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Marcello Sanguineti
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2020 – today
- 2024
- [j61]Ming Li
, Alessio Micheli, Yu Guang Wang, Shirui Pan, Pietro Lió, Giorgio Stefano Gnecco, Marcello Sanguineti:
Guest Editorial: Deep Neural Networks for Graphs: Theory, Models, Algorithms, and Applications. IEEE Trans. Neural Networks Learn. Syst. 35(4): 4367-4372 (2024) - [e1]Martin Clayton
, Mauro Passacantando
, Marcello Sanguineti
:
Intelligent Technologies for Interactive Entertainment - 14th EAI International Conference, INTETAIN 2023, Lucca, Italy, November 27, 2023, Proceedings. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 560, Springer 2024, ISBN 978-3-031-55721-7 [contents] - 2023
- [j60]Vera Kurková
, Marcello Sanguineti:
Approximation of classifiers by deep perceptron networks. Neural Networks 165: 654-661 (2023) - 2022
- [j59]Giorgio Gnecco, Yuval Hadas
, Marcello Sanguineti:
A game-theoretic approach for reliability evaluation of public transportation transfers with stochastic features. EURO J. Transp. Logist. 11: 100090 (2022) - [c43]Ming Li
, Giorgio Gnecco
, Marcello Sanguineti
:
Deeper Insights into Neural Nets with Random Weights. AI 2022: 129-140 - [i1]Durgesh Haribhau Salunkhe, Guillaume Michel, Shivesh Kumar, Marcello Sanguineti, Damien Chablat
:
An efficient combined local and global search strategy for optimization of parallel kinematic mechanisms with joint limits and collision constraints. CoRR abs/2202.11950 (2022) - 2021
- [j58]Mauro Passacantando
, Giorgio Gnecco
, Yuval Hadas
, Marcello Sanguineti
:
Braess' paradox: A cooperative game-theoretic point of view. Networks 78(3): 264-283 (2021) - [j57]Marcello Sanguineti, Elena Tànfani:
Special Issue Optimization for Machine Learning Guest Editorial. Soft Comput. 25(19): 12565-12567 (2021) - [j56]Vera Kurková
, Marcello Sanguineti:
Correlations of random classifiers on large data sets. Soft Comput. 25(19): 12641-12648 (2021) - 2020
- [j55]Fouad El Ouardighi
, Konstantin Kogan
, Giorgio Gnecco
, Marcello Sanguineti
:
Transboundary pollution control and environmental absorption efficiency management. Ann. Oper. Res. 287(2): 653-681 (2020) - [j54]Ksenia Kolykhalova, Giorgio Gnecco
, Marcello Sanguineti
, Gualtiero Volpe
, Antonio Camurri
:
Automated Analysis of the Origin of Movement: An Approach Based on Cooperative Games on Graphs. IEEE Trans. Hum. Mach. Syst. 50(6): 550-560 (2020) - [c42]Olga Matthiopoulou, Benoît G. Bardy, Giorgio Gnecco
, Denis Mottet, Marcello Sanguineti, Antonio Camurri:
A Computational Method to Automatically Detect the Perceived Origin of Full-Body Human Movement and its Propagation. ICMI Companion 2020: 449-453
2010 – 2019
- 2019
- [j53]Giorgio Gnecco
, Yuval Hadas
, Marcello Sanguineti
:
Some properties of transportation network cooperative games. Networks 74(2): 161-173 (2019) - [j52]Vera Kurková
, Marcello Sanguineti
:
Classification by Sparse Neural Networks. IEEE Trans. Neural Networks Learn. Syst. 30(9): 2746-2754 (2019) - [c41]Erfan Shojaei Barjuei
, Mohammad Mahdi Ghazaei Ardakani, Darwin G. Caldwell, Marcello Sanguineti, Jesús Ortiz:
On the Optimal Selection of Motors and Transmissions for a Back-Support Exoskeleton. CBS 2019: 42-47 - [c40]Vera Kurková, Marcello Sanguineti:
Probabilistic Bounds for Binary Classification of Large Data Sets. INNSBDDL 2019: 309-319 - 2018
- [j51]Giorgio Gnecco
, Marcello Sanguineti
:
Neural approximations in discounted infinite-horizon stochastic optimal control problems. Eng. Appl. Artif. Intell. 74: 294-302 (2018) - [c39]Vera Kurková, Marcello Sanguineti:
Probabilistic Bounds on Complexity of Networks Computing Binary Classification Tasks. ITAT 2018: 86-91 - 2017
- [j50]Giorgio Gnecco
, Alberto Bemporad, Marco Gori, Marcello Sanguineti
:
LQG Online Learning. Neural Comput. 29(8): 2203-2291 (2017) - [j49]Vera Kurková
, Marcello Sanguineti
:
Probabilistic lower bounds for approximation by shallow perceptron networks. Neural Networks 91: 34-41 (2017) - [j48]Luca Boero
, Marco Cello
, Giorgio Gnecco
, Mario Marchese
, Fabio Patrone
, Marcello Sanguineti
:
A theoretical analysis of buffer occupancy for Intermittently-Connected Networks. Perform. Evaluation 115: 108-131 (2017) - [j47]Giorgio Gnecco
, Rita Morisi, Giorgio Roth, Marcello Sanguineti
, Angela Celeste Taramasso:
Supervised and semi-supervised classifiers for the detection of flood-prone areas. Soft Comput. 21(13): 3673-3685 (2017) - [c38]Ksenia Kolykhalova, Giorgio Gnecco
, Marcello Sanguineti
, Antonio Camurri
, Gualtiero Volpe:
Graph-restricted game approach for investigating human movement qualities. MOCO 2017: 30:1-30:4 - 2016
- [j46]Vera Kurková
, Marcello Sanguineti
:
Model complexities of shallow networks representing highly varying functions. Neurocomputing 171: 598-604 (2016) - [c37]Giorgio Gnecco, Marco Gori, Stefano Melacci, Marcello Sanguineti:
Learning with hard constraints as a limit case of learning with soft constraints. ESANN 2016 - 2015
- [j45]Ksenia Kolykhalova, Antonio Camurri
, Gualtiero Volpe, Marcello Sanguineti
, Enrico Puppo
, Radoslaw Niewiadomski
:
A Multimodal Dataset for the Analysis of Movement Qualities in Karate Martial Art. EAI Endorsed Trans. Collab. Comput. 1(4): e3 (2015) - [j44]Marco Cello, Giorgio Gnecco
, Mario Marchese
, Marcello Sanguineti
:
Narrowing the Search for Optimal Call-Admission Policies Via a Nonlinear Stochastic Knapsack Model. J. Optim. Theory Appl. 164(3): 819-841 (2015) - [j43]Giorgio Gnecco
, Marco Gori, Stefano Melacci
, Marcello Sanguineti
:
Foundations of Support Constraint Machines. Neural Comput. 27(2): 388-480 (2015) - [j42]Giorgio Gnecco
, Marco Gori, Stefano Melacci
, Marcello Sanguineti
:
Learning With Mixed Hard/Soft Pointwise Constraints. IEEE Trans. Neural Networks Learn. Syst. 26(9): 2019-2032 (2015) - [c36]Giorgio Gnecco
, Alberto Bemporad, Marco Gori, Rita Morisi, Marcello Sanguineti
:
Online learning as an LQG optimal control problem with random matrices. ECC 2015: 2482-2489 - [c35]Ksenia Kolykhalova, Antonio Camurri, Gualtiero Volpe, Marcello Sanguineti, Enrico Puppo, Radoslaw Niewiadomski:
A multimodal dataset for the analysis of movement qualities in karate martial art. INTETAIN 2015: 74-78 - 2014
- [j41]Mauro Gaggero
, Giorgio Gnecco
, Marcello Sanguineti
:
Approximate dynamic programming for stochastic N-stage optimization with application to optimal consumption under uncertainty. Comput. Optim. Appl. 58(1): 31-85 (2014) - [j40]Marco Cello, Giorgio Gnecco
, Mario Marchese
, Marcello Sanguineti
:
Evaluation of the Average Packet Delivery Delay in Highly-Disrupted Networks: The DTN and IP-like Protocol Cases. IEEE Commun. Lett. 18(3): 519-522 (2014) - [j39]Giorgio Gnecco
, Donald Glowinski, Antonio Camurri
, Marcello Sanguineti
:
On the detection of the level of attention in an orchestra through head movements. Int. J. Arts Technol. 7(4): 316-338 (2014) - [j38]Giorgio Gnecco
, Marco Gori, Stefano Melacci
, Marcello Sanguineti
:
A theoretical framework for supervised learning from regions. Neurocomputing 129: 25-32 (2014) - [c34]Vera Kurková
, Marcello Sanguineti
:
Complexity of Shallow Networks Representing Functions with Large Variations. ICANN 2014: 331-338 - 2013
- [j37]Mauro Gaggero
, Giorgio Gnecco
, Marcello Sanguineti
:
Dynamic Programming and Value-Function Approximation in Sequential Decision Problems: Error Analysis and Numerical Results. J. Optim. Theory Appl. 156(2): 380-416 (2013) - [j36]Giorgio Gnecco
, Marco Gori, Marcello Sanguineti
:
Learning with Boundary Conditions. Neural Comput. 25(4): 1029-1106 (2013) - [j35]Marco Cello, Giorgio Gnecco
, Mario Marchese
, Marcello Sanguineti
:
Optimality Conditions for Coordinate-Convex Policies in CAC With Nonlinear Feasibility Boundaries. IEEE/ACM Trans. Netw. 21(5): 1363-1377 (2013) - [c33]Giorgio Gnecco
, Leonardo Badino
, Antonio Camurri
, Alessandro D'Ausilio
, Luciano Fadiga
, Donald Glowinski, Marcello Sanguineti
, Giovanna Varni, Gualtiero Volpe
:
Towards Automated Analysis of Joint Music Performance in the Orchestra. ArtsIT 2013: 120-127 - [c32]Giorgio Gnecco
, Marco Gori, Stefano Melacci
, Marcello Sanguineti
:
Learning with Hard Constraints. ICANN 2013: 146-153 - [c31]Vera Kurková
, Marcello Sanguineti:
Can Two Hidden Layers Make a Difference? ICANNGA 2013: 30-39 - [p2]Paul C. Kainen, Vera Kurková
, Marcello Sanguineti
:
Approximating Multivariable Functions by Feedforward Neural Nets. Handbook on Neural Information Processing 2013: 143-181 - 2012
- [j34]Giorgio Gnecco
, Vera Kurková
, Marcello Sanguineti
:
Accuracy of approximations of solutions to Fredholm equations by kernel methods. Appl. Math. Comput. 218(14): 7481-7497 (2012) - [j33]Marco Cello, Giorgio Gnecco
, Mario Marchese
, Marcello Sanguineti
:
A Model of Buffer Occupancy for ICNs. IEEE Commun. Lett. 16(6): 862-865 (2012) - [j32]Giorgio Gnecco
, Marcello Sanguineti
:
New insights into Witsenhausen's counterexample. Optim. Lett. 6(7): 1425-1446 (2012) - [j31]Giorgio Gnecco
, Marcello Sanguineti
, Mauro Gaggero
:
Suboptimal Solutions to Team Optimization Problems with Stochastic Information Structure. SIAM J. Optim. 22(1): 212-243 (2012) - [j30]Paul C. Kainen, Vera Kurková
, Marcello Sanguineti
:
Dependence of Computational Models on Input Dimension: Tractability of Approximation and Optimization Tasks. IEEE Trans. Inf. Theory 58(2): 1203-1214 (2012) - [c30]Mauro Gaggero
, Giorgio Gnecco
, Thomas Parisini, Marcello Sanguineti
, Riccardo Zoppoli:
Approximation structures with moderate complexity in functional optimization and dynamic programming. CDC 2012: 1902-1908 - [c29]Marco Cello, Giorgio Gnecco
, Mario Marchese
, Marcello Sanguineti
:
An application to two-hop forwarding of a model of buffer occupancy in ICNs. SoSE 2012: 491-496 - 2011
- [j29]Marco Cello, Giorgio Gnecco
, Mario Marchese
, Marcello Sanguineti
:
CAC with Nonlinearly-Constrained Feasibility Regions. IEEE Commun. Lett. 15(4): 467-469 (2011) - [j28]Giorgio Gnecco
, Vera Kurková
, Marcello Sanguineti
:
Some comparisons of complexity in dictionary-based and linear computational models. Neural Networks 24(2): 171-182 (2011) - [j27]Giorgio Gnecco
, Vera Kurková
, Marcello Sanguineti
:
Can dictionary-based computational models outperform the best linear ones? Neural Networks 24(8): 881-887 (2011) - [j26]Giorgio Gnecco
, Marcello Sanguineti
:
Team optimization problems with Lipschitz continuous strategies. Optim. Lett. 5(2): 333-346 (2011) - [j25]Giorgio Gnecco
, Marcello Sanguineti
:
On a Variational Norm Tailored to Variable-Basis Approximation Schemes. IEEE Trans. Inf. Theory 57(1): 549-558 (2011) - [c28]Marco Cello, Giorgio Gnecco, Mario Marchese, Marcello Sanguineti:
A Generalized Stochastic Knapsack Problem with Application in Call Admission Control. CTW 2011: 105-108 - [c27]Giorgio Gnecco
, Vera Kurková
, Marcello Sanguineti
:
Bounds for Approximate Solutions of Fredholm Integral Equations Using Kernel Networks. ICANN (1) 2011: 126-133 - [c26]Mario Marchese
, Marco Cello, Giorgio Gnecco
, Marcello Sanguineti
:
Structural properties of optimal coordinate-convex policies for CAC with nonlinearly-constrained feasibility regions. INFOCOM 2011: 466-470 - 2010
- [j24]Marco Baglietto
, Cristiano Cervellera, Marcello Sanguineti
, Riccardo Zoppoli:
Management of water resource systems in the presence of uncertainties by nonlinear approximation techniques and deterministic sampling. Comput. Optim. Appl. 47(2): 349-376 (2010) - [j23]Enza Messina
, Marcello Sanguineti
:
Guest editorial. Comput. Oper. Res. 37(8): 1359-1360 (2010) - [j22]Giorgio Gnecco
, Marcello Sanguineti
:
On spectral windows in supervised learning from data. Inf. Process. Lett. 110(23): 1031-1036 (2010) - [j21]Angelo Alessandri
, Giorgio Gnecco
, Marcello Sanguineti
:
Minimizing Sequences for a Family of Functional Optimal Estimation Problems. J. Optim. Theory Appl. 147(2): 243-262 (2010) - [j20]Giorgio Gnecco
, Marcello Sanguineti
:
Regularization Techniques and Suboptimal Solutions to Optimization Problems in Learning from Data. Neural Comput. 22(3): 793-829 (2010) - [j19]Giorgio Gnecco
, Marcello Sanguineti
:
Error bounds for suboptimal solutions to kernel principal component analysis. Optim. Lett. 4(2): 197-210 (2010) - [c25]Giorgio Gnecco
, Vera Kurková
, Marcello Sanguineti
:
Some Comparisons of Model Complexity in Linear and Neural-Network Approximation. ICANN (3) 2010: 358-367 - [c24]Giorgio Gnecco
, Marcello Sanguineti
:
Smooth Optimal Decision Strategies for Static Team Optimization Problems and Their Approximations. SOFSEM 2010: 440-451
2000 – 2009
- 2009
- [j18]O. Erhun Kundakcioglu
, Marcello Sanguineti
, Theodore B. Trafalis
:
Guest Editorial. Comput. Manag. Sci. 6(1): 1-3 (2009) - [j17]Giorgio Gnecco
, Marcello Sanguineti
:
The weight-decay technique in learning from data: an optimization point of view. Comput. Manag. Sci. 6(1): 53-79 (2009) - [j16]Giorgio Gnecco
, Marcello Sanguineti
:
Accuracy of suboptimal solutions to kernel principal component analysis. Comput. Optim. Appl. 42(2): 265-287 (2009) - [j15]Paul C. Kainen, Vera Kurková
, Marcello Sanguineti
:
Complexity of Gaussian-radial-basis networks approximating smooth functions. J. Complex. 25(1): 63-74 (2009) - [j14]Marco Baglietto
, Marcello Sanguineti
, Riccardo Zoppoli:
The extended Ritz method for functional optimization: overview and applications to single-person and team optimal decision problems. Optim. Methods Softw. 24(1): 15-43 (2009) - [c23]Paul C. Kainen, Vera Kurková
, Marcello Sanguineti
:
On Tractability of Neural-Network Approximation. ICANNGA 2009: 11-21 - [p1]Giorgio Gnecco
, Marcello Sanguineti
:
Regularization and Suboptimal Solutions in Learning from Data. Innovations in Neural Information Paradigms and Applications 2009: 113-154 - 2008
- [j13]Vera Kurková
, Marcello Sanguineti
:
Approximate Minimization of the Regularized Expected Error over Kernel Models. Math. Oper. Res. 33(3): 747-756 (2008) - [j12]Vera Kurková
, Marcello Sanguineti
:
Geometric Upper Bounds on Rates of Variable-Basis Approximation. IEEE Trans. Inf. Theory 54(12): 5681-5688 (2008) - [c22]Vera Kurková
, Marcello Sanguineti:
Geometric Rates of Approximation by Neural Networks. SOFSEM 2008: 541-550 - 2007
- [j11]Angelo Alessandri
, Marta Cuneo, S. Pagnan, Marcello Sanguineti
:
A recursive algorithm for nonlinear least-squares problems. Comput. Optim. Appl. 38(2): 195-216 (2007) - [j10]Vera Kurková
, Marcello Sanguineti
:
Estimates of covering numbers of convex sets with slowly decaying orthogonal subsets. Discret. Appl. Math. 155(15): 1930-1942 (2007) - [j9]Angelo Alessandri
, Cristiano Cervellera, Marcello Sanguineti
:
Design of Asymptotic Estimators: An Approach Based on Neural Networks and Nonlinear Programming. IEEE Trans. Neural Networks 18(1): 86-96 (2007) - [c21]Paul C. Kainen, Vera Kurková
, Marcello Sanguineti:
Estimates of Approximation Rates by Gaussian Radial-Basis Functions. ICANNGA (2) 2007: 11-18 - 2006
- [c20]Angelo Alessandri, Cristiano Cervellera, Danilo Macciò, Marcello Sanguineti:
Design of Parameterized State Observers and Controllers for a Class of Nonlinear Continuous-Time Systems. CDC 2006: 5388-5393 - 2005
- [j8]Vera Kurková
, Marcello Sanguineti
:
Learning with generalization capability by kernel methods of bounded complexity. J. Complex. 21(3): 350-367 (2005) - [j7]Paul C. Kainen, Vera Kurková
, Marcello Sanguineti
:
Rates of Minimization of Error Functionals over Boolean Variable-Basis Functions. J. Math. Model. Algorithms 4(4): 355-368 (2005) - [j6]Angelo Alessandri
, Marcello Sanguineti
:
Optimization of approximating networks for optimal fault diagnosis. Optim. Methods Softw. 20(2-3): 241-266 (2005) - [j5]Vera Kurková
, Marcello Sanguineti
:
Error Estimates for Approximate Optimization by the Extended Ritz Method. SIAM J. Optim. 15(2): 461-487 (2005) - [c19]Angelo Alessandri, Cristiano Cervellera, Filippo Aldo Grassia, Marcello Sanguineti:
An approximate solution to optimal Lp state estimation problems. ACC 2005: 4204-4209 - 2004
- [j4]Paul C. Kainen, Vera Kurková
, Marcello Sanguineti
:
Minimization of Error Functionals over Variable-Basis Functions. SIAM J. Optim. 14(3): 732-742 (2004) - [c18]Angelo Alessandri, Cristiano Cervellera, Filippo Aldo Grassia, Marcello Sanguineti
:
Design of observers for continuous-time nonlinear systems using neural networks. ACC 2004: 2433-2438 - 2003
- [c17]Angelo Alessandri
, Marta Cuneo, S. Pagnan, Marcello Sanguineti
:
On the convergence of EKF-based parameters optimization for neural networks. CDC 2003: 6181-6186 - [c16]Angelo Alessandri, G. Cirimele, Marta Cuneo, S. Pagnan, Marcello Sanguineti:
EKF learning for feedforward neural networks. ECC 2003: 1990-1995 - [c15]Vera Kurková
, Marcello Sanguineti:
Neural network learning as approximate optimization. ICANNGA 2003: 53-57 - 2002
- [j3]Vera Kurková
, Marcello Sanguineti
:
Comparison of worst case errors in linear and neural network approximation. IEEE Trans. Inf. Theory 48(1): 264-275 (2002) - [j2]Angelo Alessandri
, Marcello Sanguineti
, Manfredi Maggiore:
Optimization-based learning with bounded error for feedforward neural networks. IEEE Trans. Neural Networks 13(2): 261-273 (2002) - [c14]Angelo Alessandri, Marcello Sanguineti
, Manfredi Maggiore:
Batch-mode identification of black-box models using feedforward neural networks. ACC 2002: 406-411 - [c13]Angelo Alessandri, Marcello Sanguineti, Manfredi Maggiore:
Optimized feedforward neural networks for on-line identification of nonlinear models. CDC 2002: 1751-1756 - 2001
- [j1]Vera Kurková
, Marcello Sanguineti
:
Bounds on rates of variable-basis and neural-network approximation. IEEE Trans. Inf. Theory 47(6): 2659-2665 (2001) - [c12]Angelo Alessandri, Marcello Sanguineti:
Lp-stable and asymptotic estimators for nonlinear dynamic systems. ACC 2001: 1991-1996 - [c11]Angelo Alessandri, Marcello Sanguineti:
On the design of approximate state estimators for nonlinear systems. CDC 2001: 3372-3377 - [c10]Riccardo Zoppoli, Marcello Sanguineti, Thomas Parisini:
Can we cope with the curse of dimensionality in optimal control by using neural approximators? CDC 2001: 3540-3545 - [c9]Angelo Alessandri, Marcello Sanguineti:
PF-stable estimators for nonlinear systems. ECC 2001: 1-6 - [c8]Vera Kurková
, Marcello Sanguineti
:
Tight Bounds on Rates of Neural-Network Approximation. ICANN 2001: 277-284 - 2000
- [c7]Marco Baglietto
, Cristiano Cervellera, Thomas Parisini, Marcello Sanguineti, N. Zoppoli:
Approximating networks, dynamic programming and stochastic approximation. ACC 2000: 3304-3308 - [c6]Angelo Alessandri, Marcello Sanguineti:
On estimators for nonlinear systems in Lp spaces. CDC 2000: 298-303 - [c5]Vera Kurková
, Marcello Sanguineti:
Comparison of Rates of Linear and Neural Network Approximation. IJCNN (1) 2000: 277-282 - [c4]Saverio Giulini, Marcello Sanguineti:
On Dimension-Independent Approximation by Neural Networks and Linear Approximators. IJCNN (1) 2000: 283-288
1990 – 1999
- 1999
- [c3]Marcello Sanguineti, Katerina Hlavácková-Schindler
:
Some Comparisons Between Linear Approximation and Approximation by Neural Networks. ICANNGA 1999: 172-177 - 1998
- [c2]Angelo Alessandri, Manfredi Maggiore, Marcello Sanguineti:
Parameter-estimation-based learning for feedforward neural networks: convergence and robustness analysis. ESANN 1998: 285-290 - [c1]Katerina Hlavácková, Marcello Sanguineti:
Algorithm of Incremental Approximation Using Variation of a Function with Respect to a Subset. NC 1998: 896-899
Coauthor Index
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