Model Predictive Control of Port-City Traffic Interactions Over Shared Urban Infrastructure von Cervellera, Cristiano, Maccio, Danilo, Rebora, Francesco

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Voronoi tree models for distribution-preserving sampling and generation von Cervellera, Cristiano, Macciò, Danilo

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Copula-based scenario generation for urban traffic models von Cervellera, Cristiano, Macciò, Danilo, Rebora, Francesco

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Low-Discrepancy Points for Deterministic Assignment of Hidden Weights in Extreme Learning Machines von Cervellera, Cristiano, Maccio, Danilo

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Local linear regression for efficient data-driven control von Maccio, Danilo

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Local Linear Regression for Function Learning: An Analysis Based on Sample Discrepancy von Cervellera, Cristiano, Maccio, Danilo

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Learning With Kernel Smoothing Models and Low-Discrepancy Sampling von Cervellera, Cristiano, Maccio, Danilo

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An imitation learning approach for the control of a low-cost low-accuracy robotic arm for unstructured environments von Bonsignorio, Fabio, Cervellera, Cristiano, Macciò, Danilo, Zereik, Enrica

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F -Discrepancy for Efficient Sampling in Approximate Dynamic Programming von Cervellera, Cristiano, Maccio, Danilo

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Lattice point sets for state sampling in approximate dynamic programming von Cervellera, Cristiano, Gaggero, Mauro, Macciò, Danilo

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Functional Optimization Through Semilocal Approximate Minimization von Cervellera, Cristiano, Macciò, Danilo, Muselli, Marco

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Distribution-Preserving Stratified Sampling for Learning Problems von Cervellera, Cristiano, Maccio, Danilo

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Efficient global maximum likelihood estimation through kernel methods von Cervellera, Cristiano, Macciò, Danilo, Muselli, Marco

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An Extreme Learning Machine Approach to Density Estimation Problems von Cervellera, Cristiano, Maccio, Danilo

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Deterministic Learning for Maximum-Likelihood Estimation Through Neural Networks von Cervellera, C., Maccio, D., Muselli, M.

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A Novel Approach for Sampling in Approximate Dynamic Programming Based on F -Discrepancy von Cervellera, Cristiano, Maccio, Danilo

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[Formula Omitted]-Discrepancy for Efficient Sampling in Approximate Dynamic Programming von Cervellera, Cristiano, Maccio, Danilo

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Learning Robustly Stabilizing Explicit Model Predictive Controllers: A Non-Regular Sampling Approach von Cervellera, Cristiano, Maccio, Danilo, Parisini, Thomas

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An Improved Load Flow Method for MV Networks Based on LV Load Measurements and Estimations von Cataliotti, Antonio, Cervellera, Cristiano, Cosentino, Valentina, Di Cara, Dario, Gaggero, Mauro, Maccio, Danilo, Marsala, Giuseppe, Ragusa, Antonella, Tine, Giovanni

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Low-discrepancy sampling for approximate dynamic programming with local approximators von Cervellera, C., Gaggero, M., Macciò, D.

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