Dynamic stochastic approximation for multi-stage stochastic optimization
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Publication:2020613
DOI10.1007/s10107-020-01489-yzbMath1465.90053arXiv1707.03324OpenAlexW3012647659MaRDI QIDQ2020613
Publication date: 23 April 2021
Published in: Mathematical Programming. Series A. Series B (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1707.03324
Semidefinite programming (90C22) Convex programming (90C25) Large-scale problems in mathematical programming (90C06) Stochastic programming (90C15) Numerical methods based on nonlinear programming (49M37) Decentralized systems (93A14)
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Cites Work
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- Smooth minimization of non-smooth functions
- Accelerated gradient methods for nonconvex nonlinear and stochastic programming
- An optimal method for stochastic composite optimization
- Evaluating policies in risk-averse multi-stage stochastic programming
- Stochastic compositional gradient descent: algorithms for minimizing compositions of expected-value functions
- Analysis of stochastic dual dynamic programming method
- Primal-dual first-order methods with \({\mathcal {O}(1/\varepsilon)}\) iteration-complexity for cone programming
- Validation analysis of mirror descent stochastic approximation method
- Multi-stage stochastic optimization applied to energy planning
- Multi-stage stochastic linear programs for portfolio optimization
- Introductory lectures on convex optimization. A basic course.
- An optimal randomized incremental gradient method
- A first-order primal-dual algorithm for convex problems with applications to imaging
- Bundle-level type methods uniformly optimal for smooth and nonsmooth convex optimization
- On complexity of multistage stochastic programs
- On the $O(1/n)$ Convergence Rate of the Douglas–Rachford Alternating Direction Method
- On the Complexity of the Hybrid Proximal Extragradient Method for the Iterates and the Ergodic Mean
- Scenarios and Policy Aggregation in Optimization Under Uncertainty
- Lectures on Stochastic Programming
- Robust Stochastic Approximation Approach to Stochastic Programming
- Stochastic Decomposition: An Algorithm for Two-Stage Linear Programs with Recourse
- Acceleration of Stochastic Approximation by Averaging
- Introduction to Stochastic Programming
- Prox-Method with Rate of Convergence O(1/t) for Variational Inequalities with Lipschitz Continuous Monotone Operators and Smooth Convex-Concave Saddle Point Problems
- Optimal Stochastic Approximation Algorithms for Strongly Convex Stochastic Composite Optimization I: A Generic Algorithmic Framework
- On Solving Multistage Stochastic Programs with Coherent Risk Measures
- Optimal Primal-Dual Methods for a Class of Saddle Point Problems
- An Accelerated Linearized Alternating Direction Method of Multipliers
- Optimal Stochastic Approximation Algorithms for Strongly Convex Stochastic Composite Optimization, II: Shrinking Procedures and Optimal Algorithms
- Stochastic First- and Zeroth-Order Methods for Nonconvex Stochastic Programming
- Convex Analysis
- Stochastic Quasi-Newton Methods for Nonconvex Stochastic Optimization
- A Stochastic Approximation Method
- Mini-batch stochastic approximation methods for nonconvex stochastic composite optimization