Marcello Sanguineti

According to our database1, Marcello Sanguineti authored at least 88 papers between 1998 and 2020.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of two.



In proceedings 
PhD thesis 




Automated Analysis of the Origin of Movement: An Approach Based on Cooperative Games on Graphs.
IEEE Trans. Hum. Mach. Syst., 2020

Transboundary pollution control and environmental absorption efficiency management.
Ann. Oper. Res., 2020

A Computational Method to Automatically Detect the Perceived Origin of Full-Body Human Movement and its Propagation.
Proceedings of the Companion Publication of the 2020 International Conference on Multimodal Interaction, 2020

Classification by Sparse Neural Networks.
IEEE Trans. Neural Networks Learn. Syst., 2019

Some properties of transportation network cooperative games.
Networks, 2019

Probabilistic Bounds for Binary Classification of Large Data Sets.
Proceedings of the Recent Advances in Big Data and Deep Learning, 2019

On the Optimal Selection of Motors and Transmissions for a Back-Support Exoskeleton.
Proceedings of the 2019 IEEE International Conference on Cyborg and Bionic Systems, 2019

Neural approximations in discounted infinite-horizon stochastic optimal control problems.
Eng. Appl. Artif. Intell., 2018

Probabilistic Bounds on Complexity of Networks Computing Binary Classification Tasks.
Proceedings of the 18th Conference Information Technologies, 2018

Supervised and semi-supervised classifiers for the detection of flood-prone areas.
Soft Comput., 2017

A theoretical analysis of buffer occupancy for Intermittently-Connected Networks.
Perform. Evaluation, 2017

Probabilistic lower bounds for approximation by shallow perceptron networks.
Neural Networks, 2017

LQG Online Learning.
Neural Comput., 2017

Graph-restricted game approach for investigating human movement qualities.
Proceedings of the 4th International Conference on Movement Computing, 2017

Model complexities of shallow networks representing highly varying functions.
Neurocomputing, 2016

Learning with hard constraints as a limit case of learning with soft constraints.
Proceedings of the 24th European Symposium on Artificial Neural Networks, 2016

Learning With Mixed Hard/Soft Pointwise Constraints.
IEEE Trans. Neural Networks Learn. Syst., 2015

Foundations of Support Constraint Machines.
Neural Comput., 2015

Narrowing the Search for Optimal Call-Admission Policies Via a Nonlinear Stochastic Knapsack Model.
J. Optim. Theory Appl., 2015

A Multimodal Dataset for the Analysis of Movement Qualities in Karate Martial Art.
EAI Endorsed Trans. Collab. Comput., 2015

Online learning as an LQG optimal control problem with random matrices.
Proceedings of the 14th European Control Conference, 2015

A theoretical framework for supervised learning from regions.
Neurocomputing, 2014

On the detection of the level of attention in an orchestra through head movements.
Int. J. Arts Technol., 2014

Evaluation of the Average Packet Delivery Delay in Highly-Disrupted Networks: The DTN and IP-like Protocol Cases.
IEEE Commun. Lett., 2014

Approximate dynamic programming for stochastic <i>N</i>-stage optimization with application to optimal consumption under uncertainty.
Comput. Optim. Appl., 2014

Complexity of Shallow Networks Representing Functions with Large Variations.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2014, 2014

Approximating Multivariable Functions by Feedforward Neural Nets.
Proceedings of the Handbook on Neural Information Processing, 2013

Optimality Conditions for Coordinate-Convex Policies in CAC With Nonlinear Feasibility Boundaries.
IEEE/ACM Trans. Netw., 2013

Learning with Boundary Conditions.
Neural Comput., 2013

Dynamic Programming and Value-Function Approximation in Sequential Decision Problems: Error Analysis and Numerical Results.
J. Optim. Theory Appl., 2013

Can Two Hidden Layers Make a Difference?
Proceedings of the Adaptive and Natural Computing Algorithms, 2013

Learning with Hard Constraints.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2013, 2013

Towards Automated Analysis of Joint Music Performance in the Orchestra.
Proceedings of the Arts and Technology, Third International Conference, 2013

Dependence of Computational Models on Input Dimension: Tractability of Approximation and Optimization Tasks.
IEEE Trans. Inf. Theory, 2012

Suboptimal Solutions to Team Optimization Problems with Stochastic Information Structure.
SIAM J. Optim., 2012

New insights into Witsenhausen's counterexample.
Optim. Lett., 2012

A Model of Buffer Occupancy for ICNs.
IEEE Commun. Lett., 2012

Accuracy of approximations of solutions to Fredholm equations by kernel methods.
Appl. Math. Comput., 2012

An application to two-hop forwarding of a model of buffer occupancy in ICNs.
Proceedings of the 7th International Conference on System of Systems Engineering, 2012

Approximation structures with moderate complexity in functional optimization and dynamic programming.
Proceedings of the 51th IEEE Conference on Decision and Control, 2012

On a Variational Norm Tailored to Variable-Basis Approximation Schemes.
IEEE Trans. Inf. Theory, 2011

Team optimization problems with Lipschitz continuous strategies.
Optim. Lett., 2011

Can dictionary-based computational models outperform the best linear ones?
Neural Networks, 2011

Some comparisons of complexity in dictionary-based and linear computational models.
Neural Networks, 2011

CAC with Nonlinearly-Constrained Feasibility Regions.
IEEE Commun. Lett., 2011

Structural properties of optimal coordinate-convex policies for CAC with nonlinearly-constrained feasibility regions.
Proceedings of the INFOCOM 2011. 30th IEEE International Conference on Computer Communications, 2011

Bounds for Approximate Solutions of Fredholm Integral Equations Using Kernel Networks.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2011, 2011

A Generalized Stochastic Knapsack Problem with Application in Call Admission Control.
Proceedings of the 10th Cologne-Twente Workshop on graphs and combinatorial optimization. Extended Abstracts, 2011

Error bounds for suboptimal solutions to kernel principal component analysis.
Optim. Lett., 2010

Regularization Techniques and Suboptimal Solutions to Optimization Problems in Learning from Data.
Neural Comput., 2010

Minimizing Sequences for a Family of Functional Optimal Estimation Problems.
J. Optim. Theory Appl., 2010

On spectral windows in supervised learning from data.
Inf. Process. Lett., 2010

Guest editorial.
Comput. Oper. Res., 2010

Management of water resource systems in the presence of uncertainties by nonlinear approximation techniques and deterministic sampling.
Comput. Optim. Appl., 2010

Smooth Optimal Decision Strategies for Static Team Optimization Problems and Their Approximations.
Proceedings of the SOFSEM 2010: Theory and Practice of Computer Science, 2010

Some Comparisons of Model Complexity in Linear and Neural-Network Approximation.
Proceedings of the Artificial Neural Networks - ICANN 2010, 2010

Regularization and Suboptimal Solutions in Learning from Data.
Proceedings of the Innovations in Neural Information Paradigms and Applications, 2009

The extended Ritz method for functional optimization: overview and applications to single-person and team optimal decision problems.
Optim. Methods Softw., 2009

Complexity of Gaussian-radial-basis networks approximating smooth functions.
J. Complex., 2009

Accuracy of suboptimal solutions to kernel principal component analysis.
Comput. Optim. Appl., 2009

Guest Editorial.
Comput. Manag. Sci., 2009

The weight-decay technique in learning from data: an optimization point of view.
Comput. Manag. Sci., 2009

On Tractability of Neural-Network Approximation.
Proceedings of the Adaptive and Natural Computing Algorithms, 9th International Conference, 2009

Geometric Upper Bounds on Rates of Variable-Basis Approximation.
IEEE Trans. Inf. Theory, 2008

Approximate Minimization of the Regularized Expected Error over Kernel Models.
Math. Oper. Res., 2008

Geometric Rates of Approximation by Neural Networks.
Proceedings of the SOFSEM 2008: Theory and Practice of Computer Science, 2008

Design of Asymptotic Estimators: An Approach Based on Neural Networks and Nonlinear Programming.
IEEE Trans. Neural Networks, 2007

Estimates of covering numbers of convex sets with slowly decaying orthogonal subsets.
Discret. Appl. Math., 2007

A recursive algorithm for nonlinear least-squares problems.
Comput. Optim. Appl., 2007

Estimates of Approximation Rates by Gaussian Radial-Basis Functions.
Proceedings of the Adaptive and Natural Computing Algorithms, 8th International Conference, 2007

Design of Parameterized State Observers and Controllers for a Class of Nonlinear Continuous-Time Systems.
Proceedings of the 45th IEEE Conference on Decision and Control, 2006

Error Estimates for Approximate Optimization by the Extended Ritz Method.
SIAM J. Optim., 2005

Optimization of approximating networks for optimal fault diagnosis.
Optim. Methods Softw., 2005

Rates of Minimization of Error Functionals over Boolean Variable-Basis Functions.
J. Math. Model. Algorithms, 2005

Learning with generalization capability by kernel methods of bounded complexity.
J. Complex., 2005

Minimization of Error Functionals over Variable-Basis Functions.
SIAM J. Optim., 2004

Neural network learning as approximate optimization.
Proceedings of the Artificial Neural Nets and Genetic Algorithms, 2003

EKF learning for feedforward neural networks.
Proceedings of the 7th European Control Conference, 2003

Optimization-based learning with bounded error for feedforward neural networks.
IEEE Trans. Neural Networks, 2002

Comparison of worst case errors in linear and neural network approximation.
IEEE Trans. Inf. Theory, 2002

Bounds on rates of variable-basis and neural-network approximation.
IEEE Trans. Inf. Theory, 2001

Tight Bounds on Rates of Neural-Network Approximation.
Proceedings of the Artificial Neural Networks, 2001

PF-stable estimators for nonlinear systems.
Proceedings of the 6th European Control Conference, 2001

Comparison of Rates of Linear and Neural Network Approximation.
Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks, 2000

On Dimension-Independent Approximation by Neural Networks and Linear Approximators.
Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks, 2000

Some Comparisons Between Linear Approximation and Approximation by Neural Networks.
Proceedings of the International Conference on Artificial Neural Nets and Genetic Algorithms, 1999

Algorithm of Incremental Approximation Using Variation of a Function with Respect to a Subset.
Proceedings of the International ICSC / IFAC Symposium on Neural Computation (NC 1998), 1998

Parameter-estimation-based learning for feedforward neural networks: convergence and robustness analysis.
Proceedings of the ESANN 1998, 1998