Stochastic Quasigradient Methods and their Implications
Y. Ermoliev, Alexei A. Gaivoronski
Abstract
Open-access reader
Y. Ermoliev, Alexei A. Gaivoronski
Abstract
Open-access reader
A number of stochastic quasigradient methods are discussed from the point of view of implementation. The discussion revolves around the interactive package of stochastic optimization routines (STO) recently developed by the Adaptation and Optimization group at IIASA. (This package is based on the stochastic and nondifferentiable optimization package (NDO) developed at the V. Glushkov Institute of Cybernetics in Kiev.) The IIASA implementation is described and its use illustrated by application to three problems which have arisen in various IIASA projects.
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A number of stochastic quasigradient methods are discussed from the point of view of implementation. The discussion revolves around the interactive package of stochastic optimization routines (STO) recently developed by the Adaptation and Optimization group at IIASA. (This package is based on the stochastic and nondifferentiable optimization package (NDO) developed at the V. Glushkov Institute of Cybernetics in Kiev.) The IIASA implementation is described and its use illustrated by application to three problems which have arisen in various IIASA projects.
Key concepts: Computer science, Stochastic optimization, Cybernetics, Adaptation (eye), Point (geometry), Stochastic process, Stochastic modelling, Mathematical optimization