13 citations · 19 across the 11 of their papers we have counts for
8 papers · 1 filter
Sparse optimal control in the Wasserstein space
Enrico Sartor, Florian Dörfler, Nicolas Lanzetti
We study sparse optimal control of a non-local continuity equation, where the goal is to steer a distribution via finitely many controllable agents or actuators. This model arises…
Hedging against Black Swans in Day-Ahead Energy Markets
Liviu Aolaritei, Boubacar Bangoura, Saverio Bolognani +2
Renewable generators must commit to day-ahead market bids despite uncertainty in both production and real-time prices. While forecasts provide valuable guidance, rare and unpredict…
Distributionally Robust Linear Quadratic Gaussian Regulator with Stationary Distributions
Alain Schöbi, Nicolas Lanzetti, Florian Dörfler +2
We study the Linear Quadratic Gaussian regulation problem in the face of worst-case noise distributions when these are mutually independent, zero-mean, stationary, and within a rad…
Variational Analysis in the Wasserstein Space
Nicolas Lanzetti, Antonio Terpin, Florian Dörfler
We study optimization problems whereby the optimization variable is a probability measure. Since the space of probability measures is not a vector space, many classical methods for…
Capture, Propagate, and Control Distributional Uncertainty
Liviu Aolaritei, Nicolas Lanzetti, Florian Dörfler
We study stochastic dynamical systems in settings where only partial statistical information about the noise is available, e.g., in the form of a limited number of noise realizatio…
Dynamic Programming in Probability Spaces via Optimal Transport
Antonio Terpin, Nicolas Lanzetti, Florian Dörfler
We study discrete-time finite-horizon optimal control problems in probability spaces, whereby the state of the system is a probability measure. We show that, in many instances, the…
First-order Conditions for Optimization in the Wasserstein Space
Nicolas Lanzetti, Saverio Bolognani, Florian Dörfler
We study first-order optimality conditions for constrained optimization in the Wasserstein space, whereby one seeks to minimize a real-valued function over the space of probability…
Distributional Uncertainty Propagation via Optimal Transport
Liviu Aolaritei, Nicolas Lanzetti, Hongruyu Chen +1
This paper addresses the limitations of standard uncertainty models, e.g., robust (norm-bounded) and stochastic (one fixed distribution, e.g., Gaussian), and proposes to model unce…