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Song, Chenxiao

Monte Carlo variance reduction methods with applications in structural reliability analysis. (Abstract of thesis). (English) Zbl 07764683

Bull. Aust. Math. Soc. 108, No. 3, 518-521 (2023).

MSC:

65C05 Monte Carlo methods
60F05 Central limit and other weak theorems
62L20 Stochastic approximation
65C10 Random number generation in numerical analysis
65D30 Numerical integration
65Y20 Complexity and performance of numerical algorithms
93E35 Stochastic learning and adaptive control

Keywords:

Monte Carlo methods; variance reduction; adaptive simulation; stochastic approximation; structural reliability analysis
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References:

[1] Kawai, R., ‘Optimizing adaptive importance sampling by stochastic approximation’, SIAM J. Sci. Comput.40(4) (2018), A2774-A2800. · Zbl 1396.65009
[2] Kawai, R., ‘Adaptive importance sampling and control variates’, J. Math. Anal. Appl.483(1) (2020), Article no. 123608. · Zbl 07138453
[3] Song, C. and Kawai, R., ‘Adaptive radial importance sampling under directional stratification’, Probab. Eng. Mech.72 (2023), Article no. 103443.
[4] Song, C. and Kawai, R., ‘Adaptive stratified sampling for structural reliability analysis’, Struct. Safety101 (2023), Article no. 102292.
[5] Song, C. and Kawai, R., ‘Batching adaptive variance reduction’, ACM Trans. Model. Comput. Simul.33(3) (2023), 1-24. · Zbl 1515.65015
[6] Song, C. and Kawai, R., ‘Dynamic finite-budget allocation of stratified sampling with adaptive variance reduction by strata’, SIAM J. Sci. Comput.45(2) (2023), A898-A932. · Zbl 1512.65008
[7] Song, C. and Kawai, R., ‘Monte Carlo and variance reduction methods for structural reliability analysis: A comprehensive review’, Probab. Eng. Mech.73 (2023), Article no. 103479.
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