On convergence of the stochastic subgradient method with on-line stepsize rules

Andrzej Ruszczyński; Wojciech Syski

doi:10.1016/0022-247X(86)90104-6

On convergence of the stochastic subgradient method with on-line stepsize rules

Andrzej Ruszczyński, Wojciech Syski

Research output: Contribution to journal › Article › peer-review

7 Scopus citations

Abstract

A stochastic subgradient method for solving convex stochastic programming problems is considered. New on-line rules for determining stepsizes are derived from the concept of local regularized improvement functions. Convergence with probability 1 of the whole method is established.

Original language	English (US)
Pages (from-to)	512-527
Number of pages	16
Journal	Journal of Mathematical Analysis and Applications
Volume	114
Issue number	2
DOIs	https://doi.org/10.1016/0022-247X(86)90104-6
State	Published - Mar 1986
Externally published	Yes

All Science Journal Classification (ASJC) codes

Analysis
Applied Mathematics

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10.1016/0022-247X(86)90104-6

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title = "On convergence of the stochastic subgradient method with on-line stepsize rules",

abstract = "A stochastic subgradient method for solving convex stochastic programming problems is considered. New on-line rules for determining stepsizes are derived from the concept of local regularized improvement functions. Convergence with probability 1 of the whole method is established.",

author = "Andrzej Ruszczy{\'n}ski and Wojciech Syski",

year = "1986",

month = mar,

doi = "10.1016/0022-247X(86)90104-6",

language = "English (US)",

volume = "114",

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AU - Ruszczyński, Andrzej

AU - Syski, Wojciech

PY - 1986/3

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N2 - A stochastic subgradient method for solving convex stochastic programming problems is considered. New on-line rules for determining stepsizes are derived from the concept of local regularized improvement functions. Convergence with probability 1 of the whole method is established.

AB - A stochastic subgradient method for solving convex stochastic programming problems is considered. New on-line rules for determining stepsizes are derived from the concept of local regularized improvement functions. Convergence with probability 1 of the whole method is established.

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JO - Journal of Mathematical Analysis and Applications

JF - Journal of Mathematical Analysis and Applications

SN - 0022-247X

IS - 2

ER -

On convergence of the stochastic subgradient method with on-line stepsize rules

Abstract

All Science Journal Classification (ASJC) codes

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