3 citations · 3 across the 8 of their papers we have counts for
10 papers
Optimal Resource Extraction under Distribution Learning and Infinite-Horizon Stochastic Hamilton--Jacobi Equations
Ulrich Horst, Jinniao Qiu, Yang Yang
We study an infinite-horizon stochastic control problem for the optimal exploitation of an exhaustible resource with unknown total reserves. Information is generated both endogenou…
A Policy Iteration Scheme for Semilinear Stochastic Hamilton-Jacobi-Bellman Equations with Exponential Convergence
Hasib Uddin Molla, Jinniao Qiu
This paper is concerned with the non-Markovian stochastic optimal control problems in which the value function is a random field characterized by a stochastic Hamilton-Jacobi-Bellm…
Stochastic Control Methods for Optimization
Jinniao Qiu
In this work, we investigate a stochastic control framework for global optimization over both Euclidean spaces and the Wasserstein space of probability measures, where the objectiv…
A Deep Learning-Based Method for Fully Coupled Non-Markovian FBSDEs with Applications
Hasib Uddin Molla, Matthew Backhouse, Ankit Banarjee +1
In this work, we extend deep learning-based numerical methods to fully coupled forward-backward stochastic differential equations (FBSDEs) within a non-Markovian framework. Error e…
Viscosity Solutions of Fully second-order HJB Equations in the Wasserstein Space
Erhan Bayraktar, Hang Cheung, Ibrahim Ekren +3
In this paper, we show that the value functions of mean field control problems with common noise are the unique viscosity solutions to fully second-order Hamilton-Jacobi-Bellman eq…
Feynman-Kac Formula for Time-Dependent Nonlinear Schrödinger Equations with Applications in Numerical Approximations
Hang Cheung, Jinniao Qiu, Yang Yang
In this paper, we present a novel Feynman-Kac formula and investigate learning-based methods for approximating general nonlinear time-dependent Schrödinger equations which may be h…