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Privacy Against Statistical Inference

Privacy Against Statistical Inference

8 October 2012
Flavio du Pin Calmon
N. Fawaz
    FedML
ArXiv (abs)PDFHTML

Papers citing "Privacy Against Statistical Inference"

50 / 82 papers shown
Title
Breaking the Gaussian Barrier: Residual-PAC Privacy for Automatic Privatization
Breaking the Gaussian Barrier: Residual-PAC Privacy for Automatic Privatization
Tao Zhang
Yevgeniy Vorobeychik
20
0
0
06 Jun 2025
Analyzing Inference Privacy Risks Through Gradients in Machine Learning
Analyzing Inference Privacy Risks Through Gradients in Machine Learning
Zhuohang Li
Andrew Lowy
Jing Liu
T. Koike-Akino
K. Parsons
Bradley Malin
Ye Wang
FedML
64
1
0
29 Aug 2024
Information Density Bounds for Privacy
Information Density Bounds for Privacy
Sara Saeidian
Leonhard Grosse
Parastoo Sadeghi
Mikael Skoglund
T. Oechtering
60
1
0
01 Jul 2024
Federated Graph Condensation with Information Bottleneck Principles
Federated Graph Condensation with Information Bottleneck Principles
Bo Yan
DDFedML
75
4
0
07 May 2024
Maximal $α$-Leakage for Quantum Privacy Mechanisms
Maximal ααα-Leakage for Quantum Privacy Mechanisms
Bo-Yu Yang
Hsuan Yu
Hao-Chung Cheng
52
0
0
21 Mar 2024
Quantifying Privacy via Information Density
Quantifying Privacy via Information Density
Leonhard Grosse
Sara Saeidian
Parastoo Sadeghi
T. Oechtering
Mikael Skoglund
24
5
0
20 Feb 2024
Privacy for Fairness: Information Obfuscation for Fair Representation
  Learning with Local Differential Privacy
Privacy for Fairness: Information Obfuscation for Fair Representation Learning with Local Differential Privacy
Songjie Xie
Youlong Wu
Jiaxuan Li
Ming Ding
Khaled B. Letaief
AAML
59
1
0
16 Feb 2024
Approximation of Pufferfish Privacy for Gaussian Priors
Approximation of Pufferfish Privacy for Gaussian Priors
Ni Ding
FedML
40
0
0
22 Jan 2024
Online Context-aware Data Release with Sequence Information Privacy
Online Context-aware Data Release with Sequence Information Privacy
Bo Jiang
Ming Li
Ravi Tandon
34
2
0
26 Jul 2023
A Meta-learning Framework for Tuning Parameters of Protection Mechanisms
  in Trustworthy Federated Learning
A Meta-learning Framework for Tuning Parameters of Protection Mechanisms in Trustworthy Federated Learning
Xiaojin Zhang
Yan Kang
Lixin Fan
Kai Chen
Qiang Yang
FedML
49
6
0
28 May 2023
Theoretically Principled Federated Learning for Balancing Privacy and
  Utility
Theoretically Principled Federated Learning for Balancing Privacy and Utility
Xiaojin Zhang
Wenjie Li
Kai Chen
Shutao Xia
Qian Yang
FedML
49
9
0
24 May 2023
Towards Achieving Near-optimal Utility for Privacy-Preserving Federated
  Learning via Data Generation and Parameter Distortion
Towards Achieving Near-optimal Utility for Privacy-Preserving Federated Learning via Data Generation and Parameter Distortion
Xiaojin Zhang
Kai Chen
Qian Yang
FedML
58
5
0
07 May 2023
Bounding the Invertibility of Privacy-preserving Instance Encoding using
  Fisher Information
Bounding the Invertibility of Privacy-preserving Instance Encoding using Fisher Information
Kiwan Maeng
Chuan Guo
Sanjay Kariyappa
G. E. Suh
75
8
0
06 May 2023
Optimizing Privacy, Utility and Efficiency in Constrained
  Multi-Objective Federated Learning
Optimizing Privacy, Utility and Efficiency in Constrained Multi-Objective Federated Learning
Yan Kang
Hanlin Gu
Xingxing Tang
Yuanqin He
Yuzhu Zhang
Jinnan He
Yuxing Han
Lixin Fan
Kai Chen
Qiang Yang
FedML
117
19
0
29 Apr 2023
Pointwise Maximal Leakage on General Alphabets
Pointwise Maximal Leakage on General Alphabets
Sara Saeidian
Giulia Cervia
T. Oechtering
Mikael Skoglund
47
5
0
16 Apr 2023
A Game-theoretic Framework for Privacy-preserving Federated Learning
A Game-theoretic Framework for Privacy-preserving Federated Learning
Xiaojin Zhang
Lixin Fan
Si-Yi Wang
Wenjie Li
Kai Chen
Qiang Yang
FedML
48
4
0
11 Apr 2023
Probably Approximately Correct Federated Learning
Probably Approximately Correct Federated Learning
Xiaojin Zhang
Anbu Huang
Lixin Fan
Kai Chen
Qiang Yang
FedML
74
5
0
10 Apr 2023
Can Querying for Bias Leak Protected Attributes? Achieving Privacy With
  Smooth Sensitivity
Can Querying for Bias Leak Protected Attributes? Achieving Privacy With Smooth Sensitivity
Faisal Hamman
Jiahao Chen
Sanghamitra Dutta
59
9
0
03 Nov 2022
Explaining epsilon in local differential privacy through the lens of
  quantitative information flow
Explaining epsilon in local differential privacy through the lens of quantitative information flow
Natasha Fernandes
Annabelle McIver
Parastoo Sadeghi
PILM
40
2
0
24 Oct 2022
Trading Off Privacy, Utility and Efficiency in Federated Learning
Trading Off Privacy, Utility and Efficiency in Federated Learning
Xiaojin Zhang
Yan Kang
Kai Chen
Lixin Fan
Qiang Yang
FedML
120
55
0
01 Sep 2022
Deep Joint Source-Channel and Encryption Coding: Secure Semantic
  Communications
Deep Joint Source-Channel and Encryption Coding: Secure Semantic Communications
Tze-Yang Tung
Deniz Gunduz
BDL
89
50
0
19 Aug 2022
Bottlenecks CLUB: Unifying Information-Theoretic Trade-offs Among
  Complexity, Leakage, and Utility
Bottlenecks CLUB: Unifying Information-Theoretic Trade-offs Among Complexity, Leakage, and Utility
Behrooz Razeghi
Flavio du Pin Calmon
Deniz Gunduz
Svyatoslav Voloshynovskiy
58
16
0
11 Jul 2022
Classification Utility, Fairness, and Compactness via Tunable
  Information Bottleneck and Rényi Measures
Classification Utility, Fairness, and Compactness via Tunable Information Bottleneck and Rényi Measures
A. Gronowski
William Paul
F. Alajaji
Bahman Gharesifard
Philippe Burlina
FaML
56
3
0
20 Jun 2022
No Free Lunch Theorem for Security and Utility in Federated Learning
No Free Lunch Theorem for Security and Utility in Federated Learning
Xiaojin Zhang
Hanlin Gu
Lixin Fan
Kai Chen
Qiang Yang
FedML
92
66
0
11 Mar 2022
Active Privacy-Utility Trade-off Against Inference in Time-Series Data
  Sharing
Active Privacy-Utility Trade-off Against Inference in Time-Series Data Sharing
Ece Naz Erdemir
Pier Luigi Dragotti
Deniz Gunduz
47
8
0
11 Feb 2022
Lossy Compression of Noisy Data for Private and Data-Efficient Learning
Lossy Compression of Noisy Data for Private and Data-Efficient Learning
Berivan Isik
Tsachy Weissman
64
3
0
07 Feb 2022
Kantorovich Mechanism for Pufferfish Privacy
Kantorovich Mechanism for Pufferfish Privacy
Ni Ding
57
3
0
19 Jan 2022
HyObscure: Hybrid Obscuring for Privacy-Preserving Data Publishing
HyObscure: Hybrid Obscuring for Privacy-Preserving Data Publishing
Xiao Han
Yuncong Yang
Junjie Wu
48
1
0
15 Dec 2021
Privacy-Aware Communication Over a Wiretap Channel with Generative
  Networks
Privacy-Aware Communication Over a Wiretap Channel with Generative Networks
Ece Naz Erdemir
Pier Luigi Dragotti
Deniz Gunduz
82
24
0
08 Oct 2021
Subset Privacy: Draw from an Obfuscated Urn
Subset Privacy: Draw from an Obfuscated Urn
G. Wang
Jie Ding
39
2
0
02 Jul 2021
A Survey of Privacy Vulnerabilities of Mobile Device Sensors
A Survey of Privacy Vulnerabilities of Mobile Device Sensors
Paula Delgado-Santos
Giuseppe Stragapede
Ruben Tolosana
R. Guest
F. Deravi
R. Vera-Rodríguez
PILM
73
47
0
18 Jun 2021
Interval Privacy: A Framework for Privacy-Preserving Data Collection
Interval Privacy: A Framework for Privacy-Preserving Data Collection
Jie Ding
Bangjun Ding
75
6
0
17 Jun 2021
Privacy Assessment of Federated Learning using Private Personalized
  Layers
Privacy Assessment of Federated Learning using Private Personalized Layers
T. Jourdan
A. Boutet
Carole Frindel
FedML
70
7
0
15 Jun 2021
Distributed Banach-Picard Iteration for Locally Contractive Maps
Distributed Banach-Picard Iteration for Locally Contractive Maps
Francisco Andrade
Mário A. T. Figueiredo
J. Xavier
51
2
0
31 Mar 2021
Active Privacy-utility Trade-off Against a Hypothesis Testing Adversary
Active Privacy-utility Trade-off Against a Hypothesis Testing Adversary
Ece Naz Erdemir
Pier Luigi Dragotti
Deniz Gunduz
75
9
0
16 Feb 2021
Impact of Data Processing on Fairness in Supervised Learning
Impact of Data Processing on Fairness in Supervised Learning
S. Khodadadian
AmirEmad Ghassami
Negar Kiyavash
FaML
36
6
0
03 Feb 2021
Privacy-Constrained Policies via Mutual Information Regularized Policy
  Gradients
Privacy-Constrained Policies via Mutual Information Regularized Policy Gradients
Chris Cundy
Rishi Desai
Stefano Ermon
OffRL
116
4
0
30 Dec 2020
Fundamental Limits of Obfuscation for Linear Gaussian Dynamical Systems:
  An Information-Theoretic Approach
Fundamental Limits of Obfuscation for Linear Gaussian Dynamical Systems: An Information-Theoretic Approach
Song Fang
Quanyan Zhu
39
3
0
29 Oct 2020
Non-Stochastic Private Function Evaluation
Non-Stochastic Private Function Evaluation
F. Farokhi
G. Nair
55
3
0
20 Oct 2020
Learning, compression, and leakage: Minimising classification error via
  meta-universal compression principles
Learning, compression, and leakage: Minimising classification error via meta-universal compression principles
F. Rosas
P. Mediano
Michael C. Gastpar
27
10
0
14 Oct 2020
Data-driven Regularized Inference Privacy
Data-driven Regularized Inference Privacy
C. Wang
Wee Peng Tay
83
3
0
10 Oct 2020
Privacy in Targeted Advertising: A Survey
Privacy in Targeted Advertising: A Survey
Imdad Ullah
R. Boreli
S. Kanhere
49
18
0
15 Sep 2020
Information Laundering for Model Privacy
Information Laundering for Model Privacy
Xinran Wang
Yu Xiang
Jun Gao
Jie Ding
26
24
0
13 Sep 2020
On Perfect Obfuscation: Local Information Geometry Analysis
On Perfect Obfuscation: Local Information Geometry Analysis
Behrooz Razeghi
Flavio du Pin Calmon
Deniz Gunduz
Svyatoslav Voloshynovskiy
50
14
0
09 Sep 2020
Imitation Privacy
Imitation Privacy
Xun Xian
Xinran Wang
Mingyi Hong
Jie Ding
R. Ghanadan
53
3
0
30 Aug 2020
Robust Machine Learning via Privacy/Rate-Distortion Theory
Robust Machine Learning via Privacy/Rate-Distortion Theory
Ye Wang
Shuchin Aeron
Adnan Siraj Rakin
T. Koike-Akino
P. Moulin
OOD
62
6
0
22 Jul 2020
No-Go Theorems for Data Privacy
No-Go Theorems for Data Privacy
T. Studer
18
2
0
28 May 2020
Operationalizing the Legal Principle of Data Minimization for
  Personalization
Operationalizing the Legal Principle of Data Minimization for Personalization
Asia J. Biega
P. Potash
Hal Daumé
Fernando Diaz
Michèle Finck
AILaw
91
70
0
28 May 2020
Assisted Learning: A Framework for Multi-Organization Learning
Assisted Learning: A Framework for Multi-Organization Learning
Xun Xian
Xinran Wang
Jie Ding
R. Ghanadan
FedML
47
1
0
01 Apr 2020
To Split or Not to Split: The Impact of Disparate Treatment in
  Classification
To Split or Not to Split: The Impact of Disparate Treatment in Classification
Hao Wang
Hsiang Hsu
Mario Díaz
Flavio du Pin Calmon
112
23
0
12 Feb 2020
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