Approximating networks, dynamic programming and stochastic approximation. - Marco Baglietto; Cristiano Cervellera; Thomas Parisini; Marcello Sanguineti; N. Zoppoli (ACC, 2000)

Optimal neural feedback control applied to a problem of economic growth in freight transport market. - Angelo Alessandri; Cristiano Cervellera; Filippo Aldo Grassia (CDC, 2002)

Application of neural control to economic growth problems. - Angelo Alessandri; Cristiano Cervellera; Filippo Aldo Grassia (CIFEr, 2003)

A Deterministic Learning Approch Based on Discrepancy. - Cristiano Cervellera; Marco Muselli (WIRN, 2003)

Design of observers for continuous-time nonlinear systems using neural networks. - Angelo Alessandri; Cristiano Cervellera; Filippo Aldo Grassia; Marcello Sanguineti (ACC, 2004)

Deterministic design for neural network learning: an approach based on discrepancy. - Cristiano Cervellera; Marco Muselli (IEEE Trans. Neural Networks, 2004)

An approximate solution to optimal Lp state estimation problems. - Angelo Alessandri; Cristiano Cervellera; Filippo Aldo Grassia; Marcello Sanguineti (ACC, 2005)

Design of Parameterized State Observers and Controllers for a Class of Nonlinear Continuous-Time Systems. - Angelo Alessandri; Cristiano Cervellera; Danilo Macciò; Marcello Sanguineti (CDC, 2006)

Optimization of a large-scale water reservoir network by stochastic dynamic programming with efficient state space discretization. - Cristiano Cervellera; Victoria C. P. Chen; Aihong Wen (Eur. J. Oper. Res., 2006)

Efficient sampling in approximate dynamic programming algorithms. - Cristiano Cervellera; Marco Muselli (Comput. Optim. Appl., 2007)

Design of a peer-to-peer system for optimized content replication. - Luca Caviglione; Cristiano Cervellera (Comput. Commun., 2007)

Neural network and regression spline value function approximations for stochastic dynamic programming. - Cristiano Cervellera; Aihong Wen; Victoria C. P. Chen (Comput. Oper. Res., 2007)

Design of Asymptotic Estimators: An Approach Based on Neural Networks and Nonlinear Programming. - Angelo Alessandri; Cristiano Cervellera; Marcello Sanguineti (IEEE Trans. Neural Networks, 2007)

Nonlinear predictive control for the management of container flows in maritime intermodal terminals. - Angelo Alessandri; Cristiano Cervellera; Marta Cuneo; Mauro Gaggero (CDC, 2008)

Optimization of an eMule-like modifier strategy. - Luca Caviglione; Cristiano Cervellera; Franco Davoli; Filippo Aldo Grassia (Comput. Commun., 2008)

Modeling and Feedback Control for Resource Allocation and Performance Analysis in Container Terminals. - Angelo Alessandri; Cristiano Cervellera; Marta Cuneo; Mauro Gaggero; G. Soncin (IEEE Trans. Intell. Transp. Syst., 2008)

Deterministic Learning for Maximum-Likelihood Estimation Through Neural Networks. - Cristiano Cervellera; Danilo Macciò; Marco Muselli (IEEE Trans. Neural Networks, 2008)

Optimization of a peer-to-peer system for efficient content replication. - Cristiano Cervellera; Luca Caviglione (Eur. J. Oper. Res., 2009)

Management of water resource systems in the presence of uncertainties by nonlinear approximation techniques and deterministic sampling. - Marco Baglietto; Cristiano Cervellera; Marcello Sanguineti; Riccardo Zoppoli (Comput. Optim. Appl., 2010)

Functional Optimization Through Semilocal Approximate Minimization. - Cristiano Cervellera; Danilo Macciò; Marco Muselli (Oper. Res., 2010)

Efficient global maximum likelihood estimation through kernel methods. - Cristiano Cervellera; Danilo Macciò; Marco Muselli (Neural Networks, 2010)

Lattice point sets for deterministic learning and approximate optimization problems. - Cristiano Cervellera (IEEE Trans. Neural Networks, 2010)

Design, optimization and performance evaluation of a content distribution overlay for streaming. - Luca Caviglione; Cristiano Cervellera (Comput. Commun., 2011)

A comparison of global and semi-local approximation in T-stage stochastic optimization. - Cristiano Cervellera; Danilo Macciò (Eur. J. Oper. Res., 2011)

An Optimized Content Replication and Distribution Framework for Vehicular Networks. - Luca Caviglione; Cristiano Cervellera (J. Intell. Transp. Syst., 2011)

A numerical method for minimum distance estimation problems. - Cristiano Cervellera; Danilo Macciò (J. Multivar. Anal., 2011)

Local Models for data-driven learning of control policies for complex systems. - Danilo Macciò; Cristiano Cervellera (Expert Syst. Appl., 2012)

Efficient kernel models for learning and approximate minimization problems. - Cristiano Cervellera; Mauro Gaggero; Danilo Macciò (Neurocomputing, 2012)

Quasi-random sampling for approximate dynamic programming. - Cristiano Cervellera; Mauro Gaggero; Danilo Macciò; Roberto Marcialis (IJCNN, 2013)

Function learning with local linear regression models: An analysis based on discrepancy. - Cristiano Cervellera; Danilo Macciò; Roberto Marcialis (IJCNN, 2013)

Predictive Control of Container Flows in Maritime Intermodal Terminals. - Angelo Alessandri; Cristiano Cervellera; Mauro Gaggero (IEEE Trans. Control. Syst. Technol., 2013)

Learning With Kernel Smoothing Models and Low-Discrepancy Sampling. - Cristiano Cervellera; Danilo Macciò (IEEE Trans. Neural Networks Learn. Syst., 2013)

Editorial A Successful Change From TNN to TNNLS and a Very Successful Year. - Derong Liu 001; Charles Anderson 001; Ahmad Taher Azar; Giorgio Battistelli; Eduardo Bayro-Corrochano; Cristiano Cervellera; David A. Elizondo; Maurizio Filippone; Giorgio Gnecco; Xiaolin Hu; Tingwen Huang; Weifeng Liu 001; et al. (IEEE Trans. Neural Networks Learn. Syst., 2013)

An analysis based on F-discrepancy for sampling in regression tree learning. - Cristiano Cervellera; Mauro Gaggero; Danilo Macciò (IJCNN, 2014)

An approach to exploit non-optimized data for efficient control of unknown systems through neural and kernel models. - Cristiano Cervellera; Mauro Gaggero; Danilo Macciò; Roberto Marcialis (IJCNN, 2014)

Lattice sampling for efficient learning with Nadaraya-Watson local models. - Cristiano Cervellera; Mauro Gaggero; Danilo Macciò; Roberto Marcialis (IJCNN, 2014)

Low-discrepancy sampling for approximate dynamic programming with local approximators. - Cristiano Cervellera; Mauro Gaggero; Danilo Macciò (Comput. Oper. Res., 2014)

Modelling of Fault Detection and Diagnostics for Hybrid Bus Using Chain Graph Models. - Diana Flaccadoro; Cristiano Cervellera; Giorgio Bosia; Eva Riccomagno (Qual. Reliab. Eng. Int., 2014)

Local Linear Regression for Function Learning: An Analysis Based on Sample Discrepancy. - Cristiano Cervellera; Danilo Macciò (IEEE Trans. Neural Networks Learn. Syst., 2014)

Lattice point sets for efficient kernel smoothing models. - Cristiano Cervellera; Mauro Gaggero; Danilo Macciò; Roberto Marcialis (IJCNN, 2015)

Efficient use of Nadaraya-Watson models and low-discrepancy sequences for approximate dynamic programming. - Cristiano Cervellera; Mauro Gaggero; Danilo Macciò; Roberto Marcialis (IJCNN, 2015)

F-Discrepancy for Efficient Sampling in Approximate Dynamic Programming. - Cristiano Cervellera; Danilo Macciò (IEEE Trans. Cybern., 2016)

Low-Discrepancy Points for Deterministic Assignment of Hidden Weights in Extreme Learning Machines. - Cristiano Cervellera; Danilo Macciò (IEEE Trans. Neural Networks Learn. Syst., 2016)

Uniform histograms for change detection in multivariate data. - Giacomo Boracchi; Cristiano Cervellera; Danilo Macciò (IJCNN, 2017)

An Extreme Learning Machine Approach to Density Estimation Problems. - Cristiano Cervellera; Danilo Macciò (IEEE Trans. Cybern., 2017)

A Novel Approach for Sampling in Approximate Dynamic Programming Based on F-Discrepancy. - Cristiano Cervellera; Danilo Macciò (IEEE Trans. Cybern., 2017)

QuantTree: Histograms for Change Detection in Multivariate Data Streams. - Giacomo Boracchi; Diego Carrera; Cristiano Cervellera; Danilo Macciò (ICML, 2018)

Distribution-Preserving Stratified Sampling for Learning Problems. - Cristiano Cervellera; Danilo Macciò (IEEE Trans. Neural Networks Learn. Syst., 2018)

An Improved Load Flow Method for MV Networks Based on LV Load Measurements and Estimations. - Antonio Cataliotti; Cristiano Cervellera; Valentina Cosentino; Dario Di Cara; Mauro Gaggero; Danilo Macciò; Giuseppe Marsala; Antonella Ragusa; Giovanni Tinè (IEEE Trans. Instrum. Meas., 2019)

Learning Robustly Stabilizing Explicit Model Predictive Controllers: A Non-Regular Sampling Approach. - Cristiano Cervellera; Danilo Macciò; Thomas Parisini (IEEE Control. Syst. Lett., 2020)

Voronoi tree models for distribution-preserving sampling and generation. - Cristiano Cervellera; Danilo Macciò (Pattern Recognit., 2020)

Policy Optimization for Berth Allocation Problems. - Cristiano Cervellera; Mauro Gaggero; Danilo Macciò (IJCNN, 2021)

Deep Learning and Low-discrepancy Sampling for Surrogate Modeling with an Application to Urban Traffic Simulation. - Cristiano Cervellera; Danilo Macciò; Francesco Rebora (IJCNN, 2021)

Echo state network ensembles for surrogate models with an application to urban mobility. - Cristiano Cervellera; Danilo Macciò; Francesco Rebora (IJCNN, 2022)

Copula-based scenario generation for urban traffic models. - Cristiano Cervellera; Danilo Macciò; Francesco Rebora (Expert Syst. Appl., 2022)

Improving the variability of urban traffic microsimulation through the calibration of generative parameter models. - Cristiano Cervellera; Danilo Macciò; Francesco Rebora (J. Intell. Transp. Syst., 2022)

An imitation learning approach for the control of a low-cost low-accuracy robotic arm for unstructured environments. - Fabio Bonsignorio; Cristiano Cervellera; Danilo Macciò; Enrica Zereik (Int. J. Intell. Robotics Appl., 2023)

Optimized ensemble value function approximation for dynamic programming. - Cristiano Cervellera (Eur. J. Oper. Res., 2023)

Simulation and Neural Models for Traffic Light Importance Analysis in Urban Networks. - Cristiano Cervellera; Danilo Macciò; Francesco Rebora (MESA, 2024)

Model Predictive Control of Port-City Traffic Interactions Over Shared Urban Infrastructure. - Cristiano Cervellera; Danilo Macciò; Francesco Rebora (IEEE Trans. Control. Syst. Technol., 2024)

Assessing Mobility Policies by Traffic Simulation and Change Detection. - Felipe Bagni; Edoardo Peretti; Danilo Macciò; Cristiano Cervellera; Giacomo Boracchi (EANN (2), 2025)

Deep Learning and Low-Discrepancy Sampling for Efficient Approximate Dynamic Programming. - Cristiano Cervellera; Danilo Macciò (IJCNN, 2025)

Binary Voronoi linear trees for the approximate solution of functional optimization problems. - Cristiano Cervellera; Danilo Macciò (Comput. Appl. Math., 2025)

Model predictive control of port-city scenarios based on traffic simulation and efficient sampling design. - Cristiano Cervellera; Danilo Macciò (Expert Syst. Appl., 2026)