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math.OC2026
Convergence Rate of a Functional Learning Method for Contextual Stochastic Optimization
Noel Smith, Andrzej Ruszczynski
We consider a stochastic optimization problem involving two random variables: a context variable and a dependent variable . The objective is to minimize the expected value o…
math.OC2024
A Functional Model Method for Nonconvex Nonsmooth Conditional Stochastic Optimization
Andrzej Ruszczyński, Shangzhe Yang
We consider stochastic optimization problems involving an expected value of a nonlinear function of a base random vector and a conditional expectation of another function depending…
math.OC2023
An Integrated Transportation Distance Between Kernels and Approximate Dynamic Risk Evaluation in Markov Systems
Zhengqi Lin, Andrzej Ruszczynski
We introduce a distance between kernels based on the Wasserstein distances between their values, study its properties, and prove that it is a metric on an appropriately defined spa…