Distributionally Robust Optimization using Cost-Aware Ambiguity Sets

no code implementations • 16 Mar 2023 • Mathijs Schuurmans, Panagiotis Patrinos

We present a novel framework for distributionally robust optimization (DRO), called cost-aware DRO (CADRO).

Safe, Learning-Based MPC for Highway Driving under Lane-Change Uncertainty: A Distributionally Robust Approach

no code implementations • 27 Jun 2022 • Mathijs Schuurmans, Alexander Katriniok, Christopher Meissen, H. Eric Tseng, Panagiotis Patrinos

We present a case study applying learning-based distributionally robust model predictive control to highway motion planning under stochastic uncertainty of the lane change behavior of surrounding road users.

Model Predictive Control Motion Planning

Efficient semantic image segmentation with superpixel pooling

1 code implementation • 7 Jun 2018 • Mathijs Schuurmans, Maxim Berman, Matthew B. Blaschko

In this work, we evaluate the use of superpixel pooling layers in deep network architectures for semantic segmentation.

Image Segmentation Semantic Segmentation