2 citations · 2 across the 4 of their papers we have counts for
4 papers
Polynomial Optimization via Random Projection and Consensus
Etienne Buehrle, Christoph Stiller
We propose a black-box approach to reducing large semidefinite programs to a set of smaller semidefinite programs by projecting to random linear subspaces. We evaluate our method o…
Stochastic Optimal Control via Measure Relaxations
Etienne Buehrle, Christoph Stiller
The optimal control problem of stochastic systems is commonly solved via robust or scenario-based optimization methods, which are both challenging to scale to long optimization hor…
Optimal Control of Hybrid Systems via Measure Relaxations
Etienne Buehrle, Ömer Şahin Taş, Christoph Stiller
We propose an approach to trajectory optimization for piecewise polynomial systems based on the recently proposed graphs of convex sets framework. We instantiate the framework with…
SHAIL: Safety-Aware Hierarchical Adversarial Imitation Learning for Autonomous Driving in Urban Environments
Arec Jamgochian, Etienne Buehrle, Johannes Fischer +1
Designing a safe and human-like decision-making system for an autonomous vehicle is a challenging task. Generative imitation learning is one possible approach for automating policy…