ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 1502.07645
  4. Cited By
Privacy for Free: Posterior Sampling and Stochastic Gradient Monte Carlo
v1v2 (latest)

Privacy for Free: Posterior Sampling and Stochastic Gradient Monte Carlo

26 February 2015
Yu Wang
S. Fienberg
Alex Smola
ArXiv (abs)PDFHTML

Papers citing "Privacy for Free: Posterior Sampling and Stochastic Gradient Monte Carlo"

13 / 13 papers shown
Title
Distributed Differentially Private Data Analytics via Secure Sketching
Distributed Differentially Private Data Analytics via Secure Sketching
Jakob Burkhardt
Hannah Keller
Claudio Orlandi
Chris Schwiegelshohn
FedML
142
0
0
30 Nov 2024
Noise-Aware Differentially Private Variational Inference
Noise-Aware Differentially Private Variational Inference
Talal Alrawajfeh
Hibiki Ito
Antti Honkela
127
0
0
25 Oct 2024
Learning with Differential Privacy: Stability, Learnability and the
  Sufficiency and Necessity of ERM Principle
Learning with Differential Privacy: Stability, Learnability and the Sufficiency and Necessity of ERM Principle
Yu Wang
Jing Lei
S. Fienberg
78
103
0
23 Feb 2015
(Non-) asymptotic properties of Stochastic Gradient Langevin Dynamics
(Non-) asymptotic properties of Stochastic Gradient Langevin Dynamics
Sebastian J. Vollmer
K. Zygalakis
and Yee Whye Teh
87
49
0
02 Jan 2015
Preserving Statistical Validity in Adaptive Data Analysis
Preserving Statistical Validity in Adaptive Data Analysis
Cynthia Dwork
Vitaly Feldman
Moritz Hardt
T. Pitassi
Omer Reingold
Aaron Roth
97
376
0
10 Nov 2014
Differentially Private Empirical Risk Minimization: Efficient Algorithms
  and Tight Error Bounds
Differentially Private Empirical Risk Minimization: Efficient Algorithms and Tight Error Bounds
Raef Bassily
Adam D. Smith
Abhradeep Thakurta
FedML
148
371
0
27 May 2014
Stochastic Gradient Hamiltonian Monte Carlo
Stochastic Gradient Hamiltonian Monte Carlo
Tianqi Chen
E. Fox
Carlos Guestrin
BDL
114
913
0
17 Feb 2014
Bayesian Differential Privacy through Posterior Sampling
Bayesian Differential Privacy through Posterior Sampling
Christos Dimitrakakis
B. Nelson
and Zuhe Zhang
Aikaterini Mitrokotsa
Benjamin I. P. Rubinstein
89
118
0
05 Jun 2013
Bayesian Posterior Sampling via Stochastic Gradient Fisher Scoring
Bayesian Posterior Sampling via Stochastic Gradient Fisher Scoring
S. Ahn
Anoop Korattikara Balan
Max Welling
77
306
0
27 Jun 2012
Differentially Private Empirical Risk Minimization
Differentially Private Empirical Risk Minimization
Kamalika Chaudhuri
C. Monteleoni
Anand D. Sarwate
156
1,490
0
01 Dec 2009
Efficient, Differentially Private Point Estimators
Efficient, Differentially Private Point Estimators
Adam D. Smith
FedML
79
78
0
27 Sep 2008
On the `Semantics' of Differential Privacy: A Bayesian Formulation
On the `Semantics' of Differential Privacy: A Bayesian Formulation
S. Kasiviswanathan
Adam D. Smith
110
167
0
27 Mar 2008
Mixed membership stochastic blockmodels
Mixed membership stochastic blockmodels
E. Airoldi
David M. Blei
S. Fienberg
Eric Xing
511
2,122
0
30 May 2007
1