Monte Carlo method of batch iterations: probabilistic characteristics

DOI10.1134/S0005117915050045zbMath1322.93108OpenAlexW765654661MaRDI QIDQ747227

Boris S. Darkhovsky, Alexey Yu. Popkov, Yuri S. Popkov

Publication date: 23 October 2015

Published in: Automation and Remote Control (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1134/s0005117915050045

zbMATH Keywords

approximate solutionHölder conditionglobal minimum of residuesMonte Carlo trialsprobabilistic estimatessystems of nonlinear algebraic equations and inequalities

Mathematics Subject Classification ID

Related Items (4)

New method of randomized forecasting using entropy-robust estimation: application to the world population prediction ⋮ Iterative MC-algorithm to solve the global optimization problems ⋮ Mathematical methods of randomized machine learning ⋮ Randomized machine learning procedures

Cites Work

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• Global optimization with non-convex constraints. Sequential and parallel algorithms
• Simulation and the Monte Carlo Method
• Solving convex programs by random walks

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