7 papers
Effective nonvanishing of -trivial regular surfaces over imperfect fields
Jingshan Chen, Chongning Wang, Lei Zhang
For any regular projective surface over an arbitrary field of characteristic with , we prove that \[ 60K_X\sim0 . \] This uniform bound is optimal. To sho…
PolyMerge: Compressing 3D Gaussian Splats with Polytope Coverings for Provably Safe Resource-Constrained Navigation
Jihoon Hong, Chih-Yuan Chiu, Sara Fridovich-Keil +1
Obstacle avoidance is essential for safe navigation and motion planning. Recent radiance field reconstruction methods enable object detection and modeling with high fidelity, but r…
Over-Approximating Minimizer Sets of Constrained Convex Programs with Parametric Uncertainty via Reachability Analysis
Brendan Gould, Chih-Yuan Chiu, Antoine P. Leeman +3
We study the set of solutions to a parameterized, strongly convex optimization problem whose cost depends on uncertain, bounded parameters. We compute a certified outer approximati…
Active Constraint Learning in High Dimensions from Demonstrations
Zheng Qiu, Chih-Yuan Chiu, Glen Chou
We present an iterative active constraint learning (ACL) algorithm, within the learning from demonstrations (LfD) paradigm, which intelligently solicits informative demonstration t…
Robustly Constrained Dynamic Games for Uncertain Nonlinear Dynamics
Shuyu Zhan, Chih-Yuan Chiu, Antoine P. Leeman +1
We propose a novel framework for robust dynamic games with nonlinear dynamics corrupted by state-dependent additive noise, and nonlinear agent-specific and shared constraints. Leve…
Learning Constraints from Stochastic Partially-Observed Closed-Loop Demonstrations
Chih-Yuan Chiu, Zhouyu Zhang, Glen Chou
We present a method for learning unknown parametric constraints from locally-optimal input-output trajectory data. We assume the data is generated by rollouts of stochastic nonline…
Constraint Learning in Multi-Agent Dynamic Games from Demonstrations of Local Nash Interactions
Zhouyu Zhang, Chih-Yuan Chiu, Glen Chou
We present an inverse dynamic game-based algorithm to learn parametric constraints from a given dataset of local Nash equilibrium interactions between multiple agents. Specifically…