Sample average approximation - Globe Thesis

Keyword [Sample average approximation] Result: 21 - 40 \| Page: 2 of 3
21.	Minimax Distributionally Robust Optimization Problem Based On ?~2-Divergence Function
22.	Expected Value And Sample Average Approximation Methods For Solving Stochastic Second-order-cone Complementarity Problems
23.	Studies On Stochastic Variational Inequality Problems And Their Applications In Natural Gas Markets
24.	Probabilistic Constrained Optimization Model In Compressed Sensing And Its Smooth Approximation
25.	A New Model Of Stochastic Symmetry Cone Complementarity Problems And Their Solving Method
26.	Smoothing And Sample Average Approximation Methods For Solving Stochastic Symmetric Cone Complementarity Problems
27.	Mathematical Modeling And Algorithms For Two Kinds Of Stochastic Optimization Problems In Supply Chain Under Uncertainty
28.	The Study Of A Class Of Nonlinear Lagrange Method For Constrained Minimax Problems
29.	Expected Value Model And Sample Average Approximation Methods For Solving Stochastic Bilevel Programming Problems
30.	Inventory Optimization Research For Critical Spare Parts Based On Risk-measure Criterion
31.	Two Types Of Newsvendor Problem Under The Random Environment
32.	Asymptotic Analysis And Confidence Optimal Value Estimation For Two Kinds Of Stochastic Programming Problems
33.	Optimality Conditions For Two-stage Stochastic Second-order Cone Programming Problems
34.	Asymptotic Analysis And Confidence Solution Estimation For Two Kinds Of Stochastic Programming Problems
35.	Aspects of optimization with increasing concave stochastic order constraints
36.	Some Research On Stochastic Variational Inequality Problems
37.	Several Algorithms For Second-order Cone Optimization Problems
38.	A Hybrid Newton Method For Stochastic Variational Inequality Problems And Its Application
39.	Convergence Analysis Of (Stochastic) Mathematical Program Problems With Second-order-cone Complementarity Constraints And Non-Lipschitz Objective
40.	Consistency Analysis Of Optimality Conditions For A Class Of Stochastic Semidefinite Programming Problems
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