Convergence Analysis of Stochastic Algorithms
From MaRDI portal
Publication:4716927
DOI10.1287/moor.21.3.615zbMath0868.90114OpenAlexW2119374337MaRDI QIDQ4716927
No author found.
Publication date: 1 December 1996
Published in: Mathematics of Operations Research (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1287/moor.21.3.615
stochastic processesnondifferentiable optimizationconvex analysisuniform laws of large numbersgradient descent algorithmsasymptotic convergence to stationary points
Related Items (15)
On sample size control in sample average approximations for solving smooth stochastic programs ⋮ Convergence analysis of gradient descent stochastic algorithms ⋮ Stochastic \(R_0\) tensors to stochastic tensor complementarity problems ⋮ Accelerated stochastic variance reduction for a class of convex optimization problems ⋮ A unified framework for stochastic optimization ⋮ An Asymptotically Optimal Set Approach for Simulation Optimization ⋮ Optimal multivariate quota-share reinsurance: a nonparametric mean-CVaR framework ⋮ Stochastic global optimization using tangent minorants for Lipschitz functions ⋮ Extensions of stochastic optimization results to problems with system failure probability functions ⋮ Sample size selection in optimization methods for machine learning ⋮ Stochastic proximal gradient methods for nonconvex problems in Hilbert spaces ⋮ Inexact Restoration approach for minimization with inexact evaluation of the objective function ⋮ Grouping for optimal growth ⋮ Optimization of computer simulation models with rare events ⋮ A simulation-based approach to two-stage stochastic programming with recourse
This page was built for publication: Convergence Analysis of Stochastic Algorithms
