High-Probability Bounds For Heterogeneous Local Differential Privacy
Fuente:
arXiv
Saved in:
| Main Authors: | Aliakbarpour, Maryam, Fallah, Alireza, Roy, Swaha, Stevens, Ria |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Nearly-Linear Time Private Hypothesis Selection with the Optimal Approximation Factor
by: Aliakbarpour, Maryam, et al.
Published: (2025)
by: Aliakbarpour, Maryam, et al.
Published: (2025)
Optimal Prediction-Augmented Algorithms for Testing Independence of Distributions
by: Aliakbarpour, Maryam, et al.
Published: (2026)
by: Aliakbarpour, Maryam, et al.
Published: (2026)
Better Private Distribution Testing by Leveraging Unverified Auxiliary Data
by: Aliakbarpour, Maryam, et al.
Published: (2025)
by: Aliakbarpour, Maryam, et al.
Published: (2025)
Prediction with Expert Advice under Local Differential Privacy
by: Jacobsen, Ben, et al.
Published: (2025)
by: Jacobsen, Ben, et al.
Published: (2025)
The Discrete Gaussian for Differential Privacy
by: Canonne, Clément L., et al.
Published: (2020)
by: Canonne, Clément L., et al.
Published: (2020)
On the Price of Differential Privacy for Hierarchical Clustering
by: Deng, Chengyuan, et al.
Published: (2025)
by: Deng, Chengyuan, et al.
Published: (2025)
Local Pan-Privacy for Federated Analytics
by: Feldman, Vitaly, et al.
Published: (2025)
by: Feldman, Vitaly, et al.
Published: (2025)
Edgeworth Accountant: An Analytical Approach to Differential Privacy Composition
by: Wang, Hua, et al.
Published: (2022)
by: Wang, Hua, et al.
Published: (2022)
Fast John Ellipsoid Computation with Differential Privacy Optimization
by: Li, Xiaoyu, et al.
Published: (2024)
by: Li, Xiaoyu, et al.
Published: (2024)
Individual Privacy Accounting for Differentially Private Stochastic Gradient Descent
by: Yu, Da, et al.
Published: (2022)
by: Yu, Da, et al.
Published: (2022)
Differentially Private Bootstrap: New Privacy Analysis and Inference Strategies
by: Wang, Zhanyu, et al.
Published: (2022)
by: Wang, Zhanyu, et al.
Published: (2022)
Almost Tight Error Bounds on Differentially Private Continual Counting
by: Henzinger, Monika, et al.
Published: (2022)
by: Henzinger, Monika, et al.
Published: (2022)
Improved Regret in Stochastic Decision-Theoretic Online Learning under Differential Privacy
by: Wu, Ruihan, et al.
Published: (2025)
by: Wu, Ruihan, et al.
Published: (2025)
Analysis of Shuffling Beyond Pure Local Differential Privacy
by: Takagi, Shun, et al.
Published: (2026)
by: Takagi, Shun, et al.
Published: (2026)
Learning from End User Data with Shuffled Differential Privacy over Kernel Densities
by: Wagner, Tal
Published: (2025)
by: Wagner, Tal
Published: (2025)
Normalized Square Root: Sharper Matrix Factorization Bounds for Differentially Private Continual Counting
by: Henzinger, Monika, et al.
Published: (2025)
by: Henzinger, Monika, et al.
Published: (2025)
Smooth Lower Bounds for Differentially Private Algorithms via Padding-and-Permuting Fingerprinting Codes
by: Peter, Naty, et al.
Published: (2023)
by: Peter, Naty, et al.
Published: (2023)
Quantum Local Differential Privacy and Quantum Statistical Query Model
by: Angrisani, Armando, et al.
Published: (2022)
by: Angrisani, Armando, et al.
Published: (2022)
Local Node Differential Privacy
by: Raskhodnikova, Sofya, et al.
Published: (2026)
by: Raskhodnikova, Sofya, et al.
Published: (2026)
Triangle Counting with Local Edge Differential Privacy
by: Eden, Talya, et al.
Published: (2023)
by: Eden, Talya, et al.
Published: (2023)
On Computing Pairwise Statistics with Local Differential Privacy
by: Ghazi, Badih, et al.
Published: (2024)
by: Ghazi, Badih, et al.
Published: (2024)
Private Selection with Heterogeneous Sensitivities
by: Antonova, Daniela, et al.
Published: (2025)
by: Antonova, Daniela, et al.
Published: (2025)
Epsilon*: Privacy Metric for Machine Learning Models
by: Negoescu, Diana M., et al.
Published: (2023)
by: Negoescu, Diana M., et al.
Published: (2023)
Privacy-Computation trade-offs in Private Repetition and Metaselection
by: Talwar, Kunal
Published: (2024)
by: Talwar, Kunal
Published: (2024)
Privacy Amplification Persists under Unlimited Synthetic Data Release
by: Pierquin, Clément, et al.
Published: (2026)
by: Pierquin, Clément, et al.
Published: (2026)
Avoiding Pitfalls for Privacy Accounting of Subsampled Mechanisms under Composition
by: Lebeda, Christian Janos, et al.
Published: (2024)
by: Lebeda, Christian Janos, et al.
Published: (2024)
Differentially Private Clustering in Data Streams
by: Epasto, Alessandro, et al.
Published: (2023)
by: Epasto, Alessandro, et al.
Published: (2023)
Cycle Counting under Local Differential Privacy for Degeneracy-bounded Graphs
by: Hillebrand, Quentin, et al.
Published: (2024)
by: Hillebrand, Quentin, et al.
Published: (2024)
Private Mean Estimation with Person-Level Differential Privacy
by: Agarwal, Sushant, et al.
Published: (2024)
by: Agarwal, Sushant, et al.
Published: (2024)
Continual Release of Densest Subgraphs: Privacy Amplification & Sublinear Space via Subsampling
by: Zhou, Felix
Published: (2025)
by: Zhou, Felix
Published: (2025)
Differentially Private Multi-Sampling from Distributions
by: Cheu, Albert, et al.
Published: (2024)
by: Cheu, Albert, et al.
Published: (2024)
Optimal Bounds for Private Minimum Spanning Trees via Input Perturbation
by: Pagh, Rasmus, et al.
Published: (2024)
by: Pagh, Rasmus, et al.
Published: (2024)
Tighter Bounds for Local Differentially Private Core Decomposition and Densest Subgraph
by: Henzinger, Monika, et al.
Published: (2024)
by: Henzinger, Monika, et al.
Published: (2024)
Differentially Private Learning Beyond the Classical Dimensionality Regime
by: Dwork, Cynthia, et al.
Published: (2024)
by: Dwork, Cynthia, et al.
Published: (2024)
Efficient and Near-Optimal Noise Generation for Streaming Differential Privacy
by: Dvijotham, Krishnamurthy, et al.
Published: (2024)
by: Dvijotham, Krishnamurthy, et al.
Published: (2024)
A Differentially Private Clustering Algorithm for Well-Clustered Graphs
by: He, Weiqiang, et al.
Published: (2024)
by: He, Weiqiang, et al.
Published: (2024)
On Differentially Private Subspace Estimation in a Distribution-Free Setting
by: Tsfadia, Eliad
Published: (2024)
by: Tsfadia, Eliad
Published: (2024)
Scaling up the Banded Matrix Factorization Mechanism for Differentially Private ML
by: McKenna, Ryan
Published: (2024)
by: McKenna, Ryan
Published: (2024)
Lower Bounds for Private Estimation of Gaussian Covariance Matrices under All Reasonable Parameter Regimes
by: Portella, Victor S., et al.
Published: (2024)
by: Portella, Victor S., et al.
Published: (2024)
Differential Privacy on Trust Graphs
by: Ghazi, Badih, et al.
Published: (2024)
by: Ghazi, Badih, et al.
Published: (2024)
Similar Items
-
Nearly-Linear Time Private Hypothesis Selection with the Optimal Approximation Factor
by: Aliakbarpour, Maryam, et al.
Published: (2025) -
Optimal Prediction-Augmented Algorithms for Testing Independence of Distributions
by: Aliakbarpour, Maryam, et al.
Published: (2026) -
Better Private Distribution Testing by Leveraging Unverified Auxiliary Data
by: Aliakbarpour, Maryam, et al.
Published: (2025) -
Prediction with Expert Advice under Local Differential Privacy
by: Jacobsen, Ben, et al.
Published: (2025) -
The Discrete Gaussian for Differential Privacy
by: Canonne, Clément L., et al.
Published: (2020)