Universal Confidence Sets for Solutions of Optimization Problems

DOI10.1137/070680023zbMath1198.90310OpenAlexW1995997744WikidataQ105584119 ScholiaQ105584119MaRDI QIDQ3395027

Silvia Vogel

Publication date: 20 August 2009

Published in: SIAM Journal on Optimization (Search for Journal in Brave)

Full work available at URL: https://www.db-thueringen.de/servlets/MCRFileNodeServlet/dbt_derivate_00010609/IfM_Preprint_M_06_12.pdf

zbMATH Keywords

stochastic programminguniversal confidence

Mathematics Subject Classification ID

Parametric tolerance and confidence regions (62F25) Sensitivity, stability, parametric optimization (90C31) Stochastic programming (90C15)

Related Items (8)

Random approximations in multiobjective optimization ⋮ Individual confidence intervals for solutions to expected value formulations of stochastic variational inequalities ⋮ Sample average approximation with heavier tails. I: Non-asymptotic bounds with weak assumptions and stochastic constraints ⋮ Mitigating Uncertainty via Compromise Decisions in Two-Stage Stochastic Linear Programming: Variance Reduction ⋮ Generalized conditioning based approaches to computing confidence intervals for solutions to stochastic variational inequalities ⋮ A Central Limit Theorem and Hypotheses Testing for Risk-averse Stochastic Programs ⋮ On Monte-Carlo methods in convex stochastic optimization ⋮ On rates of convergence for sample average approximations in the almost sure sense and in mean

This page was built for publication: Universal Confidence Sets for Solutions of Optimization Problems