Prof. Xin Xu

National University of Defense Technology, China

Email: xinxu@nudt.edu.cn

Qualifications:

2004, Post-doctor, National University of Defense Technology, China

1996, Ph.D., Control Science and Engineering, National University of Defense Technology, China

1992, B.Sc., Electrical Engineering, National University of Defense Technology, China

Selected Publications:

1. Xin Xu, Reinforcement Learning and Approximate Dynamic Programming, Science Press, 2010, Bejing, China.
2. Xin Xu, Machine Learning for Sequential Behavior Modeling and Prediction, In: Abdelhamid Mellouk and Abdennacer Chebira,ed. Machine Learning, 2009, I-Tech, Vienna, Austria.
3. Xin Xu, Reinforcement learning and neuro-dynamic programming, In: Dewen Hu, et al., ed. Neural Networks for Adaptive Control, Press of NUDT, 2007, Changsha, China.
4. Xin Xu, Dewen Hu, Xicheng Lu. Kernel-based least squares policy iteration for reinforcement learning. IEEE Transactions on Neural Networks, 2007, 18(4) 973-992.
5. Xin Xu, Chunming Liu, Simon Yang, Dewen Hu. Hierarchial Approximate Policy Iteration with Binary-tree State Space Decomposition, submiited to IEEE Transactions on Neural Networks, under review.
6. Xin Xu, H.G. He, D.W. Hu. Efficient reinforcement learning using recursive least-squares methods. Journal of Artificial Intelligence Research, 2002,16: 259-292.
7. Xin Xu. Sequential Anomaly Detection Based on Temporal-Difference Learning: Principles, Models and Case Studies. Applied Soft Computing, 2010, 10(3): 859-867.
8. Junping Zhang, Feiyue Wang, Kungfeng Wang, Weihua Lin, Xin Xu, Cheng Chen. Data-Driven Intelligent Transportation Systems: A Survey. submitted to IEEE Transactions on Intelligent Transportation Systems, under review.
9. Xin Xu, Chunming Liu, Dewen Hu. Continuous-Action Reinforcement Learning with Fast Policy Search and Adaptive Basis Function Selection. Soft Computing, Published online: 28 March 2010.
10. Wei Wang, Xin Xu, Yan Li, Triple RRTs: An effective method for path planning in narrow passage, Advanced Robotics, 2010, vol. 24, no. 7, pp. 943-962.
11. Xin Xu. Editorial: Special section on reinforcement learning and approximate dynamic programming. Journal of Intelligent Learning Systems and Applications, 2010, 2(2): 55-56.
12. Xin Xu, Rob Law, Tao Wu. Support Vector Machines with Manifold Learning and Probabilistic Space Projection for Tourist Expenditure Analysis. International Journal of Computational Intelligence Systems, 2009, 2(1): 17 -26.
13. Xin Xu, et al. Kernel Least-Squares Temporal Difference Learning. International Journal of Information Technology, Institute of Singapore (ICIS), 2005, 11(9): 54-63.
14. Xin Xu. Adaptive Intrusion Detection Based on Machine Learning: Feature Extraction, Classifier Construction and Sequential Pattern Prediction. International Journal of Web Service Practice, 2006, 2(1-2):49-58.
15. Xin Xu. Intrusion detection based on dynamic behavior modeling: reinforcement learning versus Hidden Markov Models. International Journal of Computational Intelligence Theory and Practice, 2007, 2(1): 57-66.
16. Gang wang, Xin Xu, Dewen Hu, et al. Uniqueness of maximum non-Gaussianity estimation: a revisit from the perspective of contrained cost-function optimization. International Journal of Intelligent Computing and Applications, 2008, 1(1):53-69.
17. Refereed Conference Papers
18. Xin Xu, Hongyu Zhang, Bin Dai, Han-gen He: Self-learning path-tracking control of autonomous vehicles using kernel-based approximate dynamic programming. Proc. of International Joint Conference on Neural Networks, 2008: 2182-2189
19. Xin Xu, Rob Law, Tao Wu: Classification of Business Travelers Using SVMs Combined with Kernel Principal Component Analysis. Lecture Notes in Artificial Intelligence, Proc. of ADMA 2007, LNCS: 524-532
20. Xin Xu, Yirong Luo: A Kernel-Based Reinforcement Learning Approach to Dynamic Behavior Modeling of Intrusion Detection. Lecture Notes in Computer Science,Proc. of ISNN (1) 2007: 455-464
21. Xin Xu, Yongqiang Sun, Zunguo Huang: Defending DDoS Attacks Using Hidden Markov Models and Cooperative Reinforcement Learning. Lecture Notes in Computer Science,Proc. of PAISI 2007: 196-207
22. Wei Chen, Xuening Wang, Tao Wu, Xin Xu: Visual Protractor Based Localization Algorithm for Mobile Robot. Proc. of ISDA (3) 2006: 67-71
23. Gang Wang, Xin Xu, Dewen Hu: Local Stability Analysis of Maximum Nongaussianity Estimation in Independent Component Analysis. Lecture Notes in Computer Science, Proc. of ISNN (1) 2006: 1133-1139
24. Xin Xu, Xuening Wang. An adaptive network intrusion detection method based on PCA and support vector machines. Lecture Notes in Artificial Intelligence, ADMA 2005: 696-703
25. Xin Xu. A sparse kernel-based least-squares temporal difference algorithm for reinforcement learning. Lecture Notes in Computer Science, ICNC (1) 2006: 47-56
26. Xin Xu, et al. A reinforcement learning approach for host-based intrusion detection using sequences of system calls. Lecture Notes in Computer Science, ICIC (1) 2005: 995-1003
27. Xin Xu, Xuening Wang, Dewen Hu. Mobile robot path-tracking using an adaptive critic learning PD controller. Lecture Notes in Computer Science, ISNN(2), 2004: 25-34
28. Xin Xu, et al. Text Categorization Using SVMs with Rocchio Ensemble for Internet Information Classification. Lecture Notes in Computer Science, ICCNMC, 2005, LNCS 3619, pp. 1022-1031.
29. Xin Xu, et al. Autonomic Computing for Defense-in-Depth Information Assurance: Architecture and A Case Study, Lecture Notes in Computer Science, GCC, 2004, LNCS 3252, pp: 414-421.
30. Xin Xu, et al. A Self-Learning Reactive Navigation Method for Mobile Robots. Proceedings of IEEE Int. Conference on Machine Learning and Cybemetics, 2003.
31. Gang Wang, Xin Xu, Global Convergence of FastICA: Theoretical Analysis and Practical Considerations. Lecture Notes in Computer Science, ICNC, 2005, 700-705.
32. Gang Wang, Xin Xu, Self-Adaptive FastICA Based on Generalized Gaussian Model. Lecture Notes in Computer Science, ISNN, 2005, 961-966.
33. Xin Xu, et al. Residual-gradient-based neural reinforcement learning for the optimal control of an acrobat. Proceedings of the 2002 IEEE International Symposium on Intelligent Control, Canada, 758-763.

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