3 papers
cs.LG2026
Near-Constant Strong Violation and Last-Iterate Convergence for Online CMDPs via Decaying Safety Margins
Qian Zuo, Zhiyong Wang, Fengxiang He
We study safe online reinforcement learning in Constrained Markov Decision Processes (CMDPs) under strong regret and violation metrics, which forbid error cancellation over time. E…
cs.LG2025
Ensuring Safety in an Uncertain Environment: Constrained MDPs via Stochastic Thresholds
Qian Zuo, Fengxiang He
This paper studies constrained Markov decision processes (CMDPs) with constraints against stochastic thresholds, aiming at safety of reinforcement learning in unknown and uncertain…
cs.CV2025
Point Cloud Segmentation of Integrated Circuits Package Substrates Surface Defects Using Causal Inference: Dataset Construction and Methodology
Bingyang Guo, Qiang Zuo, Ruiyun Yu
The effective segmentation of 3D data is crucial for a wide range of industrial applications, especially for detecting subtle defects in the field of integrated circuits (IC). Cera…