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个人信息Personal Information
教授 博士生导师 硕士生导师
性别：男
毕业院校：山东大学
学历：博士研究生毕业
学位：博士生
在职信息：在职
所在单位：中泰证券金融研究院
入职时间：1999-07-01
办公地点：知新楼B座1118
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- [21] 彭滢. Three Algorithms for Solving High-Dimensional Fully Coupled FBSDEs Through Deep Learning. 《IEEE INTELLIGENT SYSTEMS》, 2020.
- [22] 嵇少林. A filtering problem with uncertainty in observation. Systems and Control Letters, 135, 2020.
- [23] 胡明尚 and 嵇少林. The existence and uniqueness of viscosity solution to a kind of Hamilton-Jacobi-Bellman equation. SIAM JOURNAL ON CONTROL AND OPTIMIZATION？？, 2019.
- [24] 胡明尚 and 嵇少林. A GLOBAL STOCHASTIC MAXIMUM PRINCIPLE FOR FULLY COUPLED FORWARD-BACKWARD STOCHASTIC SYSTEMS. SIAM Journal on Control and Optimization, 2018.
- [25] 嵇少林. The stochastic maximum principle in singular optimal control with recursive utilities. JOURNAL OF MATHEMATICAL ANALYSIS AND APPLICATIONS Journal, 471, 378, 2019.
- [26] 嵇少林. Reaching goals under ambiguity: Continuous-time optimal portfolio selection. Statistics and Probability Letters, 2018.
- [27] 嵇少林. RECURSIVE UTILITY OPTIMIZATION WITH CONCAVE COEFFICIENTS. Mathematical Control and Related Fields, 2018.
- [28] 嵇少林. A STOCHASTIC MAXIMUM PRINCIPLE FOR LINEAR QUADRATIC PROBLEM WITH NONCONVEX CONTROL DOMAIN. Mathematical Control and Related Fields, Vol. 8, No. 3&4, 653-678, 9, 495, 2019.
- [29] 胡明尚 , 嵇少林 and 彭实戈. Comparison theorem, Feynman–Kac formula and Girsanov transformation for BSDEs driven by G-Brownian motion. Stochastic Processes and their Applications, 2014.
- [30] 嵇少林. Recursive Utility Maximization for Terminal Wealth under Partial Information. Math. Probl. Eng., 2016, 2016.
- [31] 嵇少林. Explicit solutions for continuous time mean-variance portfolio selection with nonlinear wealth equations. systems & control letters, 104, 1, 2017.
- [32] 嵇少林 and 孙钏峰. The least squares estimator of random variables under sublinear expectations. Journal of MATHEMATICAL ANALYSIS AND APPLICATIONS, 451, 906, 2017.
- [33] 胡明尚 and 嵇少林. Dynamic programming principle for stochastic recursive optimal control problem driven by a G-Brownian motion. Stochastic Processes and their Applications, 127, 10, 2017.
- [34] 嵇少林. A generalized Neyman–Pearson lemma for g-probabilities. Probability theory and related fields, 148, 645, 2010.
- [35] 嵇少林. A maximum principle for fully coupled forward–backward stochastic control system with terminal state constraints. Journal of MATHEMATICAL ANALYSIS AND APPLICATIONS, 407, 200, 2013.
- [36] 嵇少林. Recursive Utility Maximization for Terminal Wealth under Partial Information. Mathematical Problems in Engineering, 2016.
- [37] 嵇少林. The Neyman-Pearson lemma under g-probability. COMPTES RENDUS MATHEMATIQUE, 346, 209, 2008.
- [38] 嵇少林. Solutions for functional fully coupled forward–backward stochastic differential equations. Statistics and Probability Letters, 2015.
- [39] 嵇少林. A note on functional derivatives on continuous paths. Statistics and Probability Letters, 2015.
- [40] 嵇少林. Fully coupled forward-backward stochastic differential equations on Markov chains. Advances in Difference Equations, 2016.