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Publication
Legend: (*) denotes corresponding author.
Publications
Large Deviation Estimates for Nonlinear Filtering with Discontinuity and Small Noise
H. Qian*, Y. Cao, and G. Yin
Stochastic Processes and their Applications, 104662.
Numerical solutions of a class of optimal stopping problems
P. Ernst, X. Ma, M. H. Nazari, H. Qian, L. Y. Wang, and G. Yin
Nonlinear Analysis: Hybrid Systems, 53: 101507, 2024.
A class of numerical algorithms for stochastic differential equations with randomly varying truncations inspired by a stochastic optimization problem
H. Qian, F. Wu, and G. Yin
Discrete and Continuous Dynamical Systems - S, 18(3): 578-602, 2025.
Deep Filtering with Adaptive Learning Rates
H. Qian, G. Yin, and Q. Zhang
IEEE Transactions on Automatic Control, 68 (6): 3285-3299, 2023.
Moderate Deviations for the Langevin Equations: Strong Damping and Fast Markovian Switching
H. Qian and G. Yin
Journal of Mathematical Physics, 63(12): 123304, 2022, 28 pp.
Filtering with degenerate observation noise: A stochastic approximation approach
H. Qian, Q. Zhang and G. Yin
Automatica. 142: 110376, 2022, 9 pp.
Numerical Solutions for Optimal Control of Stochastic Kolmogorov Systems with Regime-Switching and Random Jumps
H. Qian, Z. Wen, and G. Yin
Statistical Inference for Stochastic Processes, 25(1): 105-125, 2022 (invited paper dedicated to the 90th birthday of Professor Rafail Khasminskii).
Numerical Solutions for Optimal Control of Stochastic Kolmogorov Systems
G. Yin, Z. Wen, H. Qian, and H. Nguyen
Journal of Systems Science and Complexity, 34(5), 1703-1722, 2021.
Preprints
H. Qian, G. Yin, Q. Zhang, A deep learning approach for optimal pairs trading, submitted.
H. Qian*, Moderate Deviation Principles for Stochastic Differential Equations in a Fast Markovian Environment, submitted, [RG].
F. Bao, Y. Cao, and H. Qian*, Numerical approximations for partially observed optimal control of stochastic partial differential equations, submitted, [arXiv].
Y. Cao, H. Qian*, and G. Yin, Optimal Control of Stochastic Partial Differential Equations with Partial Observations: Stochastic Maximum Principles and Numerical Approximation, submitted, [arXiv].
H. Qian, G. Yin, Moderate Deviation Principles for Stochastic Reaction-Diffusion Equations in Random Environment, in preparation.
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