@inproceedings{d14155ce024649c2abf7a32f500ca367,
title = "“Secure” Log-Linear and logistic regression analysis of distributed databases",
abstract = "The machine learning community has focused on confidentiality problems associated with statistical analyses that “integrate” data stored in multiple, distributed databases where there are barriers to simply integrating the databases. This paper discusses various techniques which can be used to perform statistical analysis for categorical data, especially in the form of log-linear analysis and logistic regression over partitioned databases, while limiting confidentiality concerns. We show how ideas from the current literature that focus on “secure” summations and secure regression analysis can be adapted or generalized to the categorical data setting.",
author = "Fienberg, {Stephen E.} and Fulp, {William J.} and Slavkovic, {Aleksandra B.} and Wrobel, {Tracey A.}",
note = "Publisher Copyright: {\textcopyright} Springer-Verlag Berlin Heidelberg 2006.; CENEX-SDC Project of International Conference on Privacy in Statistical Databases, PSD2006 ; Conference date: 13-12-2006 Through 15-12-2006",
year = "2006",
doi = "10.1007/11930242_24",
language = "English (US)",
isbn = "9783540493303",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "277--290",
editor = "Josep Domingo-Ferrer and Luisa Franconi",
booktitle = "Privacy in Statistical Databases - CENEX-SDC Project International Conference, PSD 2006, Proceedings",
address = "Germany",
}