Guaranteeing approach to solving quantile optimization problems

DOI10.1007/BF02204810zbMath0745.90056OpenAlexW2007541029MaRDI QIDQ1178432

V. Yu. Kurbakovskij, A. I. Kibzun

Publication date: 26 June 1992

Published in: Annals of Operations Research (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/bf02204810

zbMATH Keywords

stochastic approximationMonte-Carlo methodextremal order statistics

Mathematics Subject Classification ID

Stochastic programming (90C15) Computational methods for problems pertaining to operations research and mathematical programming (90-08)

Related Items (4)

A Stochastic Approximation Method for Simulation-Based Quantile Optimization ⋮ Stochastic quasigradient algorithm to minimize the quantile function ⋮ Optimization of the quantile criterion for the convex loss function by a stochastic quasigradient algorithm ⋮ Parallelization of the quantile function optimization algorithms

Cites Work

• Moment Convergence of Sample Extremes
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