A regularized stochastic subgradient projection method for an optimal control problem in a stochastic partial differential equation
DOI10.1007/978-3-030-84721-0_19zbMath1500.93146OpenAlexW4252503825MaRDI QIDQ2080615
Miguel Sama, Akhtar A. Khan, Baasansuren Jadamba
Publication date: 9 October 2022
Full work available at URL: https://doi.org/10.1007/978-3-030-84721-0_19
optimal controlregularizationstochastic approximationstochastic PDEsprojected stochastic subgradient
Inverse problems for PDEs (35R30) Optimal stochastic control (93E20) Stochastic partial differential equations (aspects of stochastic analysis) (60H15) Numerical solutions of ill-posed problems in abstract spaces; regularization (65J20) Numerical solution to inverse problems in abstract spaces (65J22) Numerical methods for ill-posed problems for initial value and initial-boundary value problems involving PDEs (65M30)
Uses Software
Cites Work
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- Multilevel and weighted reduced basis method for stochastic optimal control problems constrained by Stokes equations
- Regularization for state constrained optimal control problems by half spaces based decoupling
- Multigrid and sparse-grid schemes for elliptic control problems with random coefficients
- On H-valued Robbins-Monro processes
- Minimizing noisy functionals in Hilbert space: An extension of the Kiefer-Wolfowitz procedure
- Stochastic mirror descent dynamics and their convergence in monotone variational inequalities
- Error estimates for integral constraint regularization of state-constrained elliptic control problems
- An approach for robust PDE-constrained optimization with application to shape optimization of electrical engines and of dynamic elastic structures under uncertainty
- Bridging the gap between constant step size stochastic gradient descent and Markov chains
- Variable smoothing for convex optimization problems using stochastic gradients
- An infeasible stochastic approximation and projection algorithm for stochastic variational inequalities
- Regularized nonlinear acceleration
- Stable conical regularization by constructible dilating cones with an application to \(L^{p}\)-constrained optimization problems
- Comparison of approaches for random PDE optimization problems based on different matching functionals
- A New Conical Regularization for Some Optimization and Optimal Control Problems: Convergence Analysis and Finite Element Discretization
- A Trust-Region Algorithm with Adaptive Stochastic Collocation for PDE Optimization under Uncertainty
- Adaptive Reduced-Order Model Construction for Conditional Value-at-Risk Estimation
- Stochastic Approximation in Hilbert Space: Identification and Optimization of Linear Continuous Parameter Systems
- Gradient Convergence in Gradient methods with Errors
- Optimal Control of PDEs under Uncertainty
- Variance-Based Extragradient Methods with Line Search for Stochastic Variational Inequalities
- Sparse Solutions in Optimal Control of PDEs with Uncertain Parameters: The Linear Case
- Mean-Variance Risk-Averse Optimal Control of Systems Governed by PDEs with Random Parameter Fields Using Quadratic Approximations
- Reduced Basis Methods for Uncertainty Quantification
- Stochastic Collocation for Optimal Control Problems with Stochastic PDE Constraints
- New development in freefem++
- Optimal Algorithms for Non-Smooth Distributed Optimization in Networks
- Projected Stochastic Gradients for Convex Constrained Problems in Hilbert Spaces
- Regularization Methods for Scalar and Vector Control Problems
- A new incremental constraint projection method for solving monotone variational inequalities
- Regularized Iterative Stochastic Approximation Methods for Stochastic Variational Inequality Problems
- Hilbert-Valued Perturbed Subgradient Algorithms
- Extragradient Method with Variance Reduction for Stochastic Variational Inequalities
- Decomposition/Coordination Algorithms in Stochastic Optimization
- A Stochastic Approximation Method
- Stochastic approximation
- Stochastic approximation with nondecaying gain: Error bound and data‐driven gain‐tuning