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Computational experiments with minimum-distance controlled perturbation methods

Autor
Castro, J.
Tipus d'activitat
Article en revista
Revista
Lecture notes in computer science
Data de publicació
2004-06
Volum
3050
Pàgina inicial
73
Pàgina final
86
DOI
https://doi.org/10.1007/978-3-540-25955-8_6 Obrir en finestra nova
URL
https://link.springer.com/chapter/10.1007/978-3-540-25955-8_6 Obrir en finestra nova
Resum
Minimum-distance controlled perturbation is a recent family of methods for the protection of statistical tabular data. These methods are both efficient and versatile, since can deal with large tables of any structure and dimension, and in practice only need the solution of a linear or quadratic optimization problem. The purpose of this paper is to give insight into the behaviour of such methods through some computational experiments. In particular, the paper (1) illustrates the theoretical resul...
Paraules clau
Statistical Disclosure Control, Controlled Perturbation Methods, Linear Programming, Quadratic Programming
Grup de recerca
GNOM - Grup d'Optimització Numèrica i Modelització

Participants