10 citations · 10 across the 5 of their papers we have counts for
6 papers
Robust POMDP Framework for Lung Cancer Screening Problems
Tong Li, Iakovos Toumazis, Yisha Xiang
Lung cancer remains a leading cause of cancer mortality because many cases are diagnosed at advanced stages. Low-dose computed tomography (LDCT) screening can reduce mortality thro…
Certifying Lower Bounds for Risk-Sensitive Reinforcement Learning under Adversarial State Perturbations
Tong Li, Saunak Kumar Panda, Yisha Xiang
Reinforcement learning (RL) agents deployed in real-world environments are often vulnerable to adversarial perturbations in state observations, creating risks in safety-critical ap…
Dynamic resource matching in manufacturing using deep reinforcement learning
Saunak Kumar Panda, Yisha Xiang, Ruiqi Liu
Matching plays an important role in the logical allocation of resources across a wide range of industries. The benefits of matching have been increasingly recognized in manufacturi…
Online Statistical Inference of Constant Sample-averaged Q-Learning
Saunak Kumar Panda, Tong Li, Ruiqi Liu +1
Reinforcement learning algorithms have been widely used for decision-making tasks in various domains. However, the performance of these algorithms can be impacted by high variance…
Modeling Multivariate Degradation Data with Dynamic Covariates Under a Bayesian Framework
Zhengzhi Lin, Xiao Liu, Yisha Xiang +1
Degradation data are essential for determining the reliability of high-end products and systems, especially when covering multiple degradation characteristics (DCs). Modern degrada…
Asymptotic Analysis of Sample-averaged Q-learning
Saunak Kumar Panda, Ruiqi Liu, Yisha Xiang
Reinforcement learning (RL) has emerged as a key approach for training agents in complex and uncertain environments. Incorporating statistical inference in RL algorithms is essenti…