Author

Filippo Fabiani

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Preprint Sep 2026

Finite-sample guarantees for data-driven operator splitting methods via martingale inequalities

Operator splitting methods are a fundamental class of algorithms for solving structured monotone inclusion problems arising in optimization, control, and game theory. We consider the case, common in stochastic regimes, where the forward evaluation of one of the constituent operators is either unavailable in closed form...

Andrea Martin, Filippo Fabiani, Giuseppe Belgioioso · 0 citations

#machine learning Preprint Aug 2026

Generalization as a robust performance property of learning-enabled dynamical systems

This work provides a system-theoretic interpretation of generalization in learning-enabled dynamical systems arising in data-driven optimization and feedback control approximation, and establishes a matrix inequality-based certificate and a uniform stability bound that separates the one-sample sensitivity of the learne...

Filippo Fabiani · 0 citations