Fast John Ellipsoid Computation with Differential Privacy Optimization
Fuente:
arXiv
Saved in:
| Main Authors: | Li, Xiaoyu, Liang, Yingyu, Shi, Zhenmei, Song, Zhao, Yu, Junwei |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
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)
Individual Privacy Accounting for Differentially Private Stochastic Gradient Descent
by: Yu, Da, et al.
Published: (2022)
by: Yu, Da, 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)
Edgeworth Accountant: An Analytical Approach to Differential Privacy Composition
by: Wang, Hua, et al.
Published: (2022)
by: Wang, Hua, et al.
Published: (2022)
Prediction with Expert Advice under Local Differential Privacy
by: Jacobsen, Ben, et al.
Published: (2025)
by: Jacobsen, Ben, et al.
Published: (2025)
High-Probability Bounds For Heterogeneous Local Differential Privacy
by: Aliakbarpour, Maryam, et al.
Published: (2025)
by: Aliakbarpour, Maryam, et al.
Published: (2025)
Differentially Private Bootstrap: New Privacy Analysis and Inference Strategies
by: Wang, Zhanyu, et al.
Published: (2022)
by: Wang, Zhanyu, et al.
Published: (2022)
Differential Private Stochastic Optimization with Heavy-tailed Data: Towards Optimal Rates
by: Zhao, Puning, et al.
Published: (2024)
by: Zhao, Puning, et al.
Published: (2024)
Privacy-Computation trade-offs in Private Repetition and Metaselection
by: Talwar, Kunal
Published: (2024)
by: Talwar, Kunal
Published: (2024)
Differential Privacy for Euclidean Jordan Algebra with Applications to Private Symmetric Cone Programming
by: Song, Zhao, et al.
Published: (2025)
by: Song, Zhao, et al.
Published: (2025)
Learning from End User Data with Shuffled Differential Privacy over Kernel Densities
by: Wagner, Tal
Published: (2025)
by: Wagner, Tal
Published: (2025)
On the Price of Privacy for Language Identification and Generation
by: Li, Xiaoyu, et al.
Published: (2026)
by: Li, Xiaoyu, et al.
Published: (2026)
On Computing Pairwise Statistics with Local Differential Privacy
by: Ghazi, Badih, et al.
Published: (2024)
by: Ghazi, Badih, et al.
Published: (2024)
Local Pan-Privacy for Federated Analytics
by: Feldman, Vitaly, et al.
Published: (2025)
by: Feldman, Vitaly, 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)
Quantum Speedups for Approximating the John Ellipsoid
by: Li, Xiaoyu, et al.
Published: (2024)
by: Li, Xiaoyu, et al.
Published: (2024)
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)
Privacy Amplification Persists under Unlimited Synthetic Data Release
by: Pierquin, Clément, et al.
Published: (2026)
by: Pierquin, Clément, et al.
Published: (2026)
Differentially Private Clustering in Data Streams
by: Epasto, Alessandro, et al.
Published: (2023)
by: Epasto, Alessandro, et al.
Published: (2023)
Private Mean Estimation with Person-Level Differential Privacy
by: Agarwal, Sushant, et al.
Published: (2024)
by: Agarwal, Sushant, et al.
Published: (2024)
Analysis of Shuffling Beyond Pure Local Differential Privacy
by: Takagi, Shun, et al.
Published: (2026)
by: Takagi, Shun, et al.
Published: (2026)
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)
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)
Quantum Local Differential Privacy and Quantum Statistical Query Model
by: Angrisani, Armando, et al.
Published: (2022)
by: Angrisani, Armando, et al.
Published: (2022)
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)
Almost Tight Error Bounds on Differentially Private Continual Counting
by: Henzinger, Monika, et al.
Published: (2022)
by: Henzinger, Monika, et al.
Published: (2022)
Scaling up the Banded Matrix Factorization Mechanism for Differentially Private ML
by: McKenna, Ryan
Published: (2024)
by: McKenna, Ryan
Published: (2024)
Differential Privacy on Trust Graphs
by: Ghazi, Badih, et al.
Published: (2024)
by: Ghazi, Badih, et al.
Published: (2024)
Making Old Things New: A Unified Algorithm for Differentially Private Clustering
by: la Tour, Max Dupré, et al.
Published: (2024)
by: la Tour, Max Dupré, et al.
Published: (2024)
A Polynomial Time, Pure Differentially Private Estimator for Binary Product Distributions
by: Singhal, Vikrant
Published: (2023)
by: Singhal, Vikrant
Published: (2023)
Efficiently Computing Similarities to Private Datasets
by: Backurs, Arturs, et al.
Published: (2024)
by: Backurs, Arturs, et al.
Published: (2024)
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)
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)
On Differentially Private String Distances
by: Hu, Jerry Yao-Chieh, et al.
Published: (2024)
by: Hu, Jerry Yao-Chieh, et al.
Published: (2024)
Differential Privacy with Multiple Selections
by: Goel, Ashish, et al.
Published: (2024)
by: Goel, Ashish, et al.
Published: (2024)
Local Node Differential Privacy
by: Raskhodnikova, Sofya, et al.
Published: (2026)
by: Raskhodnikova, Sofya, et al.
Published: (2026)
Similar Items
-
The Discrete Gaussian for Differential Privacy
by: Canonne, Clément L., et al.
Published: (2020) -
On the Price of Differential Privacy for Hierarchical Clustering
by: Deng, Chengyuan, et al.
Published: (2025) -
Individual Privacy Accounting for Differentially Private Stochastic Gradient Descent
by: Yu, Da, et al.
Published: (2022) -
Improved Regret in Stochastic Decision-Theoretic Online Learning under Differential Privacy
by: Wu, Ruihan, et al.
Published: (2025) -
Edgeworth Accountant: An Analytical Approach to Differential Privacy Composition
by: Wang, Hua, et al.
Published: (2022)