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Zhi-Hai Zhang

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Jul 2026

EXPRESS: Tackling Decision Dependency in Contextual Stochastic Optimization

It is established that CGD converges to a neighborhood of the global optimum when the loss function exhibits sufficient strong convexity, and the derived bounds reveal a key insight: the strength of convexity in the loss function can compensate for the uncertainty introduced by decision-dependent effects.

Wenxuan Liu, Xiangting Liu, Maoqi Liu et al. · 0 citations

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