# List of publications of Marco Sciandrone

- F. Ceccarelli, M. Sciandrone, C. Perricone, G. Galvan, F. Morelli, L. Vicente et al.

Prediction of chronic damage in Systemic Lupus Erythematosus by using machine-learning models.

*PLOS ONE*, to appear, 2017. - T. Bianconcini, M. Sciandrone.

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

*Optimization Methods and Software*, Vol. 31(5), pp. 1008-1035, 2016. - C.G. Nucci, P. De Bonis, A. Mangiola, P. Santini, M. Sciandrone, A. Risi, C. Anile.

Intracranial pressure wave morphological classification: automated analysis and clinical validation.

*Acta Neurochirurgica*, pp. 1-8, 2016. - L. Bravi, V. Piccialli, M. Sciandrone.

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

*IEEE Transactions on Neural Networks and Learning Systems*, to appear, 2015. - L. Grippo, A. Manno, M. Sciandrone.

Decomposition Techniques for Multi Layer Perceptrons Training.

*IEEE Transactions on Neural Networks and Learning Systems*, vol. 27(11), pp. 2146-2159, 2016. - T. Bianconcini, G. Liuzzi, B. Morini, M. Sciandrone.

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

*Computational Optimization and Applications*, vol.60, pp. 35-57, 2015. - D. Di Lorenzo, A. Galligari, M. Sciandrone.

A convergent and efficient decomposition method for the traffic assignment problem.

*Computational Optimization and Applications*, vol. 60, pp. 151-170, 2015. - L. Bravi, M. Sciandrone.

An incremental decomposition method for unconstrained optimization.

*Applied Mathematics and Computation*, vol. 235, pp. 80-86, 2014. - A. Cassioli, D. Di Lorenzo, M. Sciandrone.

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

*European Journal of Operational Research*, vol. 231, pp. 274-281, 2013. - D. Di Lorenzo, M. Passacantando, M. Sciandrone.

A convergent inexact solution method for equilibrium problems.

*Optimization Methods and Software*, vol. 29, pp. 979-991, 2014. - A. Cassioli, A. Chiavaioli, C. Manes, M. Sciandrone.

An incremental least squares algorithm for large scale linear classification.

*European Journal of Operational Research*, vol. 224, pp. 560-565, 2013. - D. Di Lorenzo, G. Liuzzi, F. Rinaldi, F. Schoen, M. Sciandrone.

A concave optimization-based approach for sparse portfolio selection.

*Optimization Methods and Software*, vol. 27, pp. 983-1000, 2012. - G. Liuzzi, S. Lucidi, M. Sciandrone.

Sequential penalty derivative-free methods for nonlinear constrained optimization.

*SIAM Journal on Optimization*, vol. 20, pp.2814-2835, 2010. - F. Facchinei, V. Piccialli, M. Sciandrone.

Decomposition Algorithms for Generalized Potential Games.

*Computational Optimization and Applications*, vol. 50, pp. 237-262, 2011. - A. Cassioli, D. Di Lorenzo, M. Locatelli, F. Schoen, M. Sciandrone.

Machine learning for global optimization.

*Computational Optimization and Applications*, vol. 51, pp. 279-303, 2012. - L. Chisci, A. Mavino, G. Perferi, M, Sciandrone, C. Anile, G. Colicchio, F. Fuggetta.

Real time epileptic seizure prediction using AR models and Support Vector Machines.

*IEEE Transactions on Biomedical Engineering*, vol. 57, pp. 1124-1132, 2010. - L. Grippo, M. Sciandrone.

Nonmonotone globalization of the finite-difference Newton-GMRES method for nonlinear equations.

*Optimization Methods and Software*, vol. 25, pp.971-999, 2010. - F. Rinaldi, M. Sciandrone.

Feature selection combining linear support vector machines and concave optimization.

*Optimization Methods and Software*, vol. 25, pp. 117-128, 2010. - S. Lucidi, L. Palagi, A. Risi, M. Sciandrone.

A convergent hybrid decomposition algorithm model for SVM training.

*IEEE Transactions on Neural Networks*, vol. 20, pp. 1055-1060, 2009. - A. De Gaetano, S. Panunzi, F. Rinaldi, A. Risi, M. Sciandrone.

A patient adaptable ECG beat classifier using neural networks.

*Applied Mathematics and Computation*, vol. 213, pp. 243-249, 2009. - A. Cassioli, M. Sciandrone.

A convergent decomposition method for box-constrained optimization problems.

*Optimization Letters*, vol. 3, pp. 397-409, 2009. - F. Rinaldi, F. Schoen, M. Sciandrone.

Concave programming for minimizing the zero-norm over polyhedral sets.

*Computational Optimization and Applications*, vol. 46, pp. 467,486, 2010. - C.-J. Lin, S. Lucidi, L. Palagi, A. Risi, M. Sciandrone.

A decomposition algorithm model for singly linearly constrained problems subject to lower and upper bounds.

*Journal of Optimization Theory and Applications*, vol. 141, pp. 107-126, 2009. - S. Lucidi, L. Palagi, A. Risi, M. Sciandrone.

A convergent decomposition algorithm for support vector machines.

*Computational Optimization and Applications*, vol. 38, pp. 217-234, 2007. - L. Grippo, M. Sciandrone.

Nonmonotone derivative-free methods for nonlinear equations.

*Computational Optimization and Applications*, vol. 27, pp. 297-328, 2007. - A. Germani, C. Manes, P. Palumbo, M. Sciandrone.

Higher-order method for the solution of a nonlinear scalar equation.

*Journal of Optimization Theory and Applications*, vol. 131, pp. 347-364, 2006. - G. Fasano, F. Lampariello, M. Sciandrone.

A truncated nonmonotone Gauss-Newton method for large-scale nonlinearleast-squares problems.

*Computational Optimization and Applications*, vol. 34 (3), pp. 343-358, 2006. - G. Liuzzi, S. Lucidi, M. Sciandrone.

A derivative-free algorithm for linearly constrained finite minimax problems.

*SIAM Journal on Optimization*, vol. 18, pp.1054-1075, 2006. - S. Lucidi, V. Piccialli, M. Sciandrone.

An algorithm model for mixed variable programming.

*SIAM Journal on Optimization*, vol. 14, pp.1057-1084, 2005. - L. Palagi, M. Sciandrone.

On the convergence of a modified version of the SVMlight algorithm.

*Optimization Methods and Software*, vol. 20, pp.315-332, 2005. - F. Lampariello, M. Sciandrone.

Use of the “minimum norm” search direction in a nonmonotone version of the Gauss-Newton method.

*Journal of Optimization Theory and Applications*, Vol. 119, pp.65-82, 2003. - L. Grippo, M. Sciandrone.

Nonmonotone globalization techniques for the Barzilai-Borwein gradient method.

*Computational Optimization and Applications*, Vol. 23, pp.143-169, 2002. - S. Lucidi, M. Sciandrone.

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

*SIAM Journal on Optimization*, Vol. 13, pp. 97-116, 2002. - S. Lucidi, M. Sciandrone.

A derivative-free algorithm for bound constrained optimization.

*Computational Optimization and Applications*, Vol. 21 (2), pp.119-142, 2002. - S. Lucidi, M. Sciandrone, P. Tseng.

Objective-derivative-free methods for constrained optimization.

*Mathematical Programming*, Vol. 92 (1), pp. 37-59, 2002. - F. Lampariello, M. Sciandrone.

Efficient training of RBF neural networks for pattern recognition.

*IEEE Transactions on Neural Networks*, Vol. 12 (5), pp.1235-1242, 2001. - F. Lampariello, M. Sciandrone.

Global convergence technique for the Newton method with periodic Hessian evaluation.

*Journal of Optimization Theory and Applications*, Vol. 111 (2), pp.341-358, 2001. - C. Buzzi, L. Grippo, M. Sciandrone.

Convergent decomposition techniques for training RBF neural networks.

*Neural Computation*, Vol.13 (8), pp.1891-1920, 2001. - M. Sciandrone, G. Placidi, L. Testa, A. Sotgiu.

Compact low field MRI magnet: design and optimization.

*Review of Scientific Instruments*, Vol.71 (3), pp.1534-1538, 2000. - L. Grippo, M. Sciandrone.

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

*Operations Research Letters*, Vol. 26 (3), pp.127-136, 2000. - L. Grippo, M. Sciandrone.

Globally convergent block-coordinate techniques for unconstrained optimization.

*Optimization Methods and Software*, Vol. 10 (4), pp.587-637, 1999. - S. Lucidi, M. Sciandrone.

Numerical results for unconstrained optimization without derivatives.

F. Giannessi and G. Di Pillo editors,*“Nonlinear Optimization and Applications”*, Plenum Publishing, pp. 261-269, 1995. - A. De Luca, R. Mattone, M. Sciandrone.

Direct kinematics of articulated parallel manipulators using neural networks.

*3 IEEE Mediterranean Symposium on New Directions in Control and Automation*, pp.53-60, 1995.