L. Jeff Hong's Research Group
L. Jeff Hong's Research Group
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Monte Carlo Methods in Stochastic Programming
Robust simulation with likelihood-ratio constrained input uncertainty
Learning-based robust optimization procedures and statistical guarantee
Gradient and Hessian of joint probability functions with applications on chance constrained programs
Approximating data-driven joint chance constrained programs via uncertainty set construction
A statistical perspective on linear programs with uncertain parameters
Robust simulation of stochastic systems with input uncertainties modeled by statistical divergences
Conditional value-at-risk approximation to value-at-risk constrained programs: A remedy via Monte Carlo
Monte Carlo methods for value-at-risk and conditional value-at-risk: A review
A smooth Monte Carlo approximation to joint chance-constrained programs
Ambiguous Probabilistic Programs
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