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Emilio Maddalena

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Emilio Maddalena

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Machine Learning Methods for Robust Uncertainty Quantification and Controller Approximation

Lessons Learned from Data-Driven Building Control Experiments: Contrasting Gaussian Process-based MPC, Bilevel DeePC, and Deep Reinforcement Learning

Experimental data-driven model predictive control of a hospital HVAC system during regular use

Deterministic error bounds for kernel-based learning techniques under bounded noise

KPC: Learning-Based Model Predictive Control with Deterministic Guarantees

Embedded PWM Predictive Control of DC-DC Power Converters Via Piecewise-Affine Neural Networks

Data-driven methods for building control - A review and promising future directions

NSM Converges to a k-NN Regressor Under Loose Lipschitz Estimates

Discrete-time regional pole-placement using convex approximations: Theory and application to a boost converter

Learning Non-Parametric Models with Guarantees: A Smooth Lipschitz Interpolation Approach