li, X. Li, Z. Cai, B. Kazimipour, X. Yao(2017). Efficient resource allocation in cooperative co-evolution for large-scale global optimization. IEEE Transactions on Evolutionary Computation, 21(4), 493-505.
  39. G. Zhang, Z. Su, M. Li, F. Yue, J. Jiang, X. Yao(2017). Constraint handling in NSGA-II for solving optimal testing resource allocation problems. IEEE Transactions on Reliability, 66(4), 1193-1212.
  40. B. Jiang, H. Chen, B. Yuan, X. Yao(2017). Scalable graph-based semi-supervised learning through sparse Bayesian model. IEEE Transactions on Knowledge and Data Engineering, 29(12), 2758-2771.
  41. B. Yuan, H. Chen, X. Yao(2017). Optimal relay placement for lifetime maximization in wireless underground sensor networks. Information Sciences, 418, 463-479.
  42. G. Zhang, Z. Su, M. Li, M. Qi, J. Jiang, X. Yao(2017). A Task-Oriented Heuristic for Repairing Infeasible Solutions to Overlapping Coalition Structure Generation. IEEE Transactions on Systems, Man, and Cybernetics: Systems, published online on 26 June 2017, DOI: 10.1109/TSMC.2017.2712624..
  43. L. Zhang, K. Tang, X. Yao(2017). Log-normality and skewness of estimated state/action values in reinforcement learning. In Advances in Neural Information Processing Systems(pp. 1804-1814).
  44. R. G. F. Soares, H. Chen, X. Yao(2017). A cluster-based semisupervised ensemble for multiclass classification. IEEE Transactions on Emerging Topics in Computational Intelligence, 1(6), 408-420.
  45. R. Cheng, M. Li, Y. Tian, X. Zhang, S. Yang, Y. Jin, X. Yao(2017). A benchmark test suite for evolutionary many-objective optimization. Complex & Intelligent Systems, 3(1), 67-81.
  46. L. Zhen,M. Li, R. Cheng, D. Peng, X. Yao(2017, November). Adjusting parallel coordinates for investigating multi-objective search. In Asia-Pacific Conference on Simulated Evolution and Learning(pp. 224-235). Springer, Cham.
  47. H. K. Singh, X. Yao(2017, November). Improvement of Reference Points for Decomposition Based Multi-objective Evolutionary Algorithms. In Asia-Pacific Conference on Simulated Evolution and Learning(pp. 284-296). Springer, Cham.
  48. P. T. Thuong, N. X. Hoai, X. Yao(2017, July). Combining conformal prediction and genetic programming for symbolic interval regression. In Proceedings of the Genetic and Evolutionary Computation Conference(pp. 1001-1008). ACM.
  49. Y. Chen, S. Shi, X. Yao, T. Nakano, P. Kosmas (2017, July). Touchable computation: Computing-inspired bio-detection. In 2017 IEEE 18th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC)(pp. 1-5). IEEE.
  50. J. Chen, M. N. Omidvar, M. Azad, X. Yao(2017, June). Knowledge-based particle swarm optimization for PID controller tuning. In 2017 IEEE Congress on Evolutionary Computation (CEC)(pp. 1819-1826). IEEE.
  51. R. Cheng, M. Li, X. Yao(2017, June). Parallel peaks: A visualization method for benchmark studies of multimodal optimization. In 2017 IEEE Congress on Evolutionary Computation (CEC)(pp. 263-270). IEEE.
  52. I. L. Yen, F. Bastani, Y. Huang, Y. Zhang, X. Yao(2017, June). SaaS for automated job performance appraisals using service technologies and big data analytics. In 2017 IEEE International Conference on Web Services (ICWS)(pp. 412-419). IEEE.

A more complete list is at https://www.cs.bham.ac.uk/~xin/publications.html.

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