Guangxin Jiang, Michael C. Fu. Technical Note-On estimating quantile sensitivities via infinitesimal perturbation analysis, Operations Research, 2015, 63(2): 435-441. Paper.pdf

Guangxin Jiang*, Chenglong Xu, Michael C. Fu. On sample average approximation algorithms for determining the optimal importance sampling parameters in pricing financial derivatives on Levy processes, Operations Research Letters, 2016, 44(1): 44-49. Paper.pdf

Guangxin Jiang, Michael C. Fu. Quantile sensitivity estimation for dependent sequences, Journal of Applied Probability, 2016, 53(3): 715-732. Paper.pdf

L. Jeff Hong*, Guangxin Jiang. Gradient and Hessian of joint probability function with applications on chance constrained programs. Journal of the Operations Research Society of China, 2017, 5(3): 431-455. Paper.pdf

Guangxin Jiang, Michael C. Fu*. Importance splitting for finite-time rare event simulation, IEEE Transactions on Automatic Control, 2018, 63(6): 1760-1767. Paper.pdf

Xin Yun, L. Jeff Hong, Guangxin Jiang*, Shouyang Wang. On Gamma estimation via matrix kriging. Naval Research Logistics, 2019, 66(5): 393-410. Paper.pdf

L. Jeff Hong, Guangxin Jiang*. Offline simulation online application: A new framework of simulation-based decision making. Asia-Pacific Journal of Operational Research, 2019, 36(6): 1940015. Paper.pdf

Guangxin Jiang, L. Jeff Hong, Barry L. Nelson. Online risk monitoring using offline simulation. INFORMS Journal on Computing, 2020, 32(2): 356-375. Paper.pdf

Zini Wang, Guangxin Jiang*, Qiang Ye. On fair designs of cross-chain exchange for cryptocurrencies via Monte Carlo simulation, Naval Research Logistics, 2021, DOI:10.1002/nav.21989. Paper.pdf

Jiang G., Fu, M. C., Xu, C., 2014. Bias reduction in estimating quantile sensitivities. IFAC 2014 World Congress.

Jiang G., Fu M. C., Xu C., 2015. Optimal importance sampling for simulation of Levy processes. The 2015 Winter Simulation Conference.

Jiang G., Hong L. J., Nelson B. L., 2016. A simulation analytics approach to dynamic risk monitoring. The 2016 Winter Simulation Conference.

Lam H., Jiang G., Fu M.C., 2018. On efficiencies of stochastic optimization procedures under importance sampling. The 2018 Winter Simulation Conference.

Feng B., Jiang G., 2020. Reuse simulation outputs of repeated experiments via likelihood ration regression. The 2020 Winter Simulation Conference.

Cai X., Yang Y., Jiang G., 2020. Online risk measure estimation via natural gradient boosting. The 2020 Winter Simulation Conference.

Shengyi He, Guangxin Jiang, Henry Lam, Michael C. Fu. 2020. Adaptive importance sampling for efficient stochastic root finding and quantile estimation. Under Review. arXiv link

L. Jeff Hong, Guangxin Jiang, Ying Zhong. 2021. Solving large-scale fixed-budget ranking and selection problems. Under Review. Researchgate Link

Shing Chih Tsai, Jun Luo, Guangxin Jiang, Wei Cheng Yeh. 2020. Adaptive fully sequential selection procedures with linear and nolinear control variates. Under Review.