Differentially Private Learning of Undirected Graphical Models using
Collective Graphical Models

Differentially Private Learning of Undirected Graphical Models using Collective Graphical Models

14 June 2017

ArXiv (abs)PDF HTML

Papers citing "Differentially Private Learning of Undirected Graphical Models using Collective Graphical Models"

14 / 14 papers shown

Title
Deep Learning with Differential Privacy Martín Abadi Andy Chu Ian Goodfellow H. B. McMahan Ilya Mironov Kunal Talwar Li Zhang FedML SyDa 223 27 0 01 Jul 2016
Bolt-on Differential Privacy for Scalable Stochastic Gradient Descent-based Analytics Xi Wu Fengan Li Arun Kumar Kamalika Chaudhuri S. Jha Jeffrey F. Naughton 56 20 0 15 Jun 2016
On the Theory and Practice of Privacy-Preserving Bayesian Data Analysis James R. Foulds J. Geumlek Max Welling Kamalika Chaudhuri 77 102 0 23 Mar 2016
Bethe Projections for Non-Local Inference Luke Vilnis David Belanger Daniel Sheldon Andrew McCallum 80 24 0 04 Mar 2015
Privacy for Free: Posterior Sampling and Stochastic Gradient Monte Carlo Yu Wang S. Fienberg Alex Smola 105 249 0 26 Feb 2015
Differentially Private Exponential Random Graphs Vishesh Karwa Aleksandra B. Slavkovic P. Krivitsky 118 42 0 16 Sep 2014
Differentially Private Empirical Risk Minimization: Efficient Algorithms and Tight Error Bounds Raef Bassily Adam D. Smith Abhradeep Thakurta FedML 153 371 0 27 May 2014
Gaussian Approximation of Collective Graphical Models Li-Ping Liu Daniel Sheldon Thomas G. Dietterich 55 9 0 20 May 2014
Bayesian Differential Privacy through Posterior Sampling Christos Dimitrakakis B. Nelson and Zuhe Zhang Aikaterini Mitrokotsa Benjamin I. P. Rubinstein 120 118 0 05 Jun 2013
Maximum likelihood estimation in log-linear models S. Fienberg Alessandro Rinaldo 68 80 0 19 Apr 2011
Differentially Private Empirical Risk Minimization Kamalika Chaudhuri C. Monteleoni Anand D. Sarwate 170 1,490 0 01 Dec 2009
Learning in a Large Function Space: Privacy-Preserving Mechanisms for SVM Learning Benjamin I. P. Rubinstein Peter L. Bartlett Ling Huang N. Taft 117 295 0 30 Nov 2009
Efficient, Differentially Private Point Estimators Adam D. Smith FedML 91 78 0 27 Sep 2008
What Can We Learn Privately? S. Kasiviswanathan Homin K. Lee Kobbi Nissim Sofya Raskhodnikova Adam D. Smith 139 1,474 0 06 Mar 2008