Concentrated Differential Privacy: Simplifications, Extensions, and Lower Bounds

6 May 2016

Papers citing "Concentrated Differential Privacy: Simplifications, Extensions, and Lower Bounds"

50 / 206 papers shown

Title
On the connection between the ABS perturbation methodology and differential privacy Parastoo Sadeghi Chien-Hung Chien 31 2 0 24 Mar 2023
Optimal and Private Learning from Human Response Data Duc Nguyen A. Zhang 25 1 0 10 Mar 2023
Considerations on the Theory of Training Models with Differential Privacy Marten van Dijk Phuong Ha Nguyen FedML 31 2 0 08 Mar 2023
How to DP-fy ML: A Practical Guide to Machine Learning with Differential Privacy Natalia Ponomareva Hussein Hazimeh Alexey Kurakin Zheng Xu Carson E. Denison H. B. McMahan Sergei Vassilvitskii Steve Chien Abhradeep Thakurta 99 167 0 01 Mar 2023
Private (Stochastic) Non-Convex Optimization Revisited: Second-Order Stationary Points and Excess Risks Arun Ganesh Daogao Liu Sewoong Oh Abhradeep Thakurta ODL 27 12 0 20 Feb 2023
Differentially Private Optimization for Smooth Nonconvex ERM Changyu Gao Stephen J. Wright 16 6 0 09 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 Distributed Bayesian Linear Regression with MCMC Barics Alparslan S. Yıldırım cS. .Ilker Birbil FedML 25 1 0 31 Jan 2023
The Fair Value of Data Under Heterogeneous Privacy Constraints in Federated Learning Justin Singh Kang Ramtin Pedarsani Kannan Ramchandran FedML 29 5 0 30 Jan 2023
Differentially Private Natural Language Models: Recent Advances and Future Directions Lijie Hu Ivan Habernal Lei Shen Di Wang AAML 35 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 24 5 0 19 Jan 2023
DP-SIPS: A simpler, more scalable mechanism for differentially private partition selection Marika Swanberg Damien Desfontaines Samuel Haney 36 6 0 05 Jan 2023
Differentially Private Decentralized Optimization with Relay Communication Luqing Wang Luyao Guo Shaofu Yang Xinli Shi 28 0 0 21 Dec 2022
Grafting Laplace and Gaussian distributions: A new noise mechanism for differential privacy Gokularam Muthukrishnan Sheetal Kalyani 36 12 0 19 Dec 2022
Answering Private Linear Queries Adaptively using the Common Mechanism Yingtai Xiao Guanhong Wang Danfeng Zhang Daniel Kifer 65 7 0 30 Nov 2022
Differentially Private Enhanced Permissioned Blockchain for Private Data Sharing in Industrial IoT Muhammad Islam M. H. Rehmani Jinjun Chen 28 8 0 30 Nov 2022
Differentially Private Image Classification from Features Harsh Mehta Walid Krichene Abhradeep Thakurta Alexey Kurakin Ashok Cutkosky 58 7 0 24 Nov 2022
Lemmas of Differential Privacy Yiyang Huang C. Canonne 37 1 0 21 Nov 2022
Learning to Generate Image Embeddings with User-level Differential Privacy Zheng Xu Maxwell D. Collins Yuxiao Wang Liviu Panait Sewoong Oh S. Augenstein Ting Liu Florian Schroff H. B. McMahan FedML 30 29 0 20 Nov 2022
A Survey on Differential Privacy with Machine Learning and Future Outlook Samah Baraheem Z. Yao SyDa 21 1 0 19 Nov 2022
A Robust Dynamic Average Consensus Algorithm that Ensures both Differential Privacy and Accurate Convergence Yongqiang Wang 28 4 0 14 Nov 2022
Multi-Epoch Matrix Factorization Mechanisms for Private Machine Learning Christopher A. Choquette-Choo H. B. McMahan Keith Rush Abhradeep Thakurta 39 42 0 12 Nov 2022
Lessons Learned: Surveying the Practicality of Differential Privacy in the Industry Gonzalo Munilla Garrido Xiaoyuan Liu Florian Matthes D. Song 28 24 0 07 Nov 2022
Ensure Differential Privacy and Convergence Accuracy in Consensus Tracking and Aggregative Games with Coupling Constraints Yongqiang Wang 30 3 0 28 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
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 69 50 0 02 Oct 2022
Algorithms with More Granular Differential Privacy Guarantees Badih Ghazi Ravi Kumar Pasin Manurangsi Thomas Steinke 67 6 0 08 Sep 2022
Bayesian and Frequentist Semantics for Common Variations of Differential Privacy: Applications to the 2020 Census Daniel Kifer John M. Abowd Robert Ashmead Ryan Cumings-Menon Philip Leclerc Ashwin Machanavajjhala William Sexton Pavel I Zhuravlev 54 26 0 07 Sep 2022
Differential Privacy on Dynamic Data Yuan Qiu K. Yi 29 0 0 03 Sep 2022
On Differential Privacy for Federated Learning in Wireless Systems with Multiple Base Stations Nima Tavangaran Mingzhe Chen Zhaohui Yang J. M. B. D. Silva H. Vincent Poor FedML 28 4 0 25 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
Faster Privacy Accounting via Evolving Discretization Badih Ghazi Pritish Kamath Ravi Kumar Pasin Manurangsi 65 14 0 10 Jul 2022
Connect the Dots: Tighter Discrete Approximations of Privacy Loss Distributions Vadym Doroshenko Badih Ghazi Pritish Kamath Ravi Kumar Pasin Manurangsi 26 40 0 10 Jul 2022
Hypothesis Testing for Differentially Private Linear Regression Daniel Alabi Salil P. Vadhan FedML 40 11 0 29 Jun 2022
Beyond Uniform Lipschitz Condition in Differentially Private Optimization Rudrajit Das Satyen Kale Zheng Xu Tong Zhang Sujay Sanghavi 26 17 0 21 Jun 2022
On Privacy and Personalization in Cross-Silo Federated Learning Ziyu Liu Shengyuan Hu Zhiwei Steven Wu Virginia Smith FedML 22 53 0 16 Jun 2022
Distributed Differential Privacy in Multi-Armed Bandits Sayak Ray Chowdhury Xingyu Zhou 30 12 0 12 Jun 2022
Analytical Composition of Differential Privacy via the Edgeworth Accountant Hua Wang Sheng-yang Gao Huanyu Zhang Milan Shen Weijie J. Su FedML 36 21 0 09 Jun 2022
Confidentiality Protection in the 2020 US Census of Population and Housing John M. Abowd Michael B. Hawes 19 26 0 07 Jun 2022
Offline Reinforcement Learning with Differential Privacy Dan Qiao Yu-Xiang Wang OffRL 39 23 0 02 Jun 2022
Data Augmentation MCMC for Bayesian Inference from Privatized Data Nianqiao P. Ju Jordan Awan Ruobin Gong Vinayak A. Rao 32 23 0 01 Jun 2022
Edge Learning for B5G Networks with Distributed Signal Processing: Semantic Communication, Edge Computing, and Wireless Sensing Wei Xu Zhaohui Yang Derrick Wing Kwan Ng Marco Levorato Yonina C. Eldar Mérouane Debbah 28 398 0 01 Jun 2022
Improved Utility Analysis of Private CountSketch Rasmus Pagh M. Thorup FedML 34 20 0 17 May 2022
$Privacy accounting $\varepsilon$conomics: Improving differential privacy composition via a posteriori bounds$ Privacy accounting $\varepsilon$ conomics: Improving differential privacy composition via a posteriori bounds Valentin Hartmann Vincent Bindschaedler Alexander Bentkamp Robert West 24 1 0 06 May 2022
Statistical Data Privacy: A Song of Privacy and Utility Aleksandra B. Slavkovic Jeremy Seeman 23 26 0 06 May 2022
A Differentially Private Framework for Deep Learning with Convexified Loss Functions Zhigang Lu Hassan Jameel Asghar M. Kâafar Darren Webb Peter Dickinson 77 15 0 03 Apr 2022
Geographic Spines in the 2020 Census Disclosure Avoidance System Ryan Cumings-Menon John M. Abowd Robert Ashmead Daniel Kifer Philip Leclerc Jeffrey C. Ocker M. Ratcliffe Pavel I Zhuravlev CML 13 86 0 30 Mar 2022
Adaptive Private-K-Selection with Adaptive K and Application to Multi-label PATE Yuqing Zhu Yu-Xiang Wang 37 18 0 30 Mar 2022