G2TT
来源类型Article
规范类型其他
DOI10.1007/BF02204816
Normalized convergence in stochastic optimization.
Ermoliev Y; Norkin VI
发表日期1991
出处Annals of Operations Research 30 (1): 187-198
出版年1991
语种英语
摘要A new concept of (normalized) convergence of random variables is introduced. This convergence is preserved under Lipschitz transformations, follows from convergence in mean and itself implies convergence in probability. If a sequence of random variables satisfies a limit theorem then it is a normalized convergent sequence. The introduced concept is applied to the convergence rate study of a statistical approach in stochastic optimization.
主题Adaption and Optimization (ADO)
关键词Probability theory normalized convergence stochastic optimization statistical approach rate of convergence
URLhttp://pure.iiasa.ac.at/id/eprint/3462/
来源智库International Institute for Applied Systems Analysis (Austria)
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资源类型智库出版物
条目标识符http://119.78.100.153/handle/2XGU8XDN/127135
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GB/T 7714
Ermoliev Y,Norkin VI. Normalized convergence in stochastic optimization.. 1991.
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