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- A. Ciancimino, G. Inzerillo, Stefano Lucidi, Laura Palagi
- Transportation Science
- 1999

- Laura Palagi, Marco Sciandrone
- Optimization Methods and Software
- 2005

- P Santambrogio, S Levi, +7 authors R Jappelli
- The Journal of biological chemistry
- 1992

Human ferritin, a multimeric iron storage protein, is composed by various proportions of two subunit types: the H- and L-chains. The biological functions of these two genic products have not been clarified, although differences in reactivity with iron have been shown. Starting from the hypothesis that the high stability typical of ferritin is an important… (More)

lemi e metodi innnovativi nell'ottimizazione non lineare, Italy. ABSTRACT Many real applications can be formulated as nonlinear minimization problems with a single linear equality constraint and box constraints. We are interested in solving problems where the number of variables is so huge that basic operations, such as the updating of the gradient or the… (More)

- Stefano Lucidi, Laura Palagi, Arnaldo Risi, Marco Sciandrone
- Comp. Opt. and Appl.
- 2007

- S. Lucidi, L. Palagi, M. Sciandrone
- 2003

In this work we consider nonlinear minimization problems with a single linear equality constraint and box constraints. In particular we are interested in solving problems where the number of variables is so huge that traditional optimization methods cannot be directly applied. Many interesting real world problems lead to the solution of large scale… (More)

- Luigi Grippo, Laura Palagi, Veronica Piccialli
- Math. Program.
- 2011

In this paper we consider low-rank semidefinite programming (LRSDP) relaxations of the max cut problem. Using the Gramian representation of a positive semidefinite matrix, the LRSDP problem is transformed into the nonconvex nonlinear programming problem of minimizing a quadratic function with quadratic equality constraints. First, we establish some new… (More)

- Stefano Lucidi, Laura Palagi, Arnaldo Risi, Marco Sciandrone
- IEEE Transactions on Neural Networks
- 2009

Training of support vector machines (SVMs) requires to solve a linearly constrained convex quadratic problem. In real applications, the number of training data may be very huge and the Hessian matrix cannot be stored. In order to take into account this issue, a common strategy consists in using decomposition algorithms which at each iteration operate only… (More)

- Stefano Lucidi, Laura Palagi, Massimo Roma
- SIAM Journal on Optimization
- 1998

In this paper we consider the problem of minimizing a (possibly nonconvex) quadratic function with a quadratic constraint. We point out some new properties of the problem. In particular, in the rst part of the paper, we show that (i) given a KKT point that is not a global minimizer, it is easy to nd a \better" feasible point; (ii) strict complementarity… (More)

- Francisco Facchinei, Stefano Lucidi, Laura Palagi
- SIAM Journal on Optimization
- 2002

A new method for the solution of minimization problems with simple bounds is presented. Global convergence of a general scheme requiring the approximate solution of a single linear system at each iteration is proved and a superlinear convergence rate is established without requiring the strict complementarity assumption. The algorithm proposed is based on a… (More)