96 citations · 286 across the 19 of their papers we have counts for
4 papers · 1 filter
Reliable Off-policy Evaluation for Reinforcement Learning
Jie Wang, Rui Gao, Hongyuan Zha
In a sequential decision-making problem, off-policy evaluation estimates the expected cumulative reward of a target policy using logged trajectory data generated from a different b…
Finite-Sample Guarantees for Wasserstein Distributionally Robust Optimization: Breaking the Curse of Dimensionality
Rui Gao
Wasserstein distributionally robust optimization (DRO) aims to find robust and generalizable solutions by hedging against data perturbations in Wasserstein distance. Despite its re…
Bridging Explicit and Implicit Deep Generative Models via Neural Stein Estimators
Qitian Wu, Rui Gao, Hongyuan Zha
There are two types of deep generative models: explicit and implicit. The former defines an explicit density form that allows likelihood inference; while the latter targets a flexi…
Wasserstein Distributionally Robust Optimization and Variation Regularization
Rui Gao, Xi Chen, Anton J. Kleywegt
Wasserstein distributionally robust optimization (DRO) has recently achieved empirical success for various applications in operations research and machine learning, owing partly to…