220 citations · 251 across the 24 of their papers we have counts for
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Sample Complexity of Data-driven Multistage Stochastic Programming under Markovian Uncertainty
Hyuk Park, Grani A. Hanasusanto
This work is motivated by the challenges of applying the sample average approximation (SAA) method to multistage stochastic programming with an unknown continuous-state Markov proc…
Generalization Bounds for Contextual Stochastic Optimization using Kernel Regression
Yijie Wang, Grani A. Hanasusanto, Chin Pang Ho
In this paper, we consider contextual stochastic optimization using Nadaraya-Watson kernel regression, which is one of the most common approaches in nonparametric regression. Recen…
Distributionally Robust Performative Optimization
Zhuangzhuang Jia, Yijie Wang, Roy Dong +1
In performative stochastic optimization, decisions can influence the distribution of random parameters, rendering the data-generating process itself decision-dependent. In practice…
Distributionally Robust Optimization with Decision-Dependent Information Discovery
Qing Jin, Angelos Georghiou, Phebe Vayanos +1
We study two-stage distributionally robust optimization (DRO) problems with decision-dependent information discovery (DDID) wherein (a portion of) the uncertain parameters are reve…
Distributionally Fair Stochastic Optimization using Wasserstein Distance
Qing Ye, Grani A. Hanasusanto, Weijun Xie
A traditional stochastic program under a finite population typically seeks to optimize efficiency by maximizing the expected profits or minimizing the expected costs, subject to a…