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The Value of Privacy: Strategic Data Subjects, Incentive Mechanisms and
  Fundamental Limits

The Value of Privacy: Strategic Data Subjects, Incentive Mechanisms and Fundamental Limits

22 March 2016
Weina Wang
Lei Ying
Junshan Zhang
ArXiv (abs)PDFHTML

Papers citing "The Value of Privacy: Strategic Data Subjects, Incentive Mechanisms and Fundamental Limits"

6 / 6 papers shown
Online Linear Regression with Paid Stochastic Features
Online Linear Regression with Paid Stochastic Features
Nadav Merlis
Kyoungseok Jang
Nicolò Cesa-Bianchi
124
0
0
11 Nov 2025
Truthful Incentive Mechanism for Federated Learning with Crowdsourced
  Data Labeling
Truthful Incentive Mechanism for Federated Learning with Crowdsourced Data LabelingIEEE Conference on Computer Communications (IEEE INFOCOM), 2023
Yuxi Zhao
Xiaowen Gong
S. Mao
FedML
305
16
0
31 Jan 2023
A Distributed Privacy-Preserving Learning Dynamics in General Social
  Networks
A Distributed Privacy-Preserving Learning Dynamics in General Social NetworksIEEE Transactions on Knowledge and Data Engineering (TKDE), 2020
Youming Tao
Shuzhen Chen
Feng Li
Dongxiao Yu
Jiguo Yu
Hao Sheng
FedML
225
5
0
15 Nov 2020
Preserving privacy enables "co-existence equilibrium" of competitive
  diffusion in social networks
Preserving privacy enables "co-existence equilibrium" of competitive diffusion in social networksIEEE Transactions on Signal and Information Processing over Networks (TSIPN), 2017
Jun Zhao
Junshan Zhang
44
3
0
02 Nov 2019
REAP: An Efficient Incentive Mechanism for Reconciling Aggregation
  Accuracy and Individual Privacy in Crowdsensing
REAP: An Efficient Incentive Mechanism for Reconciling Aggregation Accuracy and Individual Privacy in Crowdsensing
Zhikun Zhang
Shibo He
Jiming Chen
Junshan Zhang
124
57
0
02 Nov 2017
De-anonymization of Social Networks with Communities: When
  Quantifications Meet Algorithms
De-anonymization of Social Networks with Communities: When Quantifications Meet Algorithms
Luoyi Fu
Xinzhe Fu
Zhongzhao Hu
Zhiying Xu
Xinbing Wang
363
19
0
27 Mar 2017
1
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