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- Luca Zanni, Thomas Serafini, Gaetano Zanghirati
- Journal of Machine Learning Research
- 2006

Parallel software for solving the quadratic program arising in training support vector machines for classification problems is introduced. The software implements an iterative decomposition technique… (More)

- Thomas Serafini, Gaetano Zanghirati, Luca Zanni
- Optimization Methods and Software
- 2005

Gradient projection methods based on the Barzilai-Borwein spectral steplength choices are considered for quadratic programming problems with simple constraints. Well-known nonmonotone spectral… (More)

- Gaetano Zanghirati, Luca Zanni
- Parallel Computing
- 2003

This work is concerned with the solution of the convex quadratic programming problem arising in training the learning machines named support vector machines. The problem is subject to box constraints… (More)

- Thomas Serafini, Gaetano Zanghirati, Luca Zanni
- PARCO
- 2003

We consider parallel decomposition techniques for solving the large quadratic programming (QP) problems arising in training support vector machines. A recent technique is improved by introducing an… (More)

- G. Frassoldati, Lorenzo Zanni, Gaetano Zanghirati
- 2007

This paper deals with gradient methods for minimizing n-dimensional strictly convex quadratic functions. Two new adaptive stepsize selection rules are presented and some key properties are proved.… (More)

- Gaetano Zanghirati
- Applied Mathematics and Computation
- 2000

In this paper we present a new method for solving block-bordered nonlinear systems of equations. This method is based on the modi®ed Feng±Schnabel algorithm of G. Zanghirati (Global convergence… (More)

- Gaetano Zanghirati, F. Cocco, G. Paruolo, F. Taddei
- Parallel Computing
- 2000

Asset and liability management (ALM) models represent an important tool for banks and ®nance companies to measure the volatility of expected revenues. These models ± usually static and deterministic… (More)

This paper describes a signal processing method for comprehensive analysis of the large data set generated by hyphenated GC-MS technique. It is based on the study of the 2D autocovariance function… (More)

- Tatiana A. Bubba, Federica Porta, Gaetano Zanghirati, Silvia Bonettini
- Applied Mathematics and Computation
- 2018

- Ambra Giovannini, Gaetano Zanghirati, Mark A. Beaumont, Lounès Chikhi, Guido Barbujani
- Bioinformatics
- 2009

SUMMARY
Inferring population admixture from genetic data and quantifying it is a difficult but crucial task in evolutionary and conservation biology. Unfortunately state-of-the-art probabilistic… (More)