most citedDistributionally Robust Learning with Weakly Convex Losses: Convergence Rates and Finite-Sample Guarantees

2 citations · 2 across the 1 of their papers we have counts for

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2 papers

math.OC2023★ 2 cited

Distributionally Robust Learning with Weakly Convex Losses: Convergence Rates and Finite-Sample Guarantees

Landi Zhu, Mert Gürbüzbalaban, Andrzej Ruszczyński

We consider a distributionally robust stochastic optimization problem and formulate it as a stochastic two-level composition optimization problem with the use of the mean--semidevi…

math.OC2020

A Stochastic Subgradient Method for Distributionally Robust Non-Convex Learning

Mert Gürbüzbalaban, Andrzej Ruszczyński, Landi Zhu

We consider a distributionally robust formulation of stochastic optimization problems arising in statistical learning, where robustness is with respect to uncertainty in the underl…