Concentrated Differential Privacy

6 March 2016

Papers citing "Concentrated Differential Privacy"

50 / 270 papers shown

Title
Conformal-DP: Differential Privacy on Riemannian Manifolds via Conformal Transformation Peilin He Liou Tang M. Amin Rahimian James Joshi 33 0 0 29 Apr 2025
Differentially Private Geodesic and Linear Regression Aditya Kulkarni Carlos Soto 28 0 0 15 Apr 2025
Towards Optimal Differentially Private Regret Bounds in Linear MDPs Sharan Sahu 60 0 0 12 Apr 2025
Empirical Calibration and Metric Differential Privacy in Language Models Pedro Faustini Natasha Fernandes Annabelle McIver Mark Dras 65 0 0 18 Mar 2025
PREAMBLE: Private and Efficient Aggregation of Block Sparse Vectors and Applications Hilal Asi Vitaly Feldman Hannah Keller G. Rothblum Kunal Talwar FedML 59 1 0 14 Mar 2025
$(\varepsilon, δ)$ Considered Harmful: Best Practices for Reporting Differential Privacy Guarantees Juan Felipe Gomez B. Kulynych G. Kaissis Jamie Hayes Borja Balle Antti Honkela 56 0 0 13 Mar 2025
Trustworthy Machine Learning via Memorization and the Granular Long-Tail: A Survey on Interactions, Tradeoffs, and Beyond Qiongxiu Li Xiaoyu Luo Yiyi Chen Johannes Bjerva 48 0 0 10 Mar 2025
Balls-and-Bins Sampling for DP-SGD Lynn Chua Badih Ghazi Charlie Harrison Ethan Leeman Pritish Kamath Ravi Kumar Pasin Manurangsi Amer Sinha Chiyuan Zhang 80 4 0 21 Dec 2024
But Can You Use It? Design Recommendations for Differentially Private Interactive Systems Liudas Panavas Joshua Snoke Erika Tyagi C. Bowen Aaron R. Williams 82 0 0 16 Dec 2024
Meeting Utility Constraints in Differential Privacy: A Privacy-Boosting Approach Bo Jiang Wanrong Zhang Donghang Lu Jian Du Sagar Sharma Qiang Yan 78 0 0 13 Dec 2024
Differentially Private Learned Indexes Jianzhang Du Tilak Mudgal Rutvi Rahul Gadre Yukui Luo Chenghong Wang FedML 24 0 0 28 Oct 2024
Privacy without Noisy Gradients: Slicing Mechanism for Generative Model Training Kristjan Greenewald Yuancheng Yu Hao Wang Kai Xu 36 0 0 25 Oct 2024
DMM: Distributed Matrix Mechanism for Differentially-Private Federated Learning using Packed Secret Sharing Alexander Bienstock Ujjwal Kumar Antigoni Polychroniadou FedML 39 0 0 21 Oct 2024
Differential Privacy on Trust Graphs Badih Ghazi Ravi Kumar Pasin Manurangsi Serena Wang 23 1 0 15 Oct 2024
The 2020 United States Decennial Census Is More Private Than You (Might) Think Buxin Su Weijie J. Su Chendi Wang 39 3 0 11 Oct 2024
Privately Learning Smooth Distributions on the Hypercube by Projections Clément Lalanne Sébastien Gadat 38 1 0 16 Sep 2024
A Statistical Viewpoint on Differential Privacy: Hypothesis Testing, Representation and Blackwell's Theorem Weijie J. Su 31 1 0 14 Sep 2024
Protecting Activity Sensing Data Privacy Using Hierarchical Information Dissociation Guangjing Wang Hanqing Guo Yuanda Wang Bocheng Chen Ce Zhou Qiben Yan 35 0 0 04 Sep 2024
Differentially Private Stochastic Gradient Descent with Fixed-Size Minibatches: Tighter RDP Guarantees with or without Replacement Jeremiah Birrell Reza Ebrahimi R. Behnia Jason L. Pacheco 46 0 0 19 Aug 2024
Differential Private Stochastic Optimization with Heavy-tailed Data: Towards Optimal Rates Puning Zhao Xiaogang Xu Zhe Liu Chong Wang Rongfei Fan Qingming Li 48 1 0 19 Aug 2024
Smooth Sensitivity Revisited: Towards Optimality Richard Hladík Jakub Tetek 40 0 0 06 Jul 2024
Correlated Privacy Mechanisms for Differentially Private Distributed Mean Estimation Sajani Vithana V. Cadambe Flavio du Pin Calmon Haewon Jeong FedML 50 1 0 03 Jul 2024
Attack-Aware Noise Calibration for Differential Privacy B. Kulynych Juan Felipe Gomez G. Kaissis Flavio du Pin Calmon Carmela Troncoso 57 6 0 02 Jul 2024
On Convex Optimization with Semi-Sensitive Features Badih Ghazi Pritish Kamath Ravi Kumar Pasin Manurangsi Raghu Meka Chiyuan Zhang 25 0 0 27 Jun 2024
Centering Policy and Practice: Research Gaps around Usable Differential Privacy Rachel Cummings Jayshree Sarathy 38 7 0 17 Jun 2024
Private Geometric Median Mahdi Haghifam Thomas Steinke Jonathan R. Ullman 33 0 0 11 Jun 2024
PriME: Privacy-aware Membership profile Estimation in networks Abhinav Chakraborty Sayak Chatterjee Sagnik Nandy 26 1 0 04 Jun 2024
Avoiding Pitfalls for Privacy Accounting of Subsampled Mechanisms under Composition C. Lebeda Matthew Regehr Gautam Kamath Thomas Steinke 53 9 0 27 May 2024
A Universal Metric of Dataset Similarity for Cross-silo Federated Learning Ahmed Elhussein Gamze Gursoy FedML OOD 39 2 0 29 Apr 2024
A Survey on Federated Analytics: Taxonomy, Enabling Techniques, Applications and Open Issues Zibo Wang Haichao Ji Yifei Zhu Dan Wang Zhu Han 51 1 0 19 Apr 2024
Advances in Differential Privacy and Differentially Private Machine Learning Saswat Das Subhankar Mishra 30 4 0 06 Apr 2024
Deciphering the Interplay between Local Differential Privacy, Average Bayesian Privacy, and Maximum Bayesian Privacy Xiaojin Zhang Yulin Fei Wei Chen 39 1 0 25 Mar 2024
Programming Frameworks for Differential Privacy Marco Gaboardi Michael Hay Salil P. Vadhan 38 1 0 17 Mar 2024
Private Count Release: A Simple and Scalable Approach for Private Data Analytics Ryan Rogers 43 0 0 08 Mar 2024
Differentially Private Representation Learning via Image Captioning Tom Sander Yaodong Yu Maziar Sanjabi Alain Durmus Yi Ma Kamalika Chaudhuri Chuan Guo 71 3 0 04 Mar 2024
State-of-the-Art Approaches to Enhancing Privacy Preservation of Machine Learning Datasets: A Survey Chaoyu Zhang Shaoyu Li AILaw 52 3 0 25 Feb 2024
Private Gradient Descent for Linear Regression: Tighter Error Bounds and Instance-Specific Uncertainty Estimation Gavin Brown Krishnamurthy Dvijotham Georgina Evans Daogao Liu Adam D. Smith Abhradeep Thakurta 42 3 0 21 Feb 2024
Implicit Bias in Noisy-SGD: With Applications to Differentially Private Training Tom Sander Maxime Sylvestre Alain Durmus 31 1 0 13 Feb 2024
Cross-silo Federated Learning with Record-level Personalized Differential Privacy Junxu Liu Jian Lou Li Xiong Jinfei Liu Xiaofeng Meng 34 6 0 29 Jan 2024
General Inferential Limits Under Differential and Pufferfish Privacy J. Bailie Ruobin Gong 35 1 0 27 Jan 2024
Wasserstein Differential Privacy Chengyi Yang Jiayin Qi Aimin Zhou 14 2 0 23 Jan 2024
Private Fine-tuning of Large Language Models with Zeroth-order Optimization Xinyu Tang Ashwinee Panda Milad Nasr Saeed Mahloujifar Prateek Mittal 47 18 0 09 Jan 2024
Conciliating Privacy and Utility in Data Releases via Individual Differential Privacy and Microaggregation Jordi Soria-Comas David Sánchez J. Domingo-Ferrer Sergio Martínez Luis Del Vasto-Terrientes 19 0 0 21 Dec 2023
Enhancing Trade-offs in Privacy, Utility, and Computational Efficiency through MUltistage Sampling Technique (MUST) Xingyuan Zhao Fang Liu 30 0 0 20 Dec 2023
Unified Enhancement of Privacy Bounds for Mixture Mechanisms via $f$ -Differential Privacy Chendi Wang Buxin Su Jiayuan Ye Reza Shokri Weijie J. Su FedML 18 10 0 30 Oct 2023
Flow-based Distributionally Robust Optimization Chen Xu Jonghyeok Lee Xiuyuan Cheng Yao Xie OOD 36 4 0 30 Oct 2023
Mean Estimation Under Heterogeneous Privacy Demands Syomantak Chaudhuri Konstantin Miagkov T. Courtade 14 1 0 19 Oct 2023
MCMC for Bayesian nonparametric mixture modeling under differential privacy Mario Beraha Stefano Favaro Vinayak Rao 41 1 0 15 Oct 2023
Using Participants' Utility Functions to Compare Versions of Differential Privacy Nitin Kohli Michael Carl Tschantz 23 0 0 10 Oct 2023
Online Sensitivity Optimization in Differentially Private Learning Filippo Galli C. Palamidessi Tommaso Cucinotta 22 1 0 02 Oct 2023