Differential Privacy Papers
@dppapers.bsky.social
🤖
new arXiv preprints mentioning "differential privacy" or "differentially private" in the title/abstract/metadata
- unrelated quantum/FL papers
+ updates from https://differentialprivacy.org
[Under construction.]
new arXiv preprints mentioning "differential privacy" or "differentially private" in the title/abstract/metadata
- unrelated quantum/FL papers
+ updates from https://differentialprivacy.org
[Under construction.]
November 12, 2025 at 4:53 AM
Neither Private Nor Fair: Impact of Data Imbalance on Utility and Fairness in Differential Privacy
Tom Farrand, Fatemehsadat Mireshghallah, Sahib Singh, Andrew Trask
http://arxiv.org/abs/2009.06389
Tom Farrand, Fatemehsadat Mireshghallah, Sahib Singh, Andrew Trask
http://arxiv.org/abs/2009.06389
November 12, 2025 at 4:53 AM
Neither Private Nor Fair: Impact of Data Imbalance on Utility and Fairness in Differential Privacy
Tom Farrand, Fatemehsadat Mireshghallah, Sahib Singh, Andrew Trask
http://arxiv.org/abs/2009.06389
Tom Farrand, Fatemehsadat Mireshghallah, Sahib Singh, Andrew Trask
http://arxiv.org/abs/2009.06389
Consistent Spectral Clustering of Network Block Models under Local Differential Privacy
Jonathan Hehir, Aleksandra Slavkovic, Xiaoyue Niu
http://arxiv.org/abs/2105.12615
Jonathan Hehir, Aleksandra Slavkovic, Xiaoyue Niu
http://arxiv.org/abs/2105.12615
November 12, 2025 at 4:53 AM
Consistent Spectral Clustering of Network Block Models under Local Differential Privacy
Jonathan Hehir, Aleksandra Slavkovic, Xiaoyue Niu
http://arxiv.org/abs/2105.12615
Jonathan Hehir, Aleksandra Slavkovic, Xiaoyue Niu
http://arxiv.org/abs/2105.12615
Differentially Private Graph Classification with GNNs
Tamara T. Mueller, Johannes C. Paetzold, Chinmay Prabhakar, Dmitrii Usynin, Daniel Rueckert, Georgios Kaissis
http://arxiv.org/abs/2202.02575
Tamara T. Mueller, Johannes C. Paetzold, Chinmay Prabhakar, Dmitrii Usynin, Daniel Rueckert, Georgios Kaissis
http://arxiv.org/abs/2202.02575
November 12, 2025 at 4:53 AM
Differentially Private Graph Classification with GNNs
Tamara T. Mueller, Johannes C. Paetzold, Chinmay Prabhakar, Dmitrii Usynin, Daniel Rueckert, Georgios Kaissis
http://arxiv.org/abs/2202.02575
Tamara T. Mueller, Johannes C. Paetzold, Chinmay Prabhakar, Dmitrii Usynin, Daniel Rueckert, Georgios Kaissis
http://arxiv.org/abs/2202.02575
Privacy, Security, and Utility Analysis of Differentially Private CPES Data
Md Tamjid Hossain, Shahriar Badsha, Haoting Shen
http://arxiv.org/abs/2109.09963
Md Tamjid Hossain, Shahriar Badsha, Haoting Shen
http://arxiv.org/abs/2109.09963
November 12, 2025 at 4:53 AM
Privacy, Security, and Utility Analysis of Differentially Private CPES Data
Md Tamjid Hossain, Shahriar Badsha, Haoting Shen
http://arxiv.org/abs/2109.09963
Md Tamjid Hossain, Shahriar Badsha, Haoting Shen
http://arxiv.org/abs/2109.09963
Renyi Differential Privacy of Propose-Test-Release and Applications to Private and Robust Machine Learning
Jiachen T. Wang, Saeed Mahloujifar, Shouda Wang, Ruoxi Jia, Prateek Mittal
http://arxiv.org/abs/2209.07716
Jiachen T. Wang, Saeed Mahloujifar, Shouda Wang, Ruoxi Jia, Prateek Mittal
http://arxiv.org/abs/2209.07716
November 12, 2025 at 4:53 AM
Renyi Differential Privacy of Propose-Test-Release and Applications to Private and Robust Machine Learning
Jiachen T. Wang, Saeed Mahloujifar, Shouda Wang, Ruoxi Jia, Prateek Mittal
http://arxiv.org/abs/2209.07716
Jiachen T. Wang, Saeed Mahloujifar, Shouda Wang, Ruoxi Jia, Prateek Mittal
http://arxiv.org/abs/2209.07716
November 12, 2025 at 4:53 AM
Differentially Private Normalizing Flows for Privacy-Preserving Density Estimation
Chris Waites, Rachel Cummings
http://arxiv.org/abs/2103.14068
Chris Waites, Rachel Cummings
http://arxiv.org/abs/2103.14068
November 12, 2025 at 4:53 AM
Differentially Private Normalizing Flows for Privacy-Preserving Density Estimation
Chris Waites, Rachel Cummings
http://arxiv.org/abs/2103.14068
Chris Waites, Rachel Cummings
http://arxiv.org/abs/2103.14068
November 12, 2025 at 4:53 AM
Differentially Private Distributed Optimization
Zhenqi Huang, Sayan Mitra, Nitin Vaidya
http://arxiv.org/abs/1401.2596
Zhenqi Huang, Sayan Mitra, Nitin Vaidya
http://arxiv.org/abs/1401.2596
November 12, 2025 at 4:53 AM
Differentially Private Distributed Optimization
Zhenqi Huang, Sayan Mitra, Nitin Vaidya
http://arxiv.org/abs/1401.2596
Zhenqi Huang, Sayan Mitra, Nitin Vaidya
http://arxiv.org/abs/1401.2596
Compressive Mechanism: Utilizing Sparse Representation in Differential Privacy
Yang D. Li, Zhenjie Zhang, Marianne Winslett, Yin Yang
http://arxiv.org/abs/1107.3350
Yang D. Li, Zhenjie Zhang, Marianne Winslett, Yin Yang
http://arxiv.org/abs/1107.3350
November 12, 2025 at 4:53 AM
Compressive Mechanism: Utilizing Sparse Representation in Differential Privacy
Yang D. Li, Zhenjie Zhang, Marianne Winslett, Yin Yang
http://arxiv.org/abs/1107.3350
Yang D. Li, Zhenjie Zhang, Marianne Winslett, Yin Yang
http://arxiv.org/abs/1107.3350
The Value of Collaboration in Convex Machine Learning with Differential Privacy
Nan Wu, Farhad Farokhi, David Smith, Mohamed Ali Kaafar
http://arxiv.org/abs/1906.09679
Nan Wu, Farhad Farokhi, David Smith, Mohamed Ali Kaafar
http://arxiv.org/abs/1906.09679
November 12, 2025 at 4:53 AM
The Value of Collaboration in Convex Machine Learning with Differential Privacy
Nan Wu, Farhad Farokhi, David Smith, Mohamed Ali Kaafar
http://arxiv.org/abs/1906.09679
Nan Wu, Farhad Farokhi, David Smith, Mohamed Ali Kaafar
http://arxiv.org/abs/1906.09679
Scalable and Provably Accurate Algorithms for Differentially Private Distributed Decision Tree Learning
Kaiwen Wang, Travis Dick, Maria-Florina Balcan
http://arxiv.org/abs/2012.10602
Kaiwen Wang, Travis Dick, Maria-Florina Balcan
http://arxiv.org/abs/2012.10602
November 12, 2025 at 4:53 AM
Scalable and Provably Accurate Algorithms for Differentially Private Distributed Decision Tree Learning
Kaiwen Wang, Travis Dick, Maria-Florina Balcan
http://arxiv.org/abs/2012.10602
Kaiwen Wang, Travis Dick, Maria-Florina Balcan
http://arxiv.org/abs/2012.10602
Differentially Private Bayesian Persuasion
Yuqi Pan, Zhiwei Steven Wu, Haifeng Xu, Shuran Zheng
http://arxiv.org/abs/2402.15872
Yuqi Pan, Zhiwei Steven Wu, Haifeng Xu, Shuran Zheng
http://arxiv.org/abs/2402.15872
November 12, 2025 at 4:53 AM
Differentially Private Bayesian Persuasion
Yuqi Pan, Zhiwei Steven Wu, Haifeng Xu, Shuran Zheng
http://arxiv.org/abs/2402.15872
Yuqi Pan, Zhiwei Steven Wu, Haifeng Xu, Shuran Zheng
http://arxiv.org/abs/2402.15872
Concentrated Differentially Private Gradient Descent with Adaptive per-Iteration Privacy Budget
Jaewoo Lee, Daniel Kifer
http://arxiv.org/abs/1808.09501
Jaewoo Lee, Daniel Kifer
http://arxiv.org/abs/1808.09501
November 12, 2025 at 4:53 AM
Concentrated Differentially Private Gradient Descent with Adaptive per-Iteration Privacy Budget
Jaewoo Lee, Daniel Kifer
http://arxiv.org/abs/1808.09501
Jaewoo Lee, Daniel Kifer
http://arxiv.org/abs/1808.09501
Differentially Private Representation for NLP: Formal Guarantee and An Empirical Study on Privacy and Fairness
Lingjuan Lyu, Xuanli He, Yitong Li
http://arxiv.org/abs/2010.01285
Lingjuan Lyu, Xuanli He, Yitong Li
http://arxiv.org/abs/2010.01285
November 12, 2025 at 4:53 AM
Differentially Private Representation for NLP: Formal Guarantee and An Empirical Study on Privacy and Fairness
Lingjuan Lyu, Xuanli He, Yitong Li
http://arxiv.org/abs/2010.01285
Lingjuan Lyu, Xuanli He, Yitong Li
http://arxiv.org/abs/2010.01285
Privacy in Feedback: The Differentially Private LQG
Matthew Hale, Austin Jones, Kevin Leahy
http://arxiv.org/abs/1709.02862
Matthew Hale, Austin Jones, Kevin Leahy
http://arxiv.org/abs/1709.02862
November 12, 2025 at 4:53 AM
Privacy in Feedback: The Differentially Private LQG
Matthew Hale, Austin Jones, Kevin Leahy
http://arxiv.org/abs/1709.02862
Matthew Hale, Austin Jones, Kevin Leahy
http://arxiv.org/abs/1709.02862
November 12, 2025 at 4:53 AM
Differential Privacy for Credit Risk Model
Tabish Maniar, Alekhya Akkinepally, Anantha Sharma
http://arxiv.org/abs/2106.15343
Tabish Maniar, Alekhya Akkinepally, Anantha Sharma
http://arxiv.org/abs/2106.15343
November 12, 2025 at 4:53 AM
Differential Privacy for Credit Risk Model
Tabish Maniar, Alekhya Akkinepally, Anantha Sharma
http://arxiv.org/abs/2106.15343
Tabish Maniar, Alekhya Akkinepally, Anantha Sharma
http://arxiv.org/abs/2106.15343
MVG Mechanism: Differential Privacy under Matrix-Valued Query
Thee Chanyaswad, Alex Dytso, H. Vincent Poor, Prateek Mittal
http://arxiv.org/abs/1801.00823
Thee Chanyaswad, Alex Dytso, H. Vincent Poor, Prateek Mittal
http://arxiv.org/abs/1801.00823
November 12, 2025 at 4:53 AM
MVG Mechanism: Differential Privacy under Matrix-Valued Query
Thee Chanyaswad, Alex Dytso, H. Vincent Poor, Prateek Mittal
http://arxiv.org/abs/1801.00823
Thee Chanyaswad, Alex Dytso, H. Vincent Poor, Prateek Mittal
http://arxiv.org/abs/1801.00823
Publishing Community-Preserving Attributed Social Graphs with a Differential Privacy Guarantee
Xihui Chen, Sjouke Mauw, Yunior Ramírez-Cruz
http://arxiv.org/abs/1909.00280
Xihui Chen, Sjouke Mauw, Yunior Ramírez-Cruz
http://arxiv.org/abs/1909.00280
November 12, 2025 at 4:53 AM
Publishing Community-Preserving Attributed Social Graphs with a Differential Privacy Guarantee
Xihui Chen, Sjouke Mauw, Yunior Ramírez-Cruz
http://arxiv.org/abs/1909.00280
Xihui Chen, Sjouke Mauw, Yunior Ramírez-Cruz
http://arxiv.org/abs/1909.00280
Composition of Differential Privacy & Privacy Amplification by Subsampling
Thomas Steinke
http://arxiv.org/abs/2210.00597
Thomas Steinke
http://arxiv.org/abs/2210.00597
November 12, 2025 at 4:53 AM
Composition of Differential Privacy & Privacy Amplification by Subsampling
Thomas Steinke
http://arxiv.org/abs/2210.00597
Thomas Steinke
http://arxiv.org/abs/2210.00597
Learning to be adversarially robust and differentially private
Jamie Hayes, Borja Balle, M. Pawan Kumar
http://arxiv.org/abs/2201.02265
Jamie Hayes, Borja Balle, M. Pawan Kumar
http://arxiv.org/abs/2201.02265
November 12, 2025 at 4:53 AM
Learning to be adversarially robust and differentially private
Jamie Hayes, Borja Balle, M. Pawan Kumar
http://arxiv.org/abs/2201.02265
Jamie Hayes, Borja Balle, M. Pawan Kumar
http://arxiv.org/abs/2201.02265
Privacy-Preserving Student Learning with Differentially Private Data-Free Distillation
Bochao Liu, Jianghu Lu, Pengju Wang, Junjie Zhang, Dan Zeng, Zhenxing Qian, Shiming Ge
http://arxiv.org/abs/2409.12384
Bochao Liu, Jianghu Lu, Pengju Wang, Junjie Zhang, Dan Zeng, Zhenxing Qian, Shiming Ge
http://arxiv.org/abs/2409.12384
November 12, 2025 at 4:53 AM
Privacy-Preserving Student Learning with Differentially Private Data-Free Distillation
Bochao Liu, Jianghu Lu, Pengju Wang, Junjie Zhang, Dan Zeng, Zhenxing Qian, Shiming Ge
http://arxiv.org/abs/2409.12384
Bochao Liu, Jianghu Lu, Pengju Wang, Junjie Zhang, Dan Zeng, Zhenxing Qian, Shiming Ge
http://arxiv.org/abs/2409.12384
Auditing Differentially Private Machine Learning: How Private is Private SGD?
Matthew Jagielski, Jonathan Ullman, Alina Oprea
http://arxiv.org/abs/2006.07709
Matthew Jagielski, Jonathan Ullman, Alina Oprea
http://arxiv.org/abs/2006.07709
November 12, 2025 at 4:53 AM
Auditing Differentially Private Machine Learning: How Private is Private SGD?
Matthew Jagielski, Jonathan Ullman, Alina Oprea
http://arxiv.org/abs/2006.07709
Matthew Jagielski, Jonathan Ullman, Alina Oprea
http://arxiv.org/abs/2006.07709