27 citations · 87 across the 9 of their papers we have counts for
11 papers
Monte Carlo Tree Descent for Black-Box Optimization
Yaoguang Zhai, Sicun Gao
The key to Black-Box Optimization is to efficiently search through input regions with potentially widely-varying numerical properties, to achieve low-regret descent and fast progre…
Policy Optimization with Advantage Regularization for Long-Term Fairness in Decision Systems
Eric Yang Yu, Zhizhen Qin, Min Kyung Lee +1
Long-term fairness is an important factor of consideration in designing and deploying learning-based decision systems in high-stake decision-making contexts. Recent work has propos…
Learning Control Admissibility Models with Graph Neural Networks for Multi-Agent Navigation
Chenning Yu, Hongzhan Yu, Sicun Gao
Deep reinforcement learning in continuous domains focuses on learning control policies that map states to distributions over actions that ideally concentrate on the optimal choices…
Reducing Collision Checking for Sampling-Based Motion Planning Using Graph Neural Networks
Chenning Yu, Sicun Gao
Sampling-based motion planning is a popular approach in robotics for finding paths in continuous configuration spaces. Checking collision with obstacles is the major computational…
Safe Nonlinear Control Using Robust Neural Lyapunov-Barrier Functions
Charles Dawson, Zengyi Qin, Sicun Gao +1
Safety and stability are common requirements for robotic control systems; however, designing safe, stable controllers remains difficult for nonlinear and uncertain models. We devel…
Stabilizing Neural Control Using Self-Learned Almost Lyapunov Critics
Ya-Chien Chang, Sicun Gao
The lack of stability guarantee restricts the practical use of learning-based methods in core control problems in robotics. We develop new methods for learning neural control polic…