ResearchTrend.AI
  • Papers
  • Communities
  • Organizations
  • 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. 1706.08839
  4. Cited By
Preserving Differential Privacy in Convolutional Deep Belief Networks
v1v2 (latest)

Preserving Differential Privacy in Convolutional Deep Belief Networks

25 June 2017
Nhathai Phan
Xintao Wu
Dejing Dou
ArXiv (abs)PDFHTML

Papers citing "Preserving Differential Privacy in Convolutional Deep Belief Networks"

13 / 13 papers shown
Title
A Differentially Private Framework for Deep Learning with Convexified
  Loss Functions
A Differentially Private Framework for Deep Learning with Convexified Loss Functions
Zhigang Lu
Hassan Jameel Asghar
M. Kâafar
Darren Webb
Peter Dickinson
120
15
0
03 Apr 2022
A Differentially Private Multi-Output Deep Generative Networks Approach
  For Activity Diary Synthesis
A Differentially Private Multi-Output Deep Generative Networks Approach For Activity Diary Synthesis
Godwin Badu-Marfo
Bilal Farooq
Zachary Patterson
53
4
0
29 Dec 2020
Differentially Private Synthetic Data: Applied Evaluations and
  Enhancements
Differentially Private Synthetic Data: Applied Evaluations and Enhancements
Lucas Rosenblatt
Xiao-Yang Liu
Samira Pouyanfar
Eduardo de Leon
Anuj M. Desai
Joshua Allen
SyDa
74
68
0
11 Nov 2020
Differentially Private Bayesian Inference for Generalized Linear Models
Differentially Private Bayesian Inference for Generalized Linear Models
Tejas D. Kulkarni
Hibiki Ito
A. Koskela
Samuel Kaski
Antti Honkela
103
31
0
01 Nov 2020
imdpGAN: Generating Private and Specific Data with Generative
  Adversarial Networks
imdpGAN: Generating Private and Specific Data with Generative Adversarial Networks
Saurabh Gupta
Arun Balaji Buduru
Ponnurangam Kumaraguru
44
3
0
29 Sep 2020
Quantifying Membership Inference Vulnerability via Generalization Gap
  and Other Model Metrics
Quantifying Membership Inference Vulnerability via Generalization Gap and Other Model Metrics
Jason Bentley
Daniel Gibney
Gary Hoppenworth
Sumit Kumar Jha
MIACV
62
18
0
11 Sep 2020
An Overview of Privacy in Machine Learning
An Overview of Privacy in Machine Learning
Emiliano De Cristofaro
SILM
97
87
0
18 May 2020
Privacy in Deep Learning: A Survey
Privacy in Deep Learning: A Survey
Fatemehsadat Mirshghallah
Mohammadkazem Taram
Praneeth Vepakomma
Abhishek Singh
Ramesh Raskar
H. Esmaeilzadeh
FedML
153
141
0
25 Apr 2020
Interpretable and Differentially Private Predictions
Interpretable and Differentially Private Predictions
Frederik Harder
Matthias Bauer
Mijung Park
FAtt
98
54
0
05 Jun 2019
Evaluating Differentially Private Machine Learning in Practice
Evaluating Differentially Private Machine Learning in Practice
Bargav Jayaraman
David Evans
166
7
0
24 Feb 2019
No Peek: A Survey of private distributed deep learning
No Peek: A Survey of private distributed deep learning
Praneeth Vepakomma
Tristan Swedish
Ramesh Raskar
O. Gupta
Abhimanyu Dubey
SyDaFedML
86
100
0
08 Dec 2018
Security and Privacy Issues in Deep Learning
Security and Privacy Issues in Deep Learning
Ho Bae
Jaehee Jang
Dahuin Jung
Hyemi Jang
Heonseok Ha
Hyungyu Lee
Sungroh Yoon
SILMMIACV
158
79
0
31 Jul 2018
Differentially Private Generative Adversarial Network
Differentially Private Generative Adversarial Network
Liyang Xie
Kaixiang Lin
Shu Wang
Fei Wang
Jiayu Zhou
SyDa
124
507
0
19 Feb 2018
1