23 citations · 30 across the 10 of their papers we have counts for
12 papers
Graph-Enhanced Disease Trajectory Discovery and Temporal Endpoint Forecasting from Longitudinal Electronic Health Records
Jin-Jia Zheng, Vincent S. Tseng
Longitudinal electronic health records (EHRs) can reveal disease-progression structure, while useful forecasting requires leakage-controlled discovery, censor-aware outcomes, and i…
Score-Calibrated Flow for Sampling from Unnormalized Densities with Applications to Generative Online Reinforcement Learning
Zeyang Li, Yunan Wang, Risheek Garrepalli +2
Diffusion and flow models provide expressive policy classes for online reinforcement learning (RL), enabling multimodal behaviors and improved performance. However, training these…
G6D: Geometric Learning-Free RGB-D 6D Pose Solver for Robotic Manipulation
Yixuan Liang, William Chen, Yunan Wang +4
6D object pose estimation is fundamental to robotic manipulation and automation. Recent zero-shot methods have significantly improved generalization to unseen objects, but most sti…
Group-Graph Policy Optimization for Long-Horizon Agentic Reinforcement Learning
Yunan Wang, Minghui Song, Zihan Zhang +6
Group-based Reinforcement Learning (RL) has significantly enhanced Large Language Models (LLMs) in agentic scenarios. To achieve finer-grained policy updates, recent agentic RL fra…
Reachability-Augmented Dual Dynamic Programming for Optimal Path Parameterization
Yunan Wang, Jizhou Yan, Chuxiong Hu +1
Optimal path parameterization (OPP) is a fundamental problem for planning trajectories along a prescribed geometric path under kinodynamic constraints and task-dependent objectives…
Time-Optimal Switching Surfaces for Triple Integrator under Full Box Constraints
Yunan Wang, Chuxiong Hu, Zhao Jin
Time-optimal control for triple integrator under full box constraints is a fundamental problem in the field of optimal control, which has been widely applied in the industry. Howev…
A Novel State-Centric Necessary Condition for Time-Optimal Control of Controllable Linear Systems Based on Augmented Switching Laws (Extended Version)
Yunan Wang, Chuxiong Hu, Yujie Lin +3
Most existing necessary conditions for optimal control based on adjoining methods require both state and costate information, yet the unobservability of costates for a given feasib…
Chattering Phenomena in Time-Optimal Control for High-Order Chain-of-Integrator Systems with Full State Constraints (Extended Version)
Yunan Wang, Chuxiong Hu, Zeyang Li +3
Time-optimal control for high-order chain-of-integrator systems with full state constraints remains an open and challenging problem within the discipline of optimal control. The be…
Time-Optimal Control for High-Order Chain-of-Integrators Systems with Full State Constraints and Arbitrary Terminal States (Extended Version)
Yunan Wang, Chuxiong Hu, Zeyang Li +3
Time-optimal control for high-order chain-of-integrators systems with full state constraints and arbitrarily given terminal states remains a challenging problem in the optimal cont…
Robust Safe Reinforcement Learning under Adversarial Disturbances
Zeyang Li, Chuxiong Hu, Shengbo Eben Li +2
Safety is a primary concern when applying reinforcement learning to real-world control tasks, especially in the presence of external disturbances. However, existing safe reinforcem…
Bridging the Gap between Newton-Raphson Method and Regularized Policy Iteration
Zeyang Li, Chuxiong Hu, Yunan Wang +4
Regularization is a cornerstone of modern reinforcement learning. Regularized policy iteration (RPI) provides a fundamental scheme for solving regularized Markov decision processes…
Safe Reinforcement Learning with Dual Robustness
Zeyang Li, Chuxiong Hu, Yunan Wang +2
Reinforcement learning (RL) agents are vulnerable to adversarial disturbances, which can deteriorate task performance or compromise safety specifications. Existing methods either a…