The modified MSA, a gradient flow and convergence
From MaRDI portal
Publication:6620074
DOI10.1214/24-aap2071MaRDI QIDQ6620074
Publication date: 16 October 2024
Published in: The Annals of Applied Probability (Search for Journal in Brave)
Cites Work
- Unnamed Item
- Unnamed Item
- \{Euclidean, metric, and Wasserstein\} gradient flows: an overview
- Adapted solution of a backward stochastic differential equation
- Deep learning-based numerical methods for high-dimensional parabolic partial differential equations and backward stochastic differential equations
- On finite-difference approximations for normalized Bellman equations
- Continuous-time stochastic control and optimization with financial applications
- On the convergence of policy iteration for controlled diffusions
- Continuous exponential martingales and BMO
- A stability approach for solving multidimensional quadratic BSDEs
- DGM: a deep learning algorithm for solving partial differential equations
- Proof that deep artificial neural networks overcome the curse of dimensionality in the numerical approximation of Kolmogorov partial differential equations with constant diffusion and nonlinear drift coefficients
- A modified MSA for stochastic control problems
- The rate of convergence of finite-difference approximations for parabolic bellman equations with Lipschitz coefficients in cylindrical domains
- On the policy improvement algorithm in continuous time
- A General Stochastic Maximum Principle for Optimal Control Problems
- On the convergence rate of approximation schemes for Hamilton-Jacobi-Bellman Equations
- Uniform error estimates for artificial neural network approximations for heat equations
- Unbiased Deep Solvers for Linear Parametric PDEs
- Exponential Convergence and Stability of Howard's Policy Improvement Algorithm for Controlled Diffusions
- Backward Stochastic Differential Equations
- On a method of successive approximations for the solution of problems of optimal control
- A Modified Method of Successive Approximations for Stochastic Recursive Optimal Control Problems
- A Proof that Artificial Neural Networks Overcome the Curse of Dimensionality in the Numerical Approximation of Black–Scholes Partial Differential Equations
- Linear Convergence of a Policy Gradient Method for Some Finite Horizon Continuous Time Control Problems
This page was built for publication: The modified MSA, a gradient flow and convergence