48 citations · 294 across the 36 of their papers we have counts for
5 papers · 1 filter
Unconstrained learning of networked nonlinear systems via free parametrization of stable interconnected operators
Leonardo Massai, Danilo Saccani, Luca Furieri +1
This paper characterizes a new parametrization of nonlinear networked incrementally -bounded operators in discrete time. The distinctive novelty is that our parametrization is…
Closing the Gap to Quadratic Invariance: a Regret Minimization Approach to Optimal Distributed Control
Daniele Martinelli, Andrea Martin, Giancarlo Ferrari-Trecate +1
In this work, we focus on the design of optimal controllers that must comply with an information structure. State-of-the-art approaches do so based on the H2 or Hinfty norm to mini…
On the Guarantees of Minimizing Regret in Receding Horizon
Andrea Martin, Luca Furieri, Florian Dörfler +2
Towards bridging classical optimal control and online learning, regret minimization has recently been proposed as a control design criterion. This competitive paradigm penalizes th…
Regret Optimal Control for Uncertain Stochastic Systems
Andrea Martin, Luca Furieri, Florian Dörfler +2
We consider control of uncertain linear time-varying stochastic systems from the perspective of regret minimization. Specifically, we focus on the problem of designing a feedback c…
Unconstrained Parametrization of Dissipative and Contracting Neural Ordinary Differential Equations
Daniele Martinelli, Clara Lucía Galimberti, Ian R. Manchester +2
In this work, we introduce and study a class of Deep Neural Networks (DNNs) in continuous-time. The proposed architecture stems from the combination of Neural Ordinary Differential…