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http://hdl.handle.net/20.500.12188/6665
Title: | Stochastic approximation with adaptive step sizes for optimization in noisy environment and its application in regression models | Authors: | Kresoja, Milena Dimovski, Marko Stojkovska, Irena Luzanin, Zorana |
Keywords: | unconstrained optimization, stochastic optimization, stochastic approximation, noisy function, adaptive step size, gradient method, descent direction, regression models. | Issue Date: | 1-Jan-2017 | Publisher: | Union of Mathematicians of Macedonia | Journal: | Matematichki Bilten | Abstract: | We propose a generalization of recently proposed stochastic approximation method with adaptive step sizes for optimization problems in noisy environment. The adaptive step size scheme uses only a predefined number of last noisy functional values to select a step size for the next iterate and allows different intensities of influence of the past functional values. The almost sure convergence is established under suitable assumptions. Numerical results indicate a good performance of the method. Application of the method in regression models is presented. | URI: | http://hdl.handle.net/20.500.12188/6665 |
Appears in Collections: | Faculty of Natural Sciences and Mathematics: Journal Articles |
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STOCHASTIC APPROXIMATION WITH ADAPTIVE STEP SIZES FOR OPTIMIZATION IN NOISY ENVIRONMENT AND ITS APPLICATION IN REGRESSION MODELS.pdf | Journal Article | 192.74 kB | Adobe PDF | ![]() View/Open |
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