My research in the general field of Artificial Intelligence (AI) and Machine Learning (ML) includes several thrusts. The first thrust focuses on optimal sampling algorithms for sequentially learning information about different actions/decisions, i.e., best arm identification in multi-armed bandit problems, which may contribute to the improved computational efficiency of Monte Carlo tree search and reinforcement learning. I also work on supervised machine learning (neural networks, Gaussian process regression) and unsupervised machine learning (clustering). Another thrust is swarm intelligence, which has important applications in autonomous systems control and optimization. I am also developing research interests in the testing and certification of AI/ML systems using techniques from design of experiment, statistical ranking and selection, importance sampling, and stochastic optimization.


Monte Carlo Tree Search
•  Li, Y., Fu, M. C., and Xu, J., 2021. An Optimal Computing Budget Allocation Tree Policy for Monte Carlo Tree Search. Accepted, IEEE Transactions on Automatic Control. Download
•  Li, Y., Fu, M. and Xu, J., 2019. Monte Carlo tree search with optimal computing budget allocation. In 2019 IEEE 58th Conference on Decision and Control (CDC) (pp. 6332-6337). IEEE.


Optimal sampling for best arm identification
•  Wang, T., J. Xu, J.-Q. Hu, and C.-H. Chen. 2021. Optimal Computing Budget Allocation for Regression with Gradient Information. Accepted, Automatica.
•  Peng, Y., Xu, J., Lee, L.H., Hu, J. and Chen, C.H., 2019. Efficient Simulation Sampling Allocation Using Multi-fidelity Models. IEEE Transactions on Automatic Control, 64(8), pp.3156-3169 Download
•  Zhang, S., L.-H. Lee, E.-P. Chew, J. Xu, C.-H. Chen. 2016. A simulation budget allocation procedure for enhancing the efficiency of optimal subset selection. IEEE Transactions on Automatic Control 61(1) 62-75. Download
•  Brantley, M.W., Lee, L.-H., Chen, C.-H., and Xu, J. 2014. An Efficient Simulation Budget Allocation Method Incorporating Regression for Partitioned Domains. Automatica, 50: 1391-1400. Download


Reinforcement Learning
•  Wang, H., Shen, H., Liu, Q., Zheng, K. and Xu, J., 2020, August. A Reinforcement Learning Based System for Minimizing Cloud Storage Service Cost. In 49th International Conference on Parallel Processing-ICPP (pp. 1-10).
•  Liu, L., Xu, J., Yu, H. and Wei, X., 2015, June. Joint admission control and provisioning for virtual machines. In 2015 IEEE International Conference on Communications (ICC) (pp. 332-337). IEEE.


Predictive simulation learning
•  Goodwin, T., Xu, J., Chen, C.-H., and Celik, N. Efficient Simulation Optimization with Simulation Learning. In 2021 IEEE 17th International Conference on Automation Science and Engineering (CASE). IEEE.
•  Pedrielli, G., Selcuk Candan, K., Chen, X., Mathesen, L., Inanalouganji, A., Xu, J., Chen, C.H. and Lee, L.H., 2019. Generalized Ordinal Learning Framework (GOLF) for Decision Making with Future Simulated Data. Asia-Pacific Journal of Operational Research, 36(06), p.1940011. Download


Neural Networks
•  Xu, R., Xu, J., Wunsch, D.C. 2009. MicroRNA expression profile based cancer classification using Default ARTMAP, Neural Networks 22(5) 774-780. Download
•  Xu, R., Xu, J., Wunsch, D.C. 2009. Using default ARTMAP for cancer classification with MicroRNA expression signatures, International Joint Conference on Neural Networks, Atlanta, GA.


Clustering
•  Koohi, A., Homayoun, H., Xu, J. and Orooji, M., 2016, February. Co-clustering of diseases, genes, and drugs for identification of their related gene modules. In 2016 Eighth International Conference on Advanced Computational Intelligence (ICACI) (pp. 407-411). IEEE.
•  Xu, R., Xu, J., and Wunsch, D.C. 2012. A Comparison Study of Validity Indices on Swarm Intelligence-Based Clustering. IEEE Transactions on Systems, Man and Cybernetics - Part B, 42:1243 - 1256. Download
•  Xu, R., Xu, J., Wunsch, D.C. 2010. Clustering with Differential Evolution Particle Swarm Optimization. IEEE World Congress on Computational Intelligence, Barcelona, Spain. Best Overall Paper Award.


Swarm Intelligence
•  Zhang, S., J. Xu, L.-H. Lee, E.-P. Chew, E.-P. Wong, C.-H. Chen. 2017. Optimal Computing Budget Allocation for Particle Swarm Optimization in Stochastic Optimization. IEEE Transactions on Evolutionary Computation, 21(2), 206-219. Download
•  Taghiyeh, S., J. Xu. 2016. A new particle swarm optimization algorithm for noisy optimization. Swarm Intelligence, 10(3), 161-192. Download