Marco Sciandrone

发表

On the convergence of the block nonlinear Gauss-Seidel method under convex constraints

Luigi Grippo, Marco Sciandrone, L. Grippo, 2000, Oper. Res. Lett..

Efficient training of RBF neural networks for pattern recognition

Marco Sciandrone, Francesco Lampariello, F. Lampariello, 2001, IEEE Trans. Neural Networks.

Continuous Optimization On the convergence of inexact block coordinate descent methods for constrained optimization

Marco Sciandrone, Andrea Cassioli, David Di Lorenzo, 2013 .

An Optimization-Based Method for Feature Ranking in Nonlinear Regression Problems

Marco Sciandrone, Luca Bravi, Veronica Piccialli, 2017, IEEE Transactions on Neural Networks and Learning Systems.

Scheduling the Italian National Volleyball Tournament

Marco Sciandrone, Fabio Schoen, Veronica Piccialli, 2018, Interfaces.

On the Global Convergence of Derivative-Free Methods for Unconstrained Optimization

Marco Sciandrone, Stefano Lucidi, S. Lucidi, 2002, SIAM J. Optim..

Objective-derivative-free methods for constrained optimization

Paul Tseng, Marco Sciandrone, Stefano Lucidi, 2002, Math. Program..

A convergent decomposition algorithm for support vector machines

Laura Palagi, Marco Sciandrone, Stefano Lucidi, 2007, Comput. Optim. Appl..

Nonmonotone derivative-free methods for nonlinear equations

Luigi Grippo, Marco Sciandrone, L. Grippo, 2007, Comput. Optim. Appl..

Nonlinear optimization and support vector machines

Marco Sciandrone, Veronica Piccialli, M. Sciandrone, 2018, 4OR.

A cubic regularization algorithm for unconstrained optimization using line search and nonmonotone techniques

Marco Sciandrone, Tommaso Bianconcini, M. Sciandrone, 2016, Optim. Methods Softw..

Real-Time Epileptic Seizure Prediction Using AR Models and Support Vector Machines

Luigi Chisci, Marco Sciandrone, Carmelo Anile, 2010, IEEE Transactions on Biomedical Engineering.

Nonmonotone Globalization Techniques for the Barzilai-Borwein Gradient Method

Luigi Grippo, Marco Sciandrone, L. Grippo, 2002, Comput. Optim. Appl..

A computational study of path-based methods for optimal traffic assignment with both inelastic and elastic demand

Marco Sciandrone, Alessandro Galligari, M. Sciandrone, 2019, Comput. Oper. Res..

On the convergence of steepest descent methods for multiobjective optimization

Marco Sciandrone, Stefano Lucidi, Giampaolo Liuzzi, 2020, Comput. Optim. Appl..

A Derivative-Free Algorithm for Bound Constrained Optimization

Marco Sciandrone, Stefano Lucidi, S. Lucidi, 2002, Comput. Optim. Appl..

A Derivative-Free Algorithm for Linearly Constrained Finite Minimax Problems

Marco Sciandrone, Stefano Lucidi, Giampaolo Liuzzi, 2006, SIAM J. Optim..

A convergent inexact solution method for equilibrium problems

Marco Sciandrone, David Di Lorenzo, Mauro Passacantando, 2014, Optim. Methods Softw..

A unified convergence framework for nonmonotone inexact decomposition methods

Marco Sciandrone, Alessandro Galligari, Leonardo Galli, 2020, Comput. Optim. Appl..

An incremental least squares algorithm for large scale linear classification

Costanzo Manes, Marco Sciandrone, Andrea Cassioli, 2013, Eur. J. Oper. Res..

A Truncated Nonmonotone Gauss-Newton Method for Large-Scale Nonlinear Least-Squares Problems

Marco Sciandrone, Francesco Lampariello, Giovanni Fasano, 2006, Comput. Optim. Appl..

Machine learning for global optimization

Marco Sciandrone, Fabio Schoen, Andrea Cassioli, 2010, Computational Optimization and Applications.

A nonmonotone trust-region method for generalized Nash equilibrium and related problems with strong convergence properties

Marco Sciandrone, Christian Kanzow, Leonardo Galli, 2018, Comput. Optim. Appl..

Please Scroll down for Article Optimization Methods and Software Feature Selection Combining Linear Support Vector Machines and Concave Optimization Feature Selection Combining Linear Support Vector Machines and Concave Optimization

Marco Sciandrone, Francesco Rinaldi, M. Sciandrone, 2022 .

A patient adaptable ECG beat classifier based on neural networks

Marco Sciandrone, Simona Panunzi, Andrea De Gaetano, 2009, Appl. Math. Comput..

Concave programming for minimizing the zero-norm over polyhedral sets

Marco Sciandrone, Fabio Schoen, Francesco Rinaldi, 2010, Comput. Optim. Appl..

A concave optimization-based approach for sparse portfolio selection

Marco Sciandrone, Fabio Schoen, David Di Lorenzo, 2012, Optim. Methods Softw..

Machine learning methods for short‐term bid forecasting in the renewable energy market: A case study in Italy

Marco Sciandrone, Giulio Galvan, Matteo Cantù, 2018 .

A Convergent Hybrid Decomposition Algorithm Model for SVM Training

Laura Palagi, Marco Sciandrone, Stefano Lucidi, 2009, IEEE Transactions on Neural Networks.

Support Vector Machines

Marco Sciandrone, 2005 .

Convergent Decomposition Techniques for Training RBF Neural Networks

Luigi Grippo, Marco Sciandrone, C. Buzzi, 2001, Neural Computation.

On the use of iterative methods in cubic regularization for unconstrained optimization

Marco Sciandrone, Benedetta Morini, Giampaolo Liuzzi, 2015, Comput. Optim. Appl..

On the convergence of a modified version of SVM light algorithm

Laura Palagi, Marco Sciandrone, M. Sciandrone, 2005, Optim. Methods Softw..

An implicit filtering algorithm for derivative-free multiobjective optimization with box constraints

Marco Sciandrone, Giampaolo Liuzzi, Guido Cocchi, 2017, Computational Optimization and Applications.

Sequential Penalty Derivative-Free Methods for Nonlinear Constrained Optimization

Marco Sciandrone, Stefano Lucidi, Giampaolo Liuzzi, 2010, SIAM J. Optim..

A convergent and efficient decomposition method for the traffic assignment problem

Marco Sciandrone, David Di Lorenzo, Alessandro Galligari, 2015, Comput. Optim. Appl..

A convergent and fast path equilibration algorithm for the traffic assignment problem

Marco Sciandrone, Alessandro Galligari, M. Sciandrone, 2018, Optim. Methods Softw..

A concave optimization-based approach for sparse multiobjective programming

Marco Sciandrone, Giampaolo Liuzzi, Tommaso Levato, 2020, Optim. Lett..

An incremental decomposition method for unconstrained optimization

Marco Sciandrone, Luca Bravi, M. Sciandrone, 2014, Appl. Math. Comput..

An Algorithm Model for Mixed Variable Programming

Marco Sciandrone, Stefano Lucidi, Veronica Piccialli, 2005, SIAM J. Optim..

Decomposition Techniques for Multilayer Perceptron Training

Luigi Grippo, Marco Sciandrone, Andrea Manno, 2016, IEEE Transactions on Neural Networks and Learning Systems.

A convergent decomposition method for box-constrained optimization problems

Marco Sciandrone, Andrea Cassioli, 2009, Optim. Lett..

Special Issue: The 3rd International Conference on Optimization Methods and Software (May 13-17, 2012, Chania, Greece) Foreword

Andreas Griewank, Stefan Ulbrich, Masao Fukushima, 2014 .

An Alternating Augmented Lagrangian method for constrained nonconvex optimization

Marco Sciandrone, Giulio Galvan, M. Lapucci, 2020, Optim. Methods Softw..

Decomposition algorithms for generalized potential games

Francisco Facchinei, Marco Sciandrone, Veronica Piccialli, 2011, Comput. Optim. Appl..

A parameter-free unconstrained reformulation for nonsmooth problems with convex constraints

Marco Sciandrone, Stefano Lucidi, Giulio Galvan, 2021, Computational Optimization and Applications.

Convergent Inexact Penalty Decomposition Methods for Cardinality-Constrained Problems

Marco Sciandrone, Matteo Lapucci, Tommaso Levato, 2020, Journal of Optimization Theory and Applications.

A Two-Level Decomposition Framework Exploiting First and Second Order Information for SVM Training Problems

Chih-Jen Lin, Marco Sciandrone, Giulio Galvan, 2021, J. Mach. Learn. Res..

A Higher Order Method for the Solution of Nonlinear Scalar Equations

Alfredo Germani, Costanzo Manes, Marco Sciandrone, 2003 .

Higher-Order Method for the Solution of a Nonlinear Scalar Equation

Alfredo Germani, Costanzo Manes, Marco Sciandrone, 2006 .

Global Convergence Technique for the Newton Method with Periodic Hessian Evaluation

Marco Sciandrone, F. Lampariello, F. Lampariello, 2001 .

Prediction of chronic damage in systemic lupus erythematosus by using machine-learning models

Marco Sciandrone, Giulio Galvan, Fabrizio Conti, 2017, PloS one.

Intracranial pressure wave morphological classification: automated analysis and clinical validation

Marco Sciandrone, Carmelo Anile, Arnaldo Risi, 2015, Acta Neurochirurgica.