Convergence rates of finite difference stochastic approximation algorithms part II: implementation via common random numbers

Mapping Intimacies ◽

10.1117/12.2228251 ◽

2016 ◽

Author(s):

Liyi Dai

Keyword(s):

Approximation Algorithms ◽

Finite Difference ◽

Stochastic Approximation ◽

Convergence Rates ◽

Random Numbers ◽

Common Random Numbers

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Convergence rates of finite difference stochastic approximation algorithms part I: general sampling

10.1117/12.2228250 ◽

2016 ◽

Author(s):

Liyi Dai

Keyword(s):

Approximation Algorithms ◽

Finite Difference ◽

Stochastic Approximation ◽

Convergence Rates

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Convergence Rates and Decoupling in Linear Stochastic Approximation Algorithms

SIAM Journal on Control and Optimization ◽

10.1137/14095707x ◽

2015 ◽

Vol 53 (3) ◽

pp. 1484-1508 ◽

Cited By ~ 3

Author(s):

Michael A. Kouritzin ◽

Samira Sadeghi

Keyword(s):

Approximation Algorithms ◽

Stochastic Approximation ◽

Convergence Rates

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Simulation-Based Optimization with Stochastic Approximation Using Common Random Numbers

Management Science ◽

10.1287/mnsc.45.11.1570 ◽

1999 ◽

Vol 45 (11) ◽

pp. 1570-1578 ◽

Cited By ~ 48

Author(s):

Nathan L. Kleinman ◽

James C. Spall ◽

Daniel Q. Naiman

Keyword(s):

Stochastic Approximation ◽

Random Numbers ◽

Common Random Numbers ◽

Simulation Based ◽

Simulation Based Optimization

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On conditions for convergence rates of stochastic approximation algorithms

Proceedings of the 36th IEEE Conference on Decision and Control ◽

10.1109/cdc.1997.657113 ◽

2002 ◽

Author(s):

E.K.P. Chong ◽

I.-J. Wang ◽

S.R. Kulkarni

Keyword(s):

Approximation Algorithms ◽

Stochastic Approximation ◽

Convergence Rates

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Rate of Convergence for Derivative Estimation of Discrete-Time Markov Chains via Finite-Difference Approximation with Common Random Numbers

SIAM Journal on Applied Mathematics ◽

10.1137/s003613999427173x ◽

1997 ◽

Vol 57 (3) ◽

pp. 731-751 ◽

Cited By ~ 8

Author(s):

Liyi Dai

Keyword(s):

Finite Difference ◽

Markov Chains ◽

Rate Of Convergence ◽

Discrete Time ◽

Finite Difference Approximation ◽

Difference Approximation ◽

Random Numbers ◽

Derivative Estimation ◽

Common Random Numbers

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Noise conditions for prespecified convergence rates of stochastic approximation algorithms

IEEE Transactions on Information Theory ◽

10.1109/18.749035 ◽

1999 ◽

Vol 45 (2) ◽

pp. 810-814 ◽

Cited By ~ 9

Author(s):

E.K.P. Chong ◽

I-Jeng Wang ◽

S.R. Kulkarni

Keyword(s):

Approximation Algorithms ◽

Stochastic Approximation ◽

Convergence Rates

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Untangling Uncertainty With Common Random Numbers: A Simulation Study

Summer Computer Simulation Conference (SCSC) ◽

10.22360/summersim.2017.scsc.031 ◽

2017 ◽

Keyword(s):

Simulation Study ◽

Random Numbers ◽

Common Random Numbers

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NN-approach to design of the optimal stochastic approximation algorithms

International Conference on Control '94 ◽

10.1049/cp:19940173 ◽

1994 ◽

Cited By ~ 1

Author(s):

A.V. Nazin

Keyword(s):

Approximation Algorithms ◽

Stochastic Approximation

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Performance analysis of discrete event dynamic systems via common random numbers

Proceedings of 1994 33rd IEEE Conference on Decision and Control ◽

10.1109/cdc.1994.410999 ◽

2002 ◽

Cited By ~ 1

Author(s):

L. Dai

Keyword(s):

Performance Analysis ◽

Dynamic Systems ◽

Discrete Event ◽

Discrete Event Dynamic Systems ◽

Random Numbers ◽

Common Random Numbers ◽

Event Dynamic

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How common random numbers affect multinomial selection

Proceedings of the 29th conference on Winter simulation - WSC '97 ◽

10.1145/268437.268503 ◽

1997 ◽

Author(s):

J. O. Miller ◽

Kenneth W. Bauer

Keyword(s):

Random Numbers ◽

Common Random Numbers

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