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20222026
most citedLearn to Bid as a Price-Maker Wind Power Producer

2 citations · 4 across the 12 of their papers we have counts for

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10 papers · 1 filter

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

Loss-aware distributionally robust optimization via trainable optimal transport ambiguity sets

Jonas Ohnemus, Marta Fochesato, Riccardo Zuliani +1

Optimal-Transport Distributionally Robust Optimization (OT-DRO) robustifies data-driven decision-making under uncertainty by capturing the sampling-induced statistical error via op…

math.OC2025

Synthesis of safety certificates for discrete-time uncertain systems via convex optimization

Marta Fochesato, Han Wang, Antonis Papachristodoulou +1

We study the problem of co-designing control barrier functions and linear state feedback controllers for discrete-time linear systems affected by additive disturbances. For disturb…

math.OC2025

Distributionally Robust LQG with Kullback-Leibler Ambiguity Sets

Marta Fochesato, Lucia Falconi, Mattia Zorzi +2

The Linear Quadratic Gaussian (LQG) controller is known to be inherently fragile to model misspecifications common in real-world situations. We consider discrete-time partially obs…

math.OC2025

Distributionally Robust Optimization over Wasserstein Balls with i.i.d. Structure

Andrey Kharitenko, Marta Fochesato, Anastasios Tsiamis +2

We consider distributionally robust optimization problems where the uncertainty is modeled via a structured Wasserstein ambiguity set. Specifically, the ambiguity is restricted to…

math.OC2024

Joint Chance Constrained Optimal Control via Linear Programming

Niklas Schmid, Marta Fochesato, Tobias Sutter +1

We establish a linear programming formulation for the solution of joint chance constrained optimal control problems over finite time horizons. The joint chance constraint may repre…

math.OC2023★ 1 cited

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…

math.OC2023

Wasserstein Tube MPC with Exact Uncertainty Propagation

Liviu Aolaritei, Marta Fochesato, John Lygeros +1

We study model predictive control (MPC) problems for stochastic LTI systems, where the noise distribution is unknown, compactly supported, and only observable through a limited num…

math.OC2023

Designing Optimal Personalized Incentive for Traffic Routing using BIG Hype algorithm

Panagiotis D. Grontas, Carlo Cenedese, Marta Fochesato +3

We study the problem of optimally routing plug-in electric and conventional fuel vehicles on a city level. In our model, commuters selfishly aim to minimize a local cost that combi…

math.OC2023★ 1 cited

BIG Hype: Best Intervention in Games via Distributed Hypergradient Descent

Panagiotis D. Grontas, Giuseppe Belgioioso, Carlo Cenedese +3

Hierarchical decision making problems, such as bilevel programs and Stackelberg games, are attracting increasing interest in both the engineering and machine learning communities.…