Sample Complexity of Sample Average Approximation for Conditional Stochastic Optimization
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Publication:5116551
DOI10.1137/19M1284865zbMath1448.90063arXiv1905.11957MaRDI QIDQ5116551
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Publication date: 18 August 2020
Published in: SIAM Journal on Optimization (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1905.11957
Nonlinear programming (90C30) Stochastic programming (90C15) Approximation methods and heuristics in mathematical programming (90C59)
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- Stochastic compositional gradient descent: algorithms for minimizing compositions of expected-value functions
- Risk bounds for statistical learning
- Sample average approximation method for chance constrained programming: Theory and applications
- Multi-stage stochastic optimization applied to energy planning
- Decomposition methods in stochastic programming
- From error bounds to the complexity of first-order descent methods for convex functions
- Approximation of Carathéodory functions and multifunctions
- Robust sample average approximation
- Convergence of the empirical mean method in statistics and stochastic programming
- Sample average approximation with sparsity-inducing penalty for high-dimensional stochastic programming
- Statistical estimation of composite risk functionals and risk optimization problems
- On complexity of multistage stochastic programs
- The Sample Average Approximation Method for Stochastic Discrete Optimization
- CVXPY: A Python-Embedded Modeling Language for Convex Optimization
- Asynchronous Stochastic Coordinate Descent: Parallelism and Convergence Properties
- Scenarios and Policy Aggregation in Optimization Under Uncertainty
- Lectures on Stochastic Programming
- Kernel Smoothing for Nested Estimation with Application to Portfolio Risk Measurement
- Accelerating Stochastic Composition Optimization
- Optimization Methods for Large-Scale Machine Learning
- Error Bounds, Quadratic Growth, and Linear Convergence of Proximal Methods
- A Single Timescale Stochastic Approximation Method for Nested Stochastic Optimization
- Sample Average Approximation Method for Compound Stochastic Optimization Problems
- Understanding Machine Learning
