Concentrated Differential Privacy

6 March 2016

Papers citing "Concentrated Differential Privacy"

50 / 270 papers shown

Title
Recent Advances of Differential Privacy in Centralized Deep Learning: A Systematic Survey Lea Demelius Roman Kern Andreas Trügler SyDa FedML 36 6 0 28 Sep 2023
A Unifying Privacy Analysis Framework for Unknown Domain Algorithms in Differential Privacy Ryan Rogers FedML 25 1 0 17 Sep 2023
Concurrent Composition for Interactive Differential Privacy with Adaptive Privacy-Loss Parameters Samuel Haney Michael Shoemate Grace Tian Salil P. Vadhan Andrew Vyrros Vicki Xu Wanrong Zhang 11 6 0 12 Sep 2023
The Complexity of Verifying Boolean Programs as Differentially Private Mark Bun Marco Gaboardi Ludmila Glinskih 26 4 0 08 Sep 2023
Threshold KNN-Shapley: A Linear-Time and Privacy-Friendly Approach to Data Valuation Jiachen T. Wang Yuqing Zhu Yu-Xiang Wang R. Jia Prateek Mittal TDI 37 12 0 30 Aug 2023
Counting Distinct Elements Under Person-Level Differential Privacy Alexander Knop Thomas Steinke 22 3 0 24 Aug 2023
Batch Clipping and Adaptive Layerwise Clipping for Differential Private Stochastic Gradient Descent Toan N. Nguyen Phuong Ha Nguyen Lam M. Nguyen Marten van Dijk 17 1 0 21 Jul 2023
Probing the Transition to Dataset-Level Privacy in ML Models Using an Output-Specific and Data-Resolved Privacy Profile Tyler LeBlond Joseph Munoz Fred Lu Maya Fuchs Elliott Zaresky-Williams Edward Raff Brian Testa 16 3 0 27 Jun 2023
About the Cost of Central Privacy in Density Estimation Clément Lalanne Aurélien Garivier Rémi Gribonval 31 3 0 26 Jun 2023
Continual Release of Differentially Private Synthetic Data from Longitudinal Data Collections Mark Bun Marco Gaboardi Marcel Neunhoeffer Wanrong Zhang SyDa 29 7 0 13 Jun 2023
Personalized Graph Federated Learning with Differential Privacy François Gauthier Vinay Chakravarthi Gogineni Stefan Werner Yih-Fang Huang A. Kuh FedML 26 7 0 10 Jun 2023
Generating Private Synthetic Data with Genetic Algorithms Terrance Liu Jin-Lin Tang G. Vietri Zhiwei Steven Wu SyDa 21 16 0 05 Jun 2023
Less is More: Revisiting the Gaussian Mechanism for Differential Privacy Tianxi Ji Pan Li 11 0 0 04 Jun 2023
CRS-FL: Conditional Random Sampling for Communication-Efficient and Privacy-Preserving Federated Learning Jianhua Wang Xiaolin Chang J. Misic Vojislav B. Mišić Lin Li Yingying Yao FedML 19 3 0 01 Jun 2023
Concentrated Geo-Privacy Yuting Liang K. Yi 19 5 0 31 May 2023
Unleashing the Power of Randomization in Auditing Differentially Private ML Krishna Pillutla Galen Andrew Peter Kairouz H. B. McMahan Alina Oprea Sewoong Oh 38 20 0 29 May 2023
Faster Differentially Private Convex Optimization via Second-Order Methods Arun Ganesh Mahdi Haghifam Thomas Steinke Abhradeep Thakurta 19 10 0 22 May 2023
Differential Privacy with Random Projections and Sign Random Projections P. Li Xiaoyun Li 41 8 0 22 May 2023
Privacy Auditing with One (1) Training Run Thomas Steinke Milad Nasr Matthew Jagielski 53 77 0 15 May 2023
Privacy-Preserving In-Context Learning for Large Language Models Tong Wu Ashwinee Panda Jiachen T. Wang Prateek Mittal 53 29 0 02 May 2023
Mean Estimation Under Heterogeneous Privacy: Some Privacy Can Be Free Syomantak Chaudhuri T. Courtade 30 4 0 27 Apr 2023
Differential Privacy via Distributionally Robust Optimization Aras Selvi Huikang Liu W. Wiesemann 33 1 0 25 Apr 2023
A Polynomial Time, Pure Differentially Private Estimator for Binary Product Distributions Vikrant Singhal 37 9 0 13 Apr 2023
Differentially Private Stream Processing at Scale Bing Zhang Vadym Doroshenko Peter Kairouz Thomas Steinke Abhradeep Thakurta Zi-Tang Ma Eidan Cohen Himani Apte Jodi Spacek 28 7 0 31 Mar 2023
On the Query Complexity of Training Data Reconstruction in Private Learning Prateeti Mukherjee Satyanarayana V. Lokam 32 0 0 29 Mar 2023
Considerations on the Theory of Training Models with Differential Privacy Marten van Dijk Phuong Ha Nguyen FedML 28 2 0 08 Mar 2023
Faster high-accuracy log-concave sampling via algorithmic warm starts Jason M. Altschuler Sinho Chewi 29 34 0 20 Feb 2023
Breaking the Communication-Privacy-Accuracy Tradeoff with $f$ -Differential Privacy Richeng Jin Z. Su C. Zhong Zhaoyang Zhang Tony Q.S. Quek H. Dai FedML 29 2 0 19 Feb 2023
An Effective and Differentially Private Protocol for Secure Distributed Cardinality Estimation P. Wang Chengjin Yang Dongdong Xie Junzhou Zhao Hui Li Jing Tao Xiaohong Guan 24 2 0 04 Feb 2023
General Gaussian Noise Mechanisms and Their Optimality for Unbiased Mean Estimation Aleksandar Nikolov Haohua Tang 49 4 0 31 Jan 2023
Differentially Private Natural Language Models: Recent Advances and Future Directions Lijie Hu Ivan Habernal Lei Shen Di Wang AAML 30 18 0 22 Jan 2023
Differentially Private Confidence Intervals for Proportions under Stratified Random Sampling Shurong Lin Mark Bun Marco Gaboardi E. D. Kolaczyk Adam D. Smith 16 5 0 19 Jan 2023
Grafting Laplace and Gaussian distributions: A new noise mechanism for differential privacy Gokularam Muthukrishnan Sheetal Kalyani 28 12 0 19 Dec 2022
Generalizing DP-SGD with Shuffling and Batch Clipping Marten van Dijk Phuong Ha Nguyen Toan N. Nguyen Lam M. Nguyen 15 1 0 12 Dec 2022
Differentially Private Enhanced Permissioned Blockchain for Private Data Sharing in Industrial IoT Muhammad Islam M. H. Rehmani Jinjun Chen 23 8 0 30 Nov 2022
Provable Membership Inference Privacy Zachary Izzo Jinsung Yoon Sercan Ö. Arik James Zou 44 5 0 12 Nov 2022
Directional Privacy for Deep Learning Pedro Faustini Natasha Fernandes Shakila Mahjabin Tonni Annabelle McIver Mark Dras 19 1 0 09 Nov 2022
Privately Fine-Tuning Large Language Models with Differential Privacy R. Behnia Mohammadreza Ebrahimi Jason L. Pacheco B. Padmanabhan 29 44 0 26 Oct 2022
Differentially Private Language Models for Secure Data Sharing Justus Mattern Zhijing Jin Benjamin Weggenmann Bernhard Schoelkopf Mrinmaya Sachan SyDa 19 47 0 25 Oct 2022
DPIS: An Enhanced Mechanism for Differentially Private SGD with Importance Sampling Jianxin Wei Ergute Bao X. Xiao Yifan Yang 46 20 0 18 Oct 2022
Differentially Private Bootstrap: New Privacy Analysis and Inference Strategies Zhanyu Wang Guang Cheng Jordan Awan 34 9 0 12 Oct 2022
TAN Without a Burn: Scaling Laws of DP-SGD Tom Sander Pierre Stock Alexandre Sablayrolles FedML 44 42 0 07 Oct 2022
On the Statistical Complexity of Estimation and Testing under Privacy Constraints Clément Lalanne Aurélien Garivier Rémi Gribonval 27 7 0 05 Oct 2022
Composition of Differential Privacy & Privacy Amplification by Subsampling Thomas Steinke 64 50 0 02 Oct 2022
Algorithms with More Granular Differential Privacy Guarantees Badih Ghazi Ravi Kumar Pasin Manurangsi Thomas Steinke 62 6 0 08 Sep 2022
On the utility and protection of optimization with differential privacy and classic regularization techniques Eugenio Lomurno Matteo matteucci 29 9 0 07 Sep 2022
Age-Dependent Differential Privacy Meng Zhang Ermin Wei R. Berry Jianwei Huang 23 38 0 03 Sep 2022
Private Query Release via the Johnson-Lindenstrauss Transform Aleksandar Nikolov 17 14 0 15 Aug 2022
Stronger Privacy Amplification by Shuffling for Rényi and Approximate Differential Privacy Vitaly Feldman Audra McMillan Kunal Talwar FedML 29 47 0 09 Aug 2022
Differentially Private Learning of Hawkes Processes Mohsen Ghassemi Eleonora Kreavcić Niccolò Dalmasso Vamsi K. Potluru T. Balch Manuela Veloso 20 1 0 27 Jul 2022