Learning from End User Data with Shuffled Differential Privacy over Kernel Densities
Fuente:
arXiv
Guardado en:
| Autor principal: | Wagner, Tal |
|---|---|
| Formato: | Preprint |
| Publicado: |
2025
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
Analysis of Shuffling Beyond Pure Local Differential Privacy
por: Takagi, Shun, et al.
Publicado: (2026)
por: Takagi, Shun, et al.
Publicado: (2026)
The Discrete Gaussian for Differential Privacy
por: Canonne, Clément L., et al.
Publicado: (2020)
por: Canonne, Clément L., et al.
Publicado: (2020)
On the Price of Differential Privacy for Hierarchical Clustering
por: Deng, Chengyuan, et al.
Publicado: (2025)
por: Deng, Chengyuan, et al.
Publicado: (2025)
Scalable DP-SGD: Shuffling vs. Poisson Subsampling
por: Chua, Lynn, et al.
Publicado: (2024)
por: Chua, Lynn, et al.
Publicado: (2024)
Almost Instance-optimal Clipping for Summation Problems in the Shuffle Model of Differential Privacy
por: Dong, Wei, et al.
Publicado: (2024)
por: Dong, Wei, et al.
Publicado: (2024)
Improved Regret in Stochastic Decision-Theoretic Online Learning under Differential Privacy
por: Wu, Ruihan, et al.
Publicado: (2025)
por: Wu, Ruihan, et al.
Publicado: (2025)
Prediction with Expert Advice under Local Differential Privacy
por: Jacobsen, Ben, et al.
Publicado: (2025)
por: Jacobsen, Ben, et al.
Publicado: (2025)
High-Probability Bounds For Heterogeneous Local Differential Privacy
por: Aliakbarpour, Maryam, et al.
Publicado: (2025)
por: Aliakbarpour, Maryam, et al.
Publicado: (2025)
Edgeworth Accountant: An Analytical Approach to Differential Privacy Composition
por: Wang, Hua, et al.
Publicado: (2022)
por: Wang, Hua, et al.
Publicado: (2022)
Fast John Ellipsoid Computation with Differential Privacy Optimization
por: Li, Xiaoyu, et al.
Publicado: (2024)
por: Li, Xiaoyu, et al.
Publicado: (2024)
Individual Privacy Accounting for Differentially Private Stochastic Gradient Descent
por: Yu, Da, et al.
Publicado: (2022)
por: Yu, Da, et al.
Publicado: (2022)
Differentially Private Bootstrap: New Privacy Analysis and Inference Strategies
por: Wang, Zhanyu, et al.
Publicado: (2022)
por: Wang, Zhanyu, et al.
Publicado: (2022)
Differentially Private Clustering in Data Streams
por: Epasto, Alessandro, et al.
Publicado: (2023)
por: Epasto, Alessandro, et al.
Publicado: (2023)
Privacy Amplification Persists under Unlimited Synthetic Data Release
por: Pierquin, Clément, et al.
Publicado: (2026)
por: Pierquin, Clément, et al.
Publicado: (2026)
Epsilon*: Privacy Metric for Machine Learning Models
por: Negoescu, Diana M., et al.
Publicado: (2023)
por: Negoescu, Diana M., et al.
Publicado: (2023)
DPSW-Sketch: A Differentially Private Sketch Framework for Frequency Estimation over Sliding Windows (Technical Report)
por: Wang, Yiping, et al.
Publicado: (2024)
por: Wang, Yiping, et al.
Publicado: (2024)
Differentially Private Learning Beyond the Classical Dimensionality Regime
por: Dwork, Cynthia, et al.
Publicado: (2024)
por: Dwork, Cynthia, et al.
Publicado: (2024)
Differential Private Stochastic Optimization with Heavy-tailed Data: Towards Optimal Rates
por: Zhao, Puning, et al.
Publicado: (2024)
por: Zhao, Puning, et al.
Publicado: (2024)
Local Pan-Privacy for Federated Analytics
por: Feldman, Vitaly, et al.
Publicado: (2025)
por: Feldman, Vitaly, et al.
Publicado: (2025)
Differentially Private Multi-Sampling from Distributions
por: Cheu, Albert, et al.
Publicado: (2024)
por: Cheu, Albert, et al.
Publicado: (2024)
Privacy-Computation trade-offs in Private Repetition and Metaselection
por: Talwar, Kunal
Publicado: (2024)
por: Talwar, Kunal
Publicado: (2024)
Avoiding Pitfalls for Privacy Accounting of Subsampled Mechanisms under Composition
por: Lebeda, Christian Janos, et al.
Publicado: (2024)
por: Lebeda, Christian Janos, et al.
Publicado: (2024)
Private Mean Estimation with Person-Level Differential Privacy
por: Agarwal, Sushant, et al.
Publicado: (2024)
por: Agarwal, Sushant, et al.
Publicado: (2024)
Continual Release of Densest Subgraphs: Privacy Amplification & Sublinear Space via Subsampling
por: Zhou, Felix
Publicado: (2025)
por: Zhou, Felix
Publicado: (2025)
Linear-Time User-Level DP-SCO via Robust Statistics
por: Ghazi, Badih, et al.
Publicado: (2025)
por: Ghazi, Badih, et al.
Publicado: (2025)
Quantum Local Differential Privacy and Quantum Statistical Query Model
por: Angrisani, Armando, et al.
Publicado: (2022)
por: Angrisani, Armando, et al.
Publicado: (2022)
Efficient and Near-Optimal Noise Generation for Streaming Differential Privacy
por: Dvijotham, Krishnamurthy, et al.
Publicado: (2024)
por: Dvijotham, Krishnamurthy, et al.
Publicado: (2024)
A Differentially Private Clustering Algorithm for Well-Clustered Graphs
por: He, Weiqiang, et al.
Publicado: (2024)
por: He, Weiqiang, et al.
Publicado: (2024)
Almost Tight Error Bounds on Differentially Private Continual Counting
por: Henzinger, Monika, et al.
Publicado: (2022)
por: Henzinger, Monika, et al.
Publicado: (2022)
On Differentially Private Subspace Estimation in a Distribution-Free Setting
por: Tsfadia, Eliad
Publicado: (2024)
por: Tsfadia, Eliad
Publicado: (2024)
Scaling up the Banded Matrix Factorization Mechanism for Differentially Private ML
por: McKenna, Ryan
Publicado: (2024)
por: McKenna, Ryan
Publicado: (2024)
Private Vector Mean Estimation in the Shuffle Model: Optimal Rates Require Many Messages
por: Asi, Hilal, et al.
Publicado: (2024)
por: Asi, Hilal, et al.
Publicado: (2024)
Differential Privacy on Trust Graphs
por: Ghazi, Badih, et al.
Publicado: (2024)
por: Ghazi, Badih, et al.
Publicado: (2024)
Making Old Things New: A Unified Algorithm for Differentially Private Clustering
por: la Tour, Max Dupré, et al.
Publicado: (2024)
por: la Tour, Max Dupré, et al.
Publicado: (2024)
A Polynomial Time, Pure Differentially Private Estimator for Binary Product Distributions
por: Singhal, Vikrant
Publicado: (2023)
por: Singhal, Vikrant
Publicado: (2023)
Normalized Square Root: Sharper Matrix Factorization Bounds for Differentially Private Continual Counting
por: Henzinger, Monika, et al.
Publicado: (2025)
por: Henzinger, Monika, et al.
Publicado: (2025)
Smooth Lower Bounds for Differentially Private Algorithms via Padding-and-Permuting Fingerprinting Codes
por: Peter, Naty, et al.
Publicado: (2023)
por: Peter, Naty, et al.
Publicado: (2023)
Differential Privacy for Euclidean Jordan Algebra with Applications to Private Symmetric Cone Programming
por: Song, Zhao, et al.
Publicado: (2025)
por: Song, Zhao, et al.
Publicado: (2025)
Local Node Differential Privacy
por: Raskhodnikova, Sofya, et al.
Publicado: (2026)
por: Raskhodnikova, Sofya, et al.
Publicado: (2026)
Differential Privacy with Multiple Selections
por: Goel, Ashish, et al.
Publicado: (2024)
por: Goel, Ashish, et al.
Publicado: (2024)
Ejemplares similares
-
Analysis of Shuffling Beyond Pure Local Differential Privacy
por: Takagi, Shun, et al.
Publicado: (2026) -
The Discrete Gaussian for Differential Privacy
por: Canonne, Clément L., et al.
Publicado: (2020) -
On the Price of Differential Privacy for Hierarchical Clustering
por: Deng, Chengyuan, et al.
Publicado: (2025) -
Scalable DP-SGD: Shuffling vs. Poisson Subsampling
por: Chua, Lynn, et al.
Publicado: (2024) -
Almost Instance-optimal Clipping for Summation Problems in the Shuffle Model of Differential Privacy
por: Dong, Wei, et al.
Publicado: (2024)