6 citations · 6 across the 6 of their papers we have counts for
7 papers
Smooth Learning with Hard Constraints via Legendre-Regularized Policies
Zikun Lin, Rui Chen, Yijie Wang
We revisit contextual optimization from the perspective of policy class design. A desirable policy class should be expressive enough to learn rich context-decision relationships, s…
Distributionally Robust Optimization via Targeted Integral Probability Metrics for General Data Processes
Lanran Fang, Jianqiang Cheng, Grani A. Hanasusanto +1
Distributionally robust optimization (DRO) provides a principled framework for decision-making under distributional uncertainty. Classical data-driven DRO frameworks typically cons…
MATTERIX: toward a digital twin for robotics-assisted chemistry laboratory automation
Kourosh Darvish, Arjun Sohal, Abhijoy Mandal +20
Accelerated materials discovery is critical for addressing global challenges. However, developing new laboratory workflows relies heavily on real-world experimental trials, and thi…
Data-Driven Contextual Optimization with Gaussian Mixtures: Flow-Based Generalization, Robust Models, and Multistage Extensions
YoungChul Yoon, Ling Dai, Grani A. Hanasusanto +2
Contextual optimization enhances decision quality by leveraging side information to improve predictions of uncertain parameters. However, existing approaches face significant chall…
A Distributionally Robust Optimization Approach to Quick Response Models under Demand Uncertainty
Panayotis P. Papavassilopoulos, Grani A. Hanasusanto, Yijie Wang
Quick response is a widely adopted strategy to mitigate overproduction in the manufacturing industry, yet recent research reveals a counter-intuitive paradox: while it reduces wast…
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…