137 citations · 248 across the 25 of their papers we have counts for
3 papers · 2 filters
Computing Optimal Joint Chance Constrained Control Policies
Niklas Schmid, Marta Fochesato, Sarah H. Q. Li +2
We consider the problem of optimally controlling stochastic, Markovian systems subject to joint chance constraints over a finite-time horizon. For such problems, standard Dynamic P…
End-to-End Learning for Stochastic Optimization: A Bayesian Perspective
Yves Rychener, Daniel Kuhn, Tobias Sutter
We develop a principled approach to end-to-end learning in stochastic optimization. First, we show that the standard end-to-end learning algorithm admits a Bayesian interpretation…
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…