Welcome to Ke Tang's homepage

Research interests:

• Evolutionary Computation and Meta-heuristic
• Maching Learning and Data Mining

Professional activities:

• Honorary Senior Research Fellow at School of Computer Science, University of Birmingham, UK
  
  
• Senior Member of IEEE
  
  
• Member of Emergent Technologies Technical Committee, IEEE Computational Intelligence Society (2011 -)
  
  
• Associate Editor of IEEE Computational Intelligence Magazine
  
  
• Associate Editor of Computational Optimization and Applications
  
  
• Conference Services
  Program Co-chair of the 14th International Conference on Intelligent Data Engineering and Automated Learning (IDEAL2013), October 20-23, 2013, Hefei, Anhui, China.
  Technical Chair of the 2013 IEEE Congress of Evolutionary Computation (CEC2013), June 20-23, 2013, Cancun, Mexico.
  Program Co-Chair of the 2010 IEEE Congress of Evolutionary Computation (CEC2010), July 18-23, Barcelona, Spain.
  

Note: Publications listed below are made on-line available for faster dissemination. The copyright of the papers is owned by their publisher.

Refereed Journal Papers:

1. Z. Yang, X. Li, C. P. Bowers, T. Schnier, K. Tang and X. Yao, "An Efficient Evolutionary Approach to Parameter Identification in a Building Thermal Model," IEEE Transactions on Systems, Man, and Cybernetics: Part C, 42(6): 957-969, November 2012.
   
   
2. A. Devert, T. Weise and K. Tang, "A Study on Scalable Representations for Evolutionary Optimization of Ground Structures," Evolutionary Computation, 20(3): 453-472, January 2012.
   
   
3. Y. Mei, K. Tang and X. Yao, "A Memetic Algorithm for Periodic Capacitated Arc Routing Problem," IEEE Transactions on Systems, Man, and Cybernetics: Part B, 41(6): 1654-1667, December, 2011.
   
   
4. T. Chen, K. Tang, G. Chen and X. Yao, "A Large Population Size Can Be Unhelpful in Evolutionary Algorithms," Theoretical Computer Science, 436: 54-70, June 2012.
   
   
5. T. Weise and K. Tang, "Evolving Distributed Algorithms with Genetic Programming," IEEE Transactions on Evolutionary Computation, 16(2): 242-265, April 2012.
   
   
6. Z. Yang, K. Tang and X. Yao, "Scalability of Generalized Adaptive Differential Evolution for Large-Scale Continuous Optimization," Soft Computing, 15(11): 2141-2155, November, 2011.
   
   
7. X. Yu, K. Tang and X. Yao, "Immigrant Schemes for Evolutionary Algorithms in Dynamic Environments: Adapting the Replacement Rate," Science in China Series F: Information Sciences, 54(7): 1352-1364, July, 2011.
   
   
8. Y. Mei, K. Tang and X. Yao, "Decomposition-Based Memetic Algorithm for Multi-Objective Capacitated Arc Routing Problem," IEEE Transactions on Evolutionary Computation, 15(2): 151-165, April 2011.
   
   
9. Z. Wang, K. Tang and X. Yao, "A Memetic Algorithm for Multi-level Redundancy Allocation," IEEE Transactions on Reliability, 59(4): 754-765, December 2010.
   
   
10. Z. Wang, K. Tang and X. Yao, "Multi-objective Approaches to Optimal Testing Resource Allocation in Modular Software Systems," IEEE Transactions on Reliability, 59(3): 563-575, September 2010.
    available as a PDF here
    
    
11. F. Peng, K. Tang, G. Chen and X. Yao, "Population-based Algorithm Portfolios for Numerical Optimization," IEEE Transactions on Evolutionary Computation, 14(5): 782-800, October 2010.
    available as a PDF here, source code can be downloaded here
    
    
12. T. Chen, K. Tang, G. Chen and X. Yao, "Analysis of Computational Time of Simple Estimation of Distribution Algorithms," IEEE Transactions on Evolutionary Computation, 14(1): 1-22, February 2010.
    available as a PDF here
    
    
13. K. Tang, Y. Mei and X. Yao, "Memetic Algorithm with Extended Neighborhood Search for Capacitated Arc Routing Problems," IEEE Transactions on Evolutionary Computation, 13(5): 1151-1166, October 2009.
    available as a PDF here, source code can be downloaded here
    
    
14. K. Tang, G. Pugalenthi, P. N. Suganthan, C. J. Lanczycki and S. Chakrabarti, "Prediction of functionally important sites from protein sequences using sparse kernel least squares classifiers," Biochemical and Biophysical Research Communications, 384(2): 155-159, June 2009.
    
    
15. G. Pugalenthi, K. Tang, P. N. Suganthan and S. Chakrabarti, "Identification of structurally conserved residues of proteins in absence of structural homologs using neural network ensemble," Bioinformatics, 25(2): 204-210, 2009. (doi:10.1093/bioinformatics/btn618)
    available as a PDF here
    
    
16. Y. Mei, K. Tang and X. Yao, "A Global Repair Operator for Capacitated Arc Routing Problem," IEEE Transactions on Systems, Man, and Cybernetics: Part B, 39(3): 723-734, June 2009.
    available as a PDF here, source code of RTS* can be downloaded here
    
    
17. X. Yu, K. Tang, T. Chen and X. Yao, "Empirical Analysis of Evolutionary Algorithms with Immigrants Schemes for Dynamic Optimization," Memetic Computing, 1(1): 3-24, 2009. (doi: 10.1007/s12293-008-0003-6)
    available as a PDF here
    
    
18. K. Tang, M. Lin, F. L. Minku and X. Yao, "Selective Negative Correlation Learning Approach to Incremental Learning," Neurocomputing, 72(13-15): 2796-2805, August, 2009.
    
    
19. Z. Yang, K. Tang and X. Yao, "Large Scale Evolutionary Optimization Using Cooperative Coevolution," Information Sciences, 178(15): 2985-2999, 2008.
    available as a PDF here, source code of DECC-G can be downloaded here
    
    
20. G. Pugalenthi, K. Tang, P. N. Suganthan, G. Archunan and R. Sowdhamini, "A Machine Learning Approach for the Identification of Odorant binding Proteins from Sequence-derived Properties," BMC-Bioinformatics, 8:351, September 2007. (Co-first author with G. Pugalenthi)
    
    
21. E. K. Tang, P. N. Suganthan, X. Yao, "Gene Selection Algorithms for Microarray Data Based on Least Square Support Vector Machine," BMC-Bioinformatics, 7:95, 27 February 2006.
    available as a PDF here
    
    
22. E. K. Tang, P. N. Suganthan, X. Yao, "An Analysis of Diversity Measures," Machine Learning, 65: 247-271, 2006.
    available as a PDF here
    
    
23. E. K. Tang, P. N. Suganthan, X. Yao and A. K. Qin, "Linear Dimensionality Reduction Using Relevance Weighted LDA," Pattern Recognition, 38(4):485-493, April 2005.
    available as a PDF here
    
    

Selected Conference Papers:

1. K. Tang, R. Wang and T. Chen, "Towards Maximizing The Area Under The ROC Curve For Multi-class Classification Problems," accepted by The Twenty-Fifth AAAI Conference on Artificial Intelligence (AAAI 2011), San Francisco, USA, 7-11 August 2011.
   
   
2. T. Chen, P. K. Lehre, K. Tang and X. Yao, "When Is an Estimation of Distribution Algorithm Better than an Evolutionary Algorithm?," in Proceedings of the 2009 IEEE Congress on Evolutionary Computation (CEC2009), Trondheim, Norway, 2009, IEEE Press, pp. 1470-1477.
   
   
3. Z. Yang, K. Tang and X. Yao, "Self-adaptive Differential Evolution with Neighborhood Search," in Proceedings of the 2008 IEEE Congress on Evolutionary Computation (CEC2008), Hongkong, China, 2008, pp. 1110-1116.
   available as a PDF here, source code can be downloaded here
   
   
4. Z. Yang, K. Tang and X. Yao, "Multilevel Cooperative Coevolution for Large Scale Optimization," in Proceedings of the 2008 IEEE Congress on Evolutionary Computation (CEC2008), Hongkong, China, 2008, pp. 1663-1670.
   
   
5. E. K. Tang, P. N. Suganthan, X. Yao, "Feature Selection for Microarray Data Using Least Squares SVM and Particle Swarm Optimization," in Proceedings of the 2005 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB05), San Diego, USA, November 2005, pp. 9-17.
   
   

Last updated on May 13, 2013.