Special Issue on Statistical and Learning-Theoretic Challenges in Data Privacy

Special Issue on Statistical and Learning-Theoretic Challenges in Data Privacy

This special issue presents papers based on talks from a workshop on "Statistical and Learning-Theoretic Challenges in Data Privacy" held at UCLA's Institute for Pure and Applied Mathematics (IPAM), February 22–26, 2010.

Saved in:
Bibliographic Details
Published in:The journal of privacy and confidentiality Vol. 4; no. 1
Main Authors: Slavkovic, Aleksandra B., Smith, Adam
Format: Journal Article
Language:English
Published: Labor Dynamics Institute 20-07-2012
Subjects:
cryptography
data mining
machine learning
statistics
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:This special issue presents papers based on talks from a workshop on "Statistical and Learning-Theoretic Challenges in Data Privacy" held at UCLA's Institute for Pure and Applied Mathematics (IPAM), February 22–26, 2010.
ISSN:2575-8527
2575-8527
DOI:10.29012/jpc.v4i1.609