3 papers
math.OC2026
Joint Chance Constrained Safe-Optimal Control
Niklas Schmid, Jared Miller, Tristan Zeller +3
We consider the finite-time optimal control of stochastic systems subject to a probabilistic constraint on the trajectories' safety. Such formulations are known as joint chance con…
math.OC2025
Policy Gradient Algorithms for Robust MDPs with Non-Rectangular Uncertainty Sets
Mengmeng Li, Daniel Kuhn, Tobias Sutter
We propose policy gradient algorithms for robust infinite-horizon Markov decision processes (MDPs) with non-rectangular uncertainty sets, thereby addressing an open challenge in th…
stat.ML2025
Optimal Learning via Moderate Deviations Theory
Arnab Ganguly, Tobias Sutter
This paper proposes a statistically optimal approach for learning a function value using a confidence interval in a wide range of models, including general non-parametric estimatio…