Main Navigation
Main Content
Sidebar
Register
Login
Toggle navigation
Current
Archives
Announcements
TPDP workshop
Submissions
About
About the Journal
Editorial Team
Policies
Code and Data Availability Policy
Privacy Statement
Our Github repositories
Contact
Search
Search
Search articles for
Advanced filters
Published After
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
2022
2023
2024
January
February
March
April
May
June
July
August
September
October
November
December
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
Published Before
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
2022
2023
2024
January
February
March
April
May
June
July
August
September
October
November
December
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
By Author
Search Results
Program for TPDP 2016
Gilles Barthe, Christos Dimitrakakis, Marco Gaboardi, Andreas Haeberlen, Aaron Roth, Aleksandra B Slavković
Program for TPDP 2017
Jonathan Ullman; Lars Vilhuber
In Honour of Steve and Joyce Fienberg
Natalie Shlomo
Private Boosted Decision Trees via Smooth Re-Weighting
Mohammadmahdi Jahanara, Vahid Asadi, Marco Carmosino, Akbar Rafiey, Bahar Salamatian
Winning the NIST Contest: A scalable and general approach to differentially private synthetic data
Ryan McKenna, Gerome Miklau, Daniel Sheldon
Introduction to Special Section
Dan Kifer
Overlook: Differentially Private Exploratory Visualization for Big Data
Mihai Budiu, Pratiksha Thaker, Parikshit Gopalan, Udi Wieder, Matei Zaharia
Estimating Risks of Identification Disclosure in Partially Synthetic Data
Jerome P. Reiter, Robin Mitra
Reminiscences
Cynthia Dwork
Manipulation Attacks in Local Differential Privacy
Albert Cheu, Adam Smith, Jonathan Ullman
Interaction is Necessary for Distributed Learning with Privacy or Communication Constraints
Yuval Dagan, Vitaly Feldman
DPSyn: Experiences in the NIST Differential Privacy Data Synthesis Challenges
Tianhao Wang, Ninghui Li, Zhikun Zhang
Releasing Microdata: Disclosure Risk Estimation, Data Masking and Assessing Utility
Natalie Shlomo
Differentially Private Set Union
Sivakanth Gopi, Pankaj Gulhane, Janardhan Kulkarni, Judy Hanwen Shen, Milad Shokouhi, Sergey Yekhanin
Private Convex Optimization via Exponential Mechanism
Sivakanth Gopi, Yin Tat Lee, Daogao Liu
Vulnerability of Complementary Cell Suppression to Intruder Attack
Lawrence H. Cox
Optimizing Error of High-Dimensional Statistical Queries Under Differential Privacy
Ryan McKenna, Gerome Miklau, Michael Hay, Ashwin Machanavajjhala
Reminiscenses of Steve Fienberg
Dan Kifer
Exact Privacy Analysis of the Gaussian Sparse Histogram Mechanism
Arjun Wilkins, Daniel Kifer, Danfeng Zhang, Brian Karrer
Differentially Private Guarantees for Analytics and Machine Learning on Graphs: A Survey of Results
Tamara T. Mueller, Dmitrii Usynin, Johannes C. Paetzold, Rickmer Braren, Daniel Rueckert, Georgios Kaissis
Memories of Steve Fienberg
Rebecca Carter Steorts
Representing Sparse Vectors with Differential Privacy, Low Error, Optimal Space, and Fast Access
Martin Aumüller, Christian Janos Lebeda, Rasmus Pagh
On the Privacy and Utility Properties of Triple Matrix-Masking
Aidong Adam Ding, Guanhong Miao, Samuel Shangwu Wu
Maintaining Analytic Utility while Protecting Confidentiality of Survey and Nonsurvey Data
Avinash C. Singh
Tribute to Steve Fienberg
John Abowd
126 - 150 of 176 items
<<
<
1
2
3
4
5
6
7
8
>
>>