## Publications

### Refereed Journal Papers

- Z. Liu, B. Wang and K. Tang, “Handling Constrained Multi-Objective Optimization Problems via Bidirectional Coevolution,”
*IEEE Transactions on Cybernetics*, in press (DOI: 10.1109/TCYB.2021.3056176). - Y. Lei and K. Tang, “Learning Rates for Stochastic Gradient Descent with Nonconvex Objectives,”
*IEEE Transactions on Pattern Analysis and Machine Intelligence*, in press (DOI: 10.1109/TPAMI.2021.3068154). - C. Bian, C. Qian, Y. Yu and K. Tang, “On the Robustness of Median Sampling in Noisy Evolutionary Optimization,”
*SCIENCE CHINA Information Sciences*, accepted on October 16, 2020. - P. Yang, Q. Yang, K. Tang and X. Yao, “Parallel Exploration via Negatively Correlated Search,”
*Frontiers of Computer Science*, in press (DOI: 10.1007/s11704-020-0431-0), 2020. - C. Hou, H. Zhang, S. He and K. Tang, “GloDyNE: Global Topology Preserving Dynamic Network Embedding,”
*IEEE Transactions on Knowledge and Data Engineering*, in press (DOI: 10.1109/TKDE.2020.3046511). - K. Tang, S. Liu, P. Yang and X. Yao, “Few-shots Parallel Algorithm Portfolio Construction via Co- evolution,”
*IEEE Transactions on Evolutionary Computation*, in press (DOI: 10.1109/TEVC.2021.3059661). - W. Hong, P. Yang and K. Tang, “Evolutionary Computation for Large-scale Multi-objective Optimization: A Decade of Progresses,”
*International Journal of Automation and Computing*, in press (DOI: 10.1007/s11633-020-1253-0). - T. Sun, K. Tang and D. Li, “Gradient Descent Learning with Floats,”
*IEEE Transactions on Cybernetics*, in press (DOI: 10.1109/TCYB.2020.2997399). - S. Liu, K. Tang and X. Yao, “Generative Adversarial Construction of Parallel Portfolios,”
*IEEE Transactions on Cybernetics*, in press (DOI: 10.1109/TCYB.2020.2984546). - W. Hong, C. Qian and K. Tang, “Efficient Minimum Cost Seed Selection with Theoretical Guarantees for Competitive Influence Maximization,”
*IEEE Transactions on Cybernetics*, in press (DOI: 10.1109/TCYB.2020.2966593). - C. Qian, C. Bian, Y. Yu, K. Tang and Xin Yao, “Analysis of Noisy Evolutionary Optimization When Sampling Fails,”
*Algorithmica*, in press (DOI: 10.1007/s00453-019-00666-6). - L. Feng, Y. Huang, I. W. Tsang, A. Gupta, K. Tang, K. C. Tan and Y. S. Ong, “Towards Faster Vehicle Routing by Transferring Knowledge from Customer Representation,”
*IEEE Transactions on Intelligent Transportation Systems*, in press (DOI: 10.1109/TITS.2020.3018903). - L. Feng, Y. Huang, L. Zhou, J. Zhong, A. Gupta, K. Tang and K. C. Tan, “Explicit Evolutionary Multitasking for Combinatorial Optimization: A Case Study on Capacitated Vehicle Routing Problem,” IEEE Transactions on Cybernetics, 51(6): 3143-3156, June 2021.
- Y. Lei, T. Hu and K. Tang, “Generalization Performance of Multi-pass Stochastic Gradient Descent with Convex Loss Functions,”
*Journal of Machine Learning Research*, 22: 1-41, January 2021. - C. Bian, C. Qian, K. Tang and Y. Yu, “Running Time Analysis of the (1+1)-EA for Robust Linear Optimization,”
*Theoretical Computer Science*, 843: 57-72, December 2020. - C. Hou, S. He and K. Tang, “RoSANE: Robust and Scalable Attributed Network Embedding for Sparse Networks,”
*Neurocomputing*, 409: 231-243, October 2020. - Y. Lei, T. Hu, G. Li and K. Tang, “Stochastic Gradient Descent for Nonconvex Learning without Bounded Gradient Assumptions,”
*IEEE Transactions on Neural Networks and Learning Systems*, 39(10): 4394-4400, October 2020. - F. Wang. Y. Li, A. Zhou and K. Tang, “An Estimation of Distribution Algorithm for Mixed-variable Newsvendor Problems,”
*IEEE Transactions on Evolutionary Computation*, 24(3): 479-493, June 2020. - W. Du, W. Ying, P. Yang, X. Cao, G. Yan, K. Tang and D. Wu, “Network-Based Heterogeneous Particle Swarm Optimization and Its Application in UAV Communication Coverage,”
*IEEE Transactions on Emerging Topics in Computational Intelligence*, 4(3): 312-323, June 2020. - D. Jiao, P. Yang, L. Fu, L. Ke and K. Tang, “Optimal Energy-Delay Scheduling for Energy-Harvesting WSNs with Interference Channel via Negatively Correlated Search,”
*IEEE Internet of Things Journal*, 7(3): 1690-1703, March 2020. - D. Wu, N. Jiang, W. Du, K. Tang and X. Cao, “Particle Swarm Optimization with Moving Particles on Scale-free Networks,”
*IEEE Transactions on Network Science and Engineering*, 7(1): 497-506, March 2020. - C. Qian, Y. Yu, K. Tang, X. Yao and Z.-H. Zhou, “Maximizing Submodular or Monotone Approximately Submodular Functions by Multi-objective Evolutionary Algorithms,”
*Artificial Intelligence*, 275: 279-294, October 2019. - W. Hong, K. Tang, A. Zhou, H. Ishibuchi and X. Yao, “A Scalable Indicator-Based Evolutionary Algorithm for Large-Scale Multi-Objective Optimization,”
*IEEE Transactions on Evolutionary Computation*, 23(3): 525-537, June 2019. - X. Lu, T. Sun, and K. Tang, “Evolutionary Optimization with Hierarchical Surrogates,”
*Swarm and Evolutionary Computation*, vol. 47, pp. 21-32, June 2019. - X. Ma, X. Li, Q. Zhang, K. Tang, Z. Liang, W. Xie and Z. Zhu, “A Survey on Cooperative Coevolutionary Algorithms,”
*IEEE Transactions on Evolutionary Computation*, 23(3): 421-441, June 2019. - Z.-Z. Liu, Y. Wang, S. Yang and K. Tang, “An Adaptive Framework to Tune The Coordinate Systems in Nature-inspired Optimization Algorithms,”
*IEEE Transactions on Cybernetics*, 49(4): 1403-1416, April 2019. - X. Liang, A. K. Qin, K. Tang and K. C. Tan, “QoS-Aware Web Service Selection with Internal Complementarity,”
*IEEE Transactions on Services Computing*, 12(2): 276-289, March 2019. - C. Qian, C. Bian, W. Jiang and K. Tang, “Running Time Analysis of the (1+1)-EA for OneMax and LeadingOnes Under Bit-Wise Noise,” Algorithmica, 81(2): 749-795, February 2019.
- W. Du, M. Zhang, W. Ying, M. Perc, K. Tang, X. Cao and D. Wu, “The networked evolutionary algorithm: A network science perspective,”
*Applied Mathematics and Computation*, 338: 33-43, December 2018. - Y. Sun, K. Tang, Z. Zhu and X. Yao, “Concept Drift Adaptation by Exploiting Historical Knowledge,”
*IEEE Transactions on Neural Networks and Learning Systems*, 29(10): 4822-4832, October 2018. - C. Qian, J. Shi, K. Tang and Z.-H. Zhou, “Constrained Monotone k-Submodular Function Maximization Using Multiobjective Evolutionary Algorithms with Theoretical Guarantee,”
*IEEE Transactions on Evolutionary Computation*, 22(4): 595-608, August 2018. - J. Zhang, A. Zhou, K. Tang and G. Zhang, “Preselection via classification: A case study on evolutionary multiobjective optimization,”
*Information Sciences*, 465: 388-403, July 2018. - C. Qian, Y. Yu, K. Tang, Y. Jin, X. Yao and Z.-H. Zhou, “On the Effectiveness of Sampling for Evolutionary Optimization in Noisy Environments,”
*Evolutionary Computation*, 26(2): 237-267, June 2018. - X. Lu, S. Menzel, K. Tang and X. Yao, “Cooperative Co-evolution based Design Optimisation: A Concurrent Engineering Perspective,”
*IEEE Transactions on Evolutionary Computation*, 22(2): 173- 188, April 2018. - P. Yang, K. Tang and X. Yao, “Turning High-dimensional Optimization into Computationally Expensive Optimization,”
*IEEE Transactions on Evolutionary Computation*, 22(1): 143-156, February 2018. - J. Zhong, P. Yang, K. Tang, “A Quality-Sensitive Method for Learning from Crowds,”
*IEEE Transactions on Knowledge and Data Engineering*, 29(12): 2643-2654, December 2017. - K. Cai, J. Zhang, M. Xiao, K. Tang and W. Du, “Simultaneous Optimization of Airspace Congestion and Flight Delay in Air Traffic Network Flow Management,”
*IEEE Transactions on Intelligent Transportation Systems*, 18(11): 3072-3082, November 2017. - K. Tang, J. Wang X. Li and X. Yao, “A Scalable Approach to Capacitated Arc Routing Problems Based on Hierarchical Decomposition,”
*IEEE Transactions on Cybernetics*, 47(11): 3928-3940, November 2017. - Y. Zhang, Y. Mei, K. Tang and K. Jiang, “Memetic algorithm with route decomposing for periodic capacitated arc routing problem,”
*Applied Soft Computing*, 52: 1130-1142, March 2017. - B. Li, K. Tang, J. Li and X. Yao, “Stochastic Ranking Algorithm for Many-Objective Optimization Based on Multiple Indicators,”
*IEEE Transactions on Evolutionary Computation*, 20(6): 924-938, December 2016. - S. He, G. Jia, Z. Zhu, Q. Huang, K. Tang, J. Liu, M. Musolesi, J. K. Heath and X. Yao, “Cooperative Co-Evolutionary Module Identification with Application to Cancer Disease Module Discovery,”
*IEEE Transactions on Evolutionary Computation*, 20(6): 874-891, December 2016. - T. Weise, Y. Wu, R. Chiong, K. Tang and J. Lässig, “Global versus local search: the impact of population sizes on evolutionary algorithm performance,”
*Journal of Global Optimization*, 66(3): 511- 534, November 2016. - Z. Yang, B. Sendhoff, K. Tang and X. Yao, “Target shape design optimization by evolving B-splines with cooperative coevolution,”
*Applied Soft Computing*, 48: 672-682, November 2016. - Y. Sun, K. Tang, L. L. Minku, S. Wang and X. Yao, “Online Ensemble Learning of Data Streams with Gradually Evolved Classes,”
*IEEE Transactions on Knowledge and Data Engineering*, 28(6): 1532-1545, June 2016. - K. Tang, P. Yang and X. Yao, “Negatively Correlated Search,”
*IEEE Journal on Selected Areas in Communications*, 34(3): 1-9, March 2016. - J. Wang, K. Tang, J. A. Lozano and X. Yao, “Estimation of Distribution Algorithm with Stochastic Local Search for Uncertain Capacitated Arc Routing Problems,”
*IEEE Transactions on Evolutionary Computation*, 20(1): 96-109, February 2016. - W. Hong and K. Tang, “Convex hull-based multi-objective evolutionary computation for maximizing receiver operating characteristics performance,”
*Memetic Computing*, 8(1): 35-44, February 2016. - P. Yang, K. Tang, J. A. Lozano and X. Cao, “Path Planning for Single Unmanned Aerial Vehicle by Separately Evolving Waypoints,”
*IEEE Transactions on Robotics*, 31(5): 1130-1146, October 2015. - H. Fu, B. Sendhoff, K. Tang and X. Yao, “Robust Optimization Over Time: Problem Difficulties and Benchmark Problems,”
*IEEE Transactions on Evolutionary Computation*, 19(5): 731-745, October 2015. - M. Omidvar, X. Li and K. Tang, “Designing Benchmark Problems for Large-Scale Continuous Optimization,”
*Information Sciences*, 316: 419-436, September 2015. - B. Li, J. Li, K. Tang and X. Yao, “Many-Objective Evolutionary Algorithms: A Survey,”
*ACM Computing Surveys*, 48(1), Article 13, 35 pages, September 2015. - P. Yang, K. Tang and X. Lu, “Improving Estimation of Distribution Algorithm on Multimodal Problems by Detecting Promising Areas,”
*IEEE Transactions on Cybernetics*, 45(8): 1438-1449, August 2015. - L. Wan, K. Tang, M. Li, Y. Zhong and A. K. Qin, “Collaborative Active and Semi-supervised Learning for Hyperspectral Remote Sensing Image Classification,”
*IEEE Transactions on Geoscience and Remote Sensing*, 53(5): 2384-2396, May 2015. - P. Wang, M. Emmerich, R. Li, K. Tang, T. Baeck and X. Yao, “Convex Hull-Based Multi-objective Genetic Programming for Maximizing Receiver Operating Characteristic Performance,”
*IEEE Transactions on Evolutionary Computation*, 19(2): 188-200, April 2015. - X. Yang, K. Tang and X. Yao, “A Learning-to-Rank Approach to Software Defect Prediction,”
*IEEE Transactions on Reliability*, 64(1): 234-246, March 2015. - L. Li and K. Tang, “History-Based Topological Speciation for Multimodal Optimization,”
*IEEE Transactions on Evolutionary Computation*, 19(1): 136-150, February 2015. - X. Lu, K. Tang, B. Sendhoff and X. Yao, “A New Self-adaptation Scheme for Differential Evolution,”
*Neurocomputing*, 146: 2-16, December 2014. - K. Tang, F. Peng, G. Chen and X. Yao, “Population-based Algorithm Portfolios with automated constituent algorithms selection,”
*Information Sciences*, 279: 94-104, September 2014. - T. Weise, R. Chiong, J. Lassig, K. Tang, S. Tsutsui, W. Chen, Z. Michalewicz and X. Yao, “Benchmarking Optimization Algorithms: An Open Source Framework for the Traveling Salesman Problem,”
*IEEE Computational Intelligence Magazine*, 9(3): 40-52, August 2014. (This paper was highlighted by the IEEE Computational Intelligence Magazine as “Publication Spotlight” in its August 2014 issue, Page 12.) - T. Weise, M. Wan, P. Wang, K. Tang, A. Devert and X. Yao, “Frequency Fitness Assignment,”
*IEEE Transactions on Evolutionary Computation*, 18(2): 226-243, April 2014. - X. Lu, K. Tang, B. Sendhoff and X. Yao, “A Review of Concurrent Optimization Methods,”
*International Journal of Bio-inspired Computation*, 6(1): 22-31, March 2014. - P. Wang, K. Tang, T. Weise, E. P. K. Tsang and X. Yao, “Multiobjective Genetic Programming for Maximizing ROC Performance,”
*Neurocomputing*, 125: 102-118, February 2014. - M. Lin, K. Tang and X. Yao, “Dynamic Sampling Approach to Training Neural Networks for Multiclass Imbalance Classification,”
*IEEE Transactions on Neural Networks and Learning Systems*, 24(4): 647-660, April 2013. - Y. Jin, K. Tang, X. Yu, B. Sendhoff and X. Yao, “A framework for finding robust optimal solutions over time,”
*Memetic Computing*, 5(1): 3-18, March 2013. - 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. - K. Cai, J. Zhang, C. Zhou, X. Cao and K. Tang, “Using computational intelligence for large scale air route networks design,”
*Applied Soft Computing*, 12(9): 2790-2800, September 2012. - X. Lu and K. Tang, “Classification- and Regression-Assisted Differential Evolution for Computationally Expensive Problems,”
*Journal of Computer Science and Technology*, 27(5): 1024- 1034, September 2012. - T. Weise, R. Chiong and K. Tang, “Evolutionary Optimization: Pitfalls and Booby Traps,”
*Journal of Computer Science and Technology*, 27(5): 907-936, September 2012. - R. Wang and K. Tang, “Feature Selection for MAUC Oriented Classification Systems,”
*Neurocomputing*, 89: 39-54, July 2012. - 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. - T. Weise and K. Tang, “Evolving Distributed Algorithms with Genetic Programming,”
*IEEE Transactions on Evolutionary Computation*, 16(2): 242-265, April 2012. - 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. - 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. - 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. - 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. - D. Liu, K. Tang, Z. Yang and D. Liu, “A Fiber Bragg Grating Sensor Network Using an Improved Differential Evolution Algorithm,”
*IEEE Photonics Technology Letters*, 23(19): 1385-1387, June 2011. - Y. Mei, K. Tang and X. Yao, “Decomposition-Based Memetic Algorithm for Multiobjective Capacitated Arc Routing Problem,”
*IEEE Transactions on Evolutionary Computation*, 15(2): 151-165, April 2011. - 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. - 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. - 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. - 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. - 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. - 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. - 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. - 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. - 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, March 2009. - 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, January 2009. - Z. Yang, K. Tang and X. Yao, “Large Scale Evolutionary Optimization Using Cooperative Coevolution,”
*Information Sciences*, 178(15): 2985-2999, August 2008. (According to ESI, it has been selected as the Highly Cited Papers in Computer Science for the past 11 years.) - 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. (This paper was highlighted by ScienceWatch.com as a “New Hot Paper”. The report of an online interview of the authors is available at: http://archive.sciencewatch.com/dr/nhp/2009/09marnhp/09marnhpRamET/) - E. K. Tang, P. N. Suganthan and X. Yao, “Gene Selection Algorithms for Microarray Data Based on Least Squares Support Vector Machine,”
*BMC-Bioinformatics*, 7:95, 27 February 2006. - E. K. Tang, P. N. Suganthan, X. Yao, “An Analysis of Diversity Measures,”
*Machine Learning*, 65: 247-271, October 2006. - E. K. Tang, P. N. Suganthan and X. Yao and A. K. Qin, “Linear Dimensionality Reduction Using Relevance Weighted LDA,”
*Pattern Recognition*, 38(4): 485-493, April 2005.

### Refereed Papers in Conference Proceedings:

- W. Hong, P. Yang, Y. Wang and K. Tang, “Multi-objective Magnitude-Based Pruning for Latency- Aware Deep Neural Network Compression,” in
*Proceedings of the 16th International Conference on Parallel Problem Solving from Nature (PPSN’20)*, Leiden, Netherlands, September 5-9, 2020, pp.470- 483. - S. Liu, K. Tang, Y. Lei and X. Yao, “On Performance Estimation in Automatic Algorithm Configuration,” in
*Proceedings of The 34th AAAI Conference on Artificial Intelligence (AAAI-2020)*, New York, USA, February 7-12, 2020. - L. Zhang,K. Tang and X. Yao, “Explicit Planning for Efficient Exploration in Reinforcement Learning,” In:
*Advances in Neural Information Processing Systems (NIPS’19)*,Vancouver,Canada, December 08-14, 2019, pp. 7488-7497. - Y. Lei, P. Yang, K. Tang and D. X. Zhou, “Optimal Stochastic and Online Learning with Individual Iterates,” In:
*Advances in Neural Information Processing Systems (NIPS’19)*,Vancouver, Canada, December 08-14, 2019, pp. 5416-5426. (Spotlight, 164 out of 6743 submissions) - D. Jiao, P. Yang, L. Fu, L. Ke and K. Tang, “Optimal Energy-Delay Scheduling for Energy Harvesting WSNs via Negatively Correlated Search,” in
*Proceedings of ICC 2019-2019 IEEE International Conference on Communications (ICC)*, Shanghai, China, May 20-24, 2019. - S. Liu, K. Tang and X. Yao, “Automatic Construction of Parallel Portfolios via Explicit Instance Grouping,” in
*Proceedings of The 33th AAAI Conference on Artificial Intelligence (AAAI-2019)*, Honolulu, Hawaii, USA, January 27 – February 1, 2019, pp. 1560-1567. - C. Feng, C. Qian and K. Tang, “Unsupervised Feature Selection by Pareto Optimization,” in
*Proceedings of The 33th AAAI Conference on Artificial Intelligence (AAAI-2019)*, Honolulu, Hawaii, USA, January 27 – February 1, 2019, pp. 3534-3541. - Y. Lei and K. Tang, “Stochastic Composite Mirror Descent: Optimal Bounds with High Probabilities,” In:
*Advances in Neural Information Processing Systems 30 (NIPS’18)*, Montréal, Canada, December 2-8, 2018, pp. 1526-1536. - C. Bian, C. Qian and K. Tang, “A General Approach to Running Time Analysis of Multi-objective Evolutionary Algorithms,” in
*Proceedings of the 27th International Joint Conference on Artificial Intelligence (IJCAI’18)*, Stockholm, Sweden, July 13-19, 2018, pp. 1405-1411. - G.-Y. Li, C. Qian, C.-H. Jiang, X. Lu and Ke Tang, “Optimization based Layer-wise Magnitude-based Pruning for DNN Compression,” in
*Proceedings of the 27th International Joint Conference on Artificial Intelligence (IJCAI’18)*, Stockholm, Sweden, July 13-19, 2018, pp. 2383-2389. - C. Qian, Y. Yu and K. Tang, “Approximation Guarantees of Stochastic Greedy Algorithms for Subset Selection,” in Proceedings of the 27th International Joint Conference on Artificial Intelligence (IJCAI’18), Stockholm, Sweden, July 13-19, 2018, pp. 1478-1484.
- Y.-W. Lei, S.-B. Lin and K. Tang, “Generalization Bounds for Regularized Pairwise Learning,” in
*Proceedings of the 27th International Joint Conference on Artificial Intelligence (IJCAI’18)*, Stockholm, Sweden, July 13-19, 2018, pp. 2376-2382. - C.-H. Jiang, G.-Y. Li, C. Qian and K. Tang, “Efficient DNN Neuron Pruning by Minimizing Layer- wise Nonlinear Reconstruction Error,” in
*Proceedings of the 27th International Joint Conference on Artificial Intelligence (IJCAI’18)*, Stockholm, Sweden, July 13-19, 2018, pp. 2298-2304. - C. Qian, C. Feng and K. Tang, “Sequence Selection by Pareto Optimization,” in
*Proceedings of the 27th International Joint Conference on Artificial Intelligence (IJCAI’18)*, Stockholm, Sweden, July 13- 19, 2018, pp. 1485-1491. - C. Qian, G.-Y. Li, C. Feng and K. Tang, “Distributed Pareto Optimization for Subset Selection,” in
*Proceedings of the 27th International Joint Conference on Artificial Intelligence (IJCAI’18)*, Stockholm, Sweden, July 13-19, 2018, pp. 1492-1498. - L. Zhang, K. Tang and X. Yao, “Log-normality and Skewness of Estimated State/Action Values in Reinforcement Learning,” In:
*Advances in Neural Information Processing Systems 30 (NIPS’17)*, Long Beach, CA, December 4-9, 2017, pp.1802–1812. - C. Qian, J. Shi, Y. Yu, K. Tang and Z.-H. Zhou, “Subset Selection under Noise,” In:
*Advances in Neural Information Processing Systems 30 (NIPS’17)*, Long Beach, CA, December 4-9, 2017, pp.3563- 3573. - C. Qian, J. Shi, Y. Yu and K. Tang, “On Subset Selection with General Cost Constraints,” in
*Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI’17)*, Melbourne, Australia, 2017, pp.2613-2619. - C. Qian, J. Shi, Y. Yu, K. Tang and Z.-H. Zhou, “Optimizing Ratio of Monotone Set Functions,” in
*Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI’17)*, Melbourne, Australia, 2017, pp.2606-2612. - C. Qian, C. Bian, W. Jiang and K. Tang, “Running Time Analysis of the (1+1)-EA for OneMax and LeadingOnes under Bit-wise Noise,” in
*Proceedings of the 19th ACM Conference on Genetic and Evolutionary Computation (GECCO’17)*, Berlin, Germany, 2017, pp.1399-1406. - C. Qian, K. Tang and Z.-H. Zhou, “Selection Hyper-heuristics Can Provably be Helpful in Evolutionary Multi-objective Optimization,” in
*Proceedings of the 14th International Conference on Parallel Problem Solving from Nature (PPSN’16)*, Edinburgh, Scotland, September 17-21, 2016, pp.835-846. - J. Fu, J. Zhong, Y. Liu, Z. Wang and K. Tang, “A Non-parametric Approach for Learning from Crowds,” in
*Proceedings of the 2016 International Joint Conference on Neural Networks (IJCNN’16)*, Vancouver, Canada, July 24-29, 2016, pp. 2228-2235. - C. Jiang, G. Li, J. Liu, Y. Liu and K. Tang, “A Trajectory-based Approach for Object Detection from Video,” in
*Proceedings of the 2016 International Joint Conference on Neural Networks (IJCNN’16)*, Vancouver, Canada, July 24-29, 2016, pp. 2887-2893. - P. Yang, G. Lu, K. Tang and X. Yao, “A Multi-Modal Optimization Approach to Single Path Planning for Unmanned Aerial Vehicle,” in
*Proceedings of the 2016 IEEE Congress on Evolutionary Computation (CEC’16)*, Vancouver, Canada, July 24-29, 2016, pp. 1735-1742. - B. Li, C. Qian, J. Li, K. Tang and X. Yao, “Search Based Recommender System Using Many- Objective Evolutionary Algorithm,” in
*Proceedings of the 2016 IEEE Congress on Evolutionary Computation (CEC’16)*, Vancouver, Canada, July 24-29, 2016, pp. 120-126. - C. Qian, J.-C. Shi, Y. Yu, K. Tang and Z.-H. Zhou, “Parallel Pareto Optimization for Subset Selection,” in
*Proceedings of the 25th International Joint Conference on Artificial Intelligence (IJCAI’16)*, New York, NY, July 9-15, 2016, pp.1939-1945. - L. Zhang, K. Tang and X. Yao, “Increasingly Cautious Optimism for Practical PAC-MDP Exploration,” in
*Proceedings of the 24th International Joint Conference on Artificial Intelligence (IJCAI’15),*Buenos Aires, Argentina, July 25-31, 2015, pp. 4033-4040. - J. Zhong, K. Tang and Z.-H. Zhou, “Active Learning from Crowds with Unsure Option,” in
*Proceedings of the 24th International Joint Conference on Artificial Intelligence (IJCAI’15),*Buenos Aires, Argentina, July 25-31, 2015, pp. 1061-1067. - Y. Wu, Y. Sun, X. Liang, K. Tang and Z. Cai, “Evolutionary Semi-Supervised Ordinal Regression Using Weighted Kernel Fisher Discriminant Analysis,” in
*Proceedings of the 2015 IEEE Congress on Evolutionary Computation (CEC2015)*, Sendai, Japan, May 25-28, 2015, pp. 3279-3286. - S. Liu, Y. Wei, K. Tang, A. K. Qin and X. Yao, “QoS-aware Long-term Based Service Composition in Cloud Computing,” in
*Proceedings of the 2015 IEEE Congress on Evolutionary Computation (CEC2015)*, Sendai, Japan, May 25-28, 2015, pp. 3362-3369. - W. Hong, G. Lu, P. Yang, Y. Wang and K. Tang, “A New Evolutionary Multi-objective Algorithm for Convex Hull Maximization,” in
*Proceedings of the 2015 IEEE Congress on Evolutionary Computation (CEC2015)*, Sendai, Japan, May 25-28, 2015, pp. 931-938. - X. Lu, S. Menzel, K. Tang and X. Yao, “The Performance Effects of Interaction Frequency in Parallel Cooperative Coevolution,” in
*Proceedings of the 10th International Conference on Simulated Evolution And Learning (SEAL 2014)*, December 15-18, 2014,*Lecture Notes in Computer Science*Volume 8886, 2014, pp.82-93, Springer-Verlag, Berlin. - Z. Miao, J. Wang, A. Zhou and K. Tang, “Regularized Boost for Semi-supervised Ranking,” in
*Proceedings of the 18th Asia Pacific Symposium on Intelligent and Evolutionary Systems (IES2014),*November 10-12, 2014, Singapore,*Proceedings in Adaptation, Learning and Optimization Volume 1, 2015,*pp. 643-651*.* - P. Yang, K. Tang, L. Li and A. K. Qin, “Evolutionary Robust Optimization with Multiple Solutions,” in
*Proceedings of the 18th Asia Pacific Symposium on Intelligent and Evolutionary Systems (IES2014),*November 10-12, 2014, Singapore,*Proceedings in Adaptation, Learning and Optimization Volume 1, 2015,*pp. 611-625*.* - T. Chen, Q. Guo, K. Tang, O. Temam, Z. Xu, Z.-H. Zhou, and Y. Chen, “ArchRanker: A ranking approach to design space exploration,” in
*Proceedings of the 41st International Symposium on Computer Architecture (ISCA’14)*, Minneapolis, MN, 2014, pp.85-96. - H. Fu, P. R. Lewis, B. Sendhoff, K. Tang, and X. Yao, “What Are Dynamic Optimization Problems?” in
*Proceedings of the 2014 IEEE Congress on Evolutionary Computation (CEC2014)*, Beijing, China, July 6-11, 2014, pp. 1550-1557. - J. Zhong, K. Tang and A. K. Qin, “Finding Convex Hull Vertices in Metric Space,” in
*Proceedings of the 2014 International Joint Conference on Neural Networks (IJCNN2014)*, Beijing, China, July 6-11, 2014, pp. 1587-1592. - P. Yang, K. Tang and J. A. Lozano, “Estimation of Distribution Algorithms based Unmanned Aerial Vehicle Path Planner Using a New Coordinate System,” in
*Proceedings of the 2014 IEEE Congress on Evolutionary Computation (CEC2014)*, Beijing, China, July 6-11, 2014, pp. 1469-1476. - T. Weise, M. Wan, K. Tang and X. Yao, “Evolving exact integer algorithms with Genetic Programming,” in
*Proceedings of the 2014 IEEE Congress on Evolutionary Computation (CEC2014)*, Beijing, China, July 6-11, 2014, pp.1816-1823. - B. Li, J. Li, K. Tang and X. Yao, “An Improved Two Archive Algorithm for Many-Objective Optimization,” in
*Proceedings of the 2014 IEEE Congress on Evolutionary Computation (CEC2014)*, Beijing, China, July 6-11, 2014, pp. 2869-2876. - Z. Miao and K. Tang, “Semi-supervised Ranking via List-wise Approach,” in
*Proceedings of the 14th International Conference on Intelligent Data Engineering and Automated Learning (IDEAL’13)*, Hefei, China, October 20-23, 2013, pp. 376-383, Lecture Notes in Computer Science, Volume 8206, Springer- Verlag Berlin Heidelberg, Germany. - L. Zhuang, K. Tang and Y. Jin, “Metamodel Assisted Mixed-Integer Evolution Strategies Based on Kendall Rank Correlation Coefficient,” in
*Proceedings of the 14th International Conference on Intelligent Data Engineering and Automated Learning (IDEAL’13)*, Hefei, China, October 20-23, 2013, pp. 366-375, Lecture Notes in Computer Science, Volume 8206, Springer-Verlag Berlin Heidelberg, Germany. - L. Wan, K. Tang and R. Wang, “Gradient Boosting-based Negative Correlation Learning,” in
*Proceedings of the 14th International Conference on Intelligent Data Engineering and Automated Learning (IDEAL’13)*, Hefei, China, October 20-23, 2013, pp. 358-365, Lecture Notes in Computer Science, Volume 8206, Springer-Verlag Berlin Heidelberg, Germany. - J. Liu and K. Tang, “Scaling Up Covariance Matrix Adaptation Evolution Strategy using Cooperative Coevolution,” in
- W. Chen and K. Tang, “Impact of problem decomposition on Cooperative Coevolution,” in
*Proceedings of 2013 IEEE Congress on Evolutionary Computation (CEC’13)*, Cancun, Mexico, June 20-23, 2013, pp. 733-740. - M. Li, R. Wang and K. Tang, “Combining Semi-Supervised and Active Learning for Hyperspectral Image Classification,” in
*Proceedings of 2013 IEEE Symposium Series on Computational Intelligence (SSCI’13)*, Singapore, April 16-19, 2013, pp. 89-94. - J. Wang, K. Tang and X. Yao, “A Memetic Algorithm for Uncertain Capacitated Arc Routing Problems,” in
*Proceedings of 2013 IEEE Symposium Series on Computational Intelligence (SSCI’13)*, Singapore, April 16-19, 2013, pp. 80-87. - R. Wang, W. Dong, Y. Wang, K. Tang and X. Yao, “Pipe Failure Prediction: A Data Mining Method,” in
*Proceedings of the 29th IEEE International Conference on Data Engineering (ICDE’13)*, Brisbane, Australia, April 8-11, 2013, pp. 1208-1218. - Q. Huang, G. Jia, T. White, M. Musolesi, N. Turan, K. Tang, S. He, J. K. Heath and X. Yao, “Community Detection Using Cooperative Co-evolutionary Differential Evolution,” in
*Proceedings of the 12th International Conference on Parallel Problem Solving From Nature*. Taormina, Italy, September 1-5, 2012. - T. Weise, A. Devert and K. Tang, “A Developmental Solution to (Dynamic) Capacitated Arc Routing Problems using Genetic Programming,” in
*Proceedings of the Genetic and Evolutionary Computation Conference (GECCO’12)*, Philadelphia, PA, USA, July 7–11, 2012, pp. 831-838. - H. Fu, B. Sendhoff, K. Tang, and Xin Yao, “Characterizing environmental changes in Robust Optimization Over Time,” in
*Proceedings of the IEEE Congress on Evolutionary Computation (CEC2012)*, Brisbane, Queensland, Australia, 10-15 June 2012, pp. 1-8. - L. Chen, H. Chen and K. Tang, “Semi-supervised Learning with Extremely Sparse Labeled Data on Multiple Semi-supervised Assumptions,” in
*Proceedings of The 2011 International Conference of Soft Computing and Pattern Recognition (SoCPaR)*, Dalian, China, 14-16 October 2011, pp. 242-247. - K. Tang, R. Wang and T. Chen, “Towards Maximizing The Area Under The ROC Curve For Multi- class Classification Problems,” in
*Proceedings of The 25th AAAI Conference on Artificial Intelligence (AAAI 2011)*, San Francisco, USA, 7-11 August 2011, pp. 483-488. - X. Lu, K. Tang, and X. Yao, “Classification-Assisted Differential Evolution for Computationally Expensive Problems,” in
*Proceedings of the 2011 IEEE Congress on Evolutionary Computation (CEC2011)*, New Orleans, USA, 5-8 June 2011, pp. 1986-1993. - P. Wang, K. Tang, E.P.K. Tsang and X. Yao, “A Memetic Genetic Programming with Decision Tree- based Local Search for Classification Problems,” in
*Proceedings of the 2011 IEEE Congress on Evolutionary Computation (CEC2011)*, New Orleans, USA, 5-8 June 2011, pp. 916-923. - X. Fan, K. Tang and T. Weise, “Margin-Based Over-Sampling Method for Learning From Imbalanced Datasets,” in
*Proceedings of the 15th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD2011)*, Shenzhen, China, 24-27 May 2011, pp. 309-320. - M. Wan, T. Weise and K. Tang, “Novel Loop Structures and the Evolution of Mathematical Algorithms,” in
*Proceedings of the 14th European Conference on Genetic Programming (EuroGP’11)*, Torino, Italy, 27-29 April 2011, pp. 300-309, Lecture Notes in Computer Science, Volume 6621, Springer-Verlag, Berlin, Germany. - W. Chen, T. Weise, Z. Yang and K. Tang, “Large-Scale Global Optimization using Cooperative Coevolution with Variable Interaction Learning,” in
*Proceedings of the 11th International Conference on Parallel Problem Solving From Nature (PPSN)*, Kraków, Poland, September 11–15, 2010, pp. 300– 309, Lecture Notes in Computer Science, Volume 6239, Part II, Springer-Verlag, Berlin, Germany. - X. Fan and K. Tang, “Enhanced Maximum AUC Linear Classifier,” in
*Proceedings of The 7th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD2010)*, Yantai, China, 10- 12 August 2010, vol. 4, pp. 1540-1544. - P. Wang, E. P. K. Tsang, T. Weise, K. Tang and X. Yao, “Using GP to Evolve Decision Rules for Classification in Financial Data Sets,” in
*Proceedings of the 9th IEEE International Conference on Cognitive Informatics (ICCI 2010)*, Beijing, China, 7-9 July 2010, pp. 722-727. - T. Weise, L. Niu and K. Tang, “AOAB – Automated Optimization Algorithm Benchmarking,” in
*Proceedings of the 2010 Genetic and Evolutionary Computation Conference (GECCO-2010)*, Portland, USA, 7-11 July 2010, pp. 1479-1486. - X. Lu, K. Tang and X. Yao, “Evolving Neural Networks with Maximum AUC for Imbalanced Data Classification,” in
*Proceedings of the 5th International Conference on Hybrid Artificial Intelligence Systems (HAIS2010)*, San Sebastián, Spain, 23-25 June 2010, Lecture Notes in Computer Science, Volume 6076, Springer-Verlag, Berlin pp. 335-342. - X. Yu, Y. Jin, K. Tang and X. Yao, “Robust Optimization over Time – A New Perspective on Dynamic Optimization Problems,” in
*Proceedings of the 2010 IEEE Congress on Evolutionary Computation (CEC2010)*, Barcelona, Spain, 18-23 July 2010, pp. 3998-4003. - Y. Mei, K. Tang and X. Yao, “Capacitated Arc Routing Problem in Uncertain Environments,” in
*Proceedings of the 2010 IEEE Congress on Evolutionary Computation (CEC2010)*, Barcelona, Spain, 18-23 July 2010, pp. 1400-1407. - H. Fu, Y. Mei, K. Tang and Y. Zhu, “Memetic Algorithm with Heuristic Candidate List Strategy for Capacitated Arc Routing Problem,” in
*Proceedings of the 2010 IEEE Congress on Evolutionary Computation (CEC2010)*, Barcelona, Spain, 18-23 July 2010, pp. 3229-3236. - R. Wang and K. Tang, “Feature Selection for Maximizing the Area Under the ROC Curve,” in
*Proceedings of the 2009 International Conference on Data Mining – Workshops*, Miami, USA, 6-9 December 2009, pp. 400-405. - X. Yang, K. Tang and X. Yao, “The Minimum Redundancy – Maximum Relevance Approach to Building Sparse Support Vector Machines,” in
*Proceedings of the 10th International Conference on Intelligent Data Engineering and Automated Learning (IDEAL2009),*Lecture Notes in Computer Science, Volume 5788, Springer-Verlag, Berlin, September 2009, pp. 184-190. - S. Wang, K. Tang and X. Yao, “Diversity Exploration and Negative Correlation Learning on Imbalanced Data Sets,” in
*Proceedings of the 2009 International Joint Conference on Neural Networks (IJCNN2009)*, Atlanta, USA, 14-19 June 2009, pp. 3259-3266. - T. Chen, K. Tang, G. Chen and X. Yao, “Rigorous Time Complexity Analysis of Univariate Marginal Distribution Algorithm with Margins,” in
*Proceedings of the 2009 IEEE Congress on Evolutionary Computation (CEC2009)*, Trondheim, Norway, 18-21 May 2009, pp. 2157-2164. - 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, 18-21 May 2009, pp. 1470-1477. - Y. Chen, K. Tang and T. Chen, “A Stochastic Method for Controlling the Scaling Parameters of Cauchy Mutation in Fast Evolutionary Programming,” in
*Proceedings of the 2009 IEEE Congress on Evolutionary Computation (CEC2009)*, Trondheim, Norway, 18-21 May 2009, pp. 1101-1107. - Y. Mei, K. Tang and X. Yao, “Improved Memetic Algorithm for Capacitated Arc Routing Problem,” in
*Proceedings of the 2009 IEEE Congress on Evolutionary Computation (CEC2009)*, Trondheim, Norway, 18-21 May 2009, pp. 1699-1706. - F. Peng, K. Tang, G. Chen and X. Yao, “Multi-start JADE with knowledge transfer for numerical optimization,” in
*Proceedings of the 2009 IEEE Congress on Evolutionary Computation (CEC2009)*, Trondheim, Norway, 18-21 May 2009, pp. 1889-1895. - Z. Wang, T. Chen, K. Tang and X. Yao, “A Multi-objective Approach to Redundancy Allocation Problem in Parallel-series Systems,” in
*Proceedings of the 2009 IEEE Congress on Evolutionary Computation (CEC2009)*, Trondheim, Norway, 18-21 May 2009, pp. 582-589. - Z. Yang, J. Zhang, K. Tang, X. Yao and A. Sanderson, “An Adaptive Coevolutionary Differential Evolution Algorithm for Large-scale Optimization,” in
*Proceedings of the 2009 IEEE Congress on Evolutionary Computation (CEC2009)*, Trondheim, Norway, 18-21 May 2009, pp. 102-109. - Z. Wang, Z. Yang, K. Tang, and X. Yao, “Adaptive Differential Evolution for Multi-objective Optimization,” in
*Proceedings of the 20th International Conference on Multiple Criteria Decision Making (MCDM’09)*, Chengdu, China, 2009, pp. 9-16. - M. Lin, K. Tang and X. Yao, “Selective Negative Correlation Learning Algorithm for Incremental Learning,” in
*Proceedings of the 2008 International Joint Conference on Neural Networks (IJCNN2008)*, Hong Kong, 2008, pp. 2526-2531. - X. Yu, K. Tang and X. Yao, “An Immigrants Scheme Based on Environmental Information for Genetic Algorithms in Changing Environments,” in
*Proceedings of the 2008 IEEE Congress on Evolutionary Computation (CEC2008)*, Hong Kong, 2008, pp. 1141-1147. - Z. Wang, K. Tang and X. Yao, “A Multi-objective Approach to Testing Resource Allocation in Modular Software Systems,” in
*Proceedings of the 2008 IEEE Congress on Evolutionary Computation (CEC2008)*, Hong Kong, 2008, pp. 1148-1153. - 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)*, Hong Kong, 2008, pp. 1663-1670. - 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)*, Hong Kong, 2008, pp. 1110-1116. - K. Tang, Z. Wang, X. Cao and J. Zhang, “A Multi-objective Evolutionary Approach to Aircraft Landing Scheduling Problems,” in
*Proceedings of the 2008 IEEE Congress on Evolutionary Computation (CEC2008)*, Hong Kong, 2008, pp. 3651-3657. - T. Chen, K. Tang, G. Chen and X. Yao, “On the Analysis of Average Time Complexity of Estimation of Distribution Algorithms,” in
*Proceedings of 2007 IEEE Congress on Evolutionary Computation (CEC2007)*, Singapore, 2007, pp. 453-460. - Z. Yang, K. Tang and X. Yao, “Differential Evolution for High-Dimensional Function Optimization,” in
*Proceedings of 2007 IEEE Congress on Evolutionary Computation (CEC2007)*, Singapore, 2007, pp. 3523-3530. - A. Ashish, G. Fogel, E. K. Tang and P. N. Suganthan, “Feature Selection Approach for Quantitative Prediction of Transcriptional Activities,” in
*Proceedings of the 2006 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology*2006. - E. K. Tang, P. N. Suganthan and 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 (CIBCB)*, San Diego, USA, November 2005, pp. 9-17. - E. K. Tang, P. N. Suganthan and X. Yao, “Nonlinear Feature Extraction Using Evolutionary Algorithm,” in
*Proceedings of the 11th Int. Conference on Neural Information Processing*, Calcutta, India, November 2004, LNCS Vol. 3316, pp. 1014-1019. - E. K. Tang, P. N. Suganthan and X. Yao, “Generalized LDA Using Relevance Weighting and Evolution Strategy,” in
*Proceedings of the 2004 Congress on Evolutionary Computation*, Portland, USA, June 2004, Vol. 2, pp. 2230-2234.