Cover Image

Sample Average Approximation for Stochastic Programming with Equality Constraints

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Lew, Thomas, Bonalli, Riccardo, Pavone, Marco
Format:	Preprint
Published:	2022
Subjects:	Optimization and Control Systems and Control Statistics Theory 90C15, 65C05, 62F99, 60D05, 93E20
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Multi-Iteration Stochastic Optimizers
by: Carlon, Andre, et al.
Published: (2020)

BISTRO -- A Bi-Fidelity Stochastic Gradient Framework using Trust-Regions for Optimization Under Uncertainty
by: Dixon, Thomas O., et al.
Published: (2025)

On Strategic Measures and Optimality Properties in Discrete-Time Stochastic Control with Universally Measurable Policies
by: Yu, Huizhen
Published: (2022)

A Robbins--Monro Sequence That Can Exploit Prior Information For Faster Convergence
by: Liu, Siwei, et al.
Published: (2024)

An optimal experimental design approach to sensor placement in continuous stochastic filtering
by: Pathiraja, Sahani, et al.
Published: (2025)

IPAS: An Adaptive Sample Size Method for Weighted Finite Sum Problems with Linear Equality Constraints
by: Krejić, Nataša, et al.
Published: (2025)

Adjoint-based optimal control of jump-diffusion processes
by: Bartsch, Jan, et al.
Published: (2025)

Probabilistic Approach to Black-Box Binary Optimization with Budget Constraints: Application to Sensor Placement
by: Attia, Ahmed
Published: (2024)

Drift Optimization of Regulated Stochastic Models Using Sample Average Approximation
by: Zhou, Zihe, et al.
Published: (2025)

Decision-Scaled Scenario Approach for Rare Chance-Constrained Optimization
by: Choi, Jaeseok, et al.
Published: (2026)

A Sequential Quadratic Programming Method for Optimization with Stochastic Objective Functions, Deterministic Inequality Constraints and Robust Subproblems
by: Qiu, Songqiang, et al.
Published: (2023)

Taylor Approximation Variance Reduction for Approximation Errors in PDE-constrained Bayesian Inverse Problems
by: Nicholson, Ruanui, et al.
Published: (2025)

Thompson Sampling for Infinite-Horizon Discounted Decision Processes
by: Adelman, Daniel, et al.
Published: (2024)

Posterior error bounds for prior-driven balancing in linear Gaussian inverse problems
by: König, Josie, et al.
Published: (2026)

ASPEN: An Additional Sampling Penalty Method for Finite-Sum Optimization Problems with Nonlinear Equality Constraints
by: Krejić, Nataša, et al.
Published: (2025)

Entropic Risk-Averse Generalized Momentum Methods
by: Can, Bugra, et al.
Published: (2022)

A Probabilistic Approach to Trajectory-Based Optimal Experimental Design
by: Attia, Ahmed
Published: (2026)

Nonsmooth Projection-Free Optimization with Functional Constraints
by: Asgari, Kamiar, et al.
Published: (2023)

Stochastic Approach for Price Optimization Problems with Decision-dependent Uncertainty
by: Hikima, Yuya, et al.
Published: (2023)

A simulation-optimization approach for fractional, profitability-oriented inventory control under service-level type constraints
by: Sun, Tianxiao, et al.
Published: (2026)

Large-Scale Minimization of the Pseudospectral Abscissa
by: Aliyev, Nicat, et al.
Published: (2022)

Deep neural networks can provably solve Bellman equations for Markov decision processes without the curse of dimensionality
by: Jentzen, Arnulf, et al.
Published: (2025)

Blackwell optimality and policy stability for long-run risk sensitive stochastic control
by: Bäuerle, Nicole, et al.
Published: (2024)

Policy stability and ultimate stationarity in discounted risk-sensitive stochastic control
by: Bäuerle, Nicole, et al.
Published: (2026)

A Regression-Based Prediction-Correction Method for Stochastic Time-Varying Optimization Problems
by: Kamijima, Tomoya, et al.
Published: (2025)

Sufficient Conditions for Error Distance Reduction in the (\ell^2)-norm Trust Region between Minimizers of Local Nonconvex Multivariate Quadratic Approximates
by: Xie, Pengcheng
Published: (2023)

Stochastic Block Bregman Projection with Polyak-like Stepsize for Possibly Inconsistent Convex Feasibility Problems
by: Zhang, Lu, et al.
Published: (2026)

Record-based transmuted unit omega distribution: different methods of estimation and applications
by: Pathak, Ashok Kumar, et al.
Published: (2024)

Design Guidelines for Noise-Tolerant Optimization with Applications in Robust Design
by: Lou, Yuchen, et al.
Published: (2024)

Metric Entropy-Free Sample Complexity Bounds for Sample Average Approximation in Convex Stochastic Programming
by: Liu, Hongcheng, et al.
Published: (2024)

The Geometry and Well-Posedness of Sparse Regularized Linear Regression
by: Everink, Jasper Marijn, et al.
Published: (2024)

Asynchronous Stochastic Approximation with Applications to Average-Reward Reinforcement Learning
by: Yu, Huizhen, et al.
Published: (2024)

Feature preserving data assimilation via feature alignment
by: Subrahmanya, Amit N., et al.
Published: (2025)

Randomized quasi-Monte Carlo methods for risk-averse stochastic optimization
by: Melnikov, Olena, et al.
Published: (2024)

Consistency of sample-based stationary points for infinite-dimensional stochastic optimization
by: Milz, Johannes
Published: (2023)

Time-integrated Optimal Transport: A Robust Minimax Framework
by: Nguyen, Thai P. D., et al.
Published: (2025)

Efficient Data-Driven Optimization with Noisy Data
by: Van Parys, Bart P. G.
Published: (2021)

Gaussian Approximation and Multiplier Bootstrap for Stochastic Gradient Descent
by: Sheshukova, Marina, et al.
Published: (2025)

Bregman Stochastic Proximal Point Algorithm with Variance Reduction
by: Traoré, Cheik, et al.
Published: (2025)

Any-Dimensional Polynomial Optimization via de Finetti Theorems
by: Levin, Eitan, et al.
Published: (2025)