3 papers
cs.LG2025
Wasserstein Distributionally Robust Bayesian Optimization with Continuous Context
Francesco Micheli, Efe C. Balta, Anastasios Tsiamis +1
We address the challenge of sequential data-driven decision-making under context distributional uncertainty. This problem arises in numerous real-world scenarios where the learner…
math.OC2025
Semismooth Newton Methods for Risk-Averse Markov Decision Processes
Matilde Gargiani, Francesco Micheli, Anastasios Tsiamis +1
Inspired by semismooth Newton methods, we propose a general framework for designing solution methods with convergence guarantees for risk-averse Markov decision processes. Our appr…
math.OC2024
Data-Driven Distributionally Robust System Level Synthesis
Francesco Micheli, Anastasios Tsiamis, John Lygeros
We present a novel approach for the control of uncertain, linear time-invariant systems, which are perturbed by potentially unbounded, additive disturbances. We propose a \emph{dou…