Cover Image

DP-SPRT: Differentially Private Sequential Probability Ratio Tests

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Michel, Thomas, Basu, Debabrota, Kaufmann, Emilie
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Cryptography and Security Statistics Theory
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Sequential Membership Inference Attacks
by: Michel, Thomas, et al.
Published: (2026)

Differentially Private Best-Arm Identification
by: Azize, Achraf, et al.
Published: (2024)

Concentrated Differential Privacy for Bandits
by: Azize, Achraf, et al.
Published: (2023)

Some Targets Are Harder to Identify than Others: Quantifying the Target-dependent Membership Leakage
by: Azize, Achraf, et al.
Published: (2024)

Optimal Regret of Bernoulli Bandits under Global Differential Privacy
by: Azize, Achraf, et al.
Published: (2025)

Differentially Private Permutation Tests: Applications to Kernel Methods
by: Kim, Ilmun, et al.
Published: (2023)

Differentially Private Manifold Denoising
by: Wu, Jiaqi, et al.
Published: (2026)

On Differentially Private U Statistics
by: Chaudhuri, Kamalika, et al.
Published: (2024)

Differentially Private Synthetic High-dimensional Tabular Stream
by: Kumar, Girish, et al.
Published: (2024)

Differentially Private Sliced Inverse Regression: Minimax Optimality and Algorithm
by: Xia, Xintao, et al.
Published: (2024)

Contraction of Locally Differentially Private Mechanisms
by: Asoodeh, Shahab, et al.
Published: (2022)

Differentially Private Inference for Longitudinal Linear Regression
by: Sopa, Getoar, et al.
Published: (2026)

An Iterative Algorithm for Differentially Private $k$-PCA with Adaptive Noise
by: Düngler, Johanna, et al.
Published: (2025)

Differentially Private Federated Learning: Servers Trustworthiness, Estimation, and Statistical Inference
by: Zhang, Zhe, et al.
Published: (2024)

A Statistical Viewpoint on Differential Privacy: Hypothesis Testing, Representation and Blackwell's Theorem
by: Su, Weijie J.
Published: (2024)

Score Attack: A Lower Bound Technique for Optimal Differentially Private Learning
by: Cai, T. Tony, et al.
Published: (2023)

Optimal Rates for Differentially Private Hypothesis Testing with E-values
by: Jacobsen, Ben, et al.
Published: (2026)

On Privately Estimating a Single Parameter
by: Asi, Hilal, et al.
Published: (2025)

Optimal Survey Design for Private Mean Estimation
by: Chen, Yu-Wei, et al.
Published: (2025)

Differentially Private Synthetic Data with Private Density Estimation
by: Bojkovic, Nikolija, et al.
Published: (2024)

Testing Credibility of Public and Private Surveys through the Lens of Regression
by: Basu, Debabrota, et al.
Published: (2024)

Differentially Private Joint Independence Test
by: Liu, Xingwei, et al.
Published: (2025)

Differentially Private Low-dimensional Synthetic Data from High-dimensional Datasets
by: He, Yiyun, et al.
Published: (2023)

Better and Simpler Lower Bounds for Differentially Private Statistical Estimation
by: Narayanan, Shyam
Published: (2023)

Federated Transfer Learning with Differential Privacy
by: Li, Mengchu, et al.
Published: (2024)

DP-LDMs: Differentially Private Latent Diffusion Models
by: Liu, Michael F., et al.
Published: (2023)

DP-KAN: Differentially Private Kolmogorov-Arnold Networks
by: Kalinin, Nikita P., et al.
Published: (2024)

Beyond Covariance Matrix: The Statistical Complexity of Private Linear Regression
by: Chen, Fan, et al.
Published: (2025)

DP-TLDM: Differentially Private Tabular Latent Diffusion Model
by: Zhu, Chaoyi, et al.
Published: (2024)

Mitigating Privacy-Utility Trade-off in Decentralized Federated Learning via $f$-Differential Privacy
by: Li, Xiang, et al.
Published: (2025)

Shifted Interpolation for Differential Privacy
by: Bok, Jinho, et al.
Published: (2024)

Attack-Aware Noise Calibration for Differential Privacy
by: Kulynych, Bogdan, et al.
Published: (2024)

Sequential Change Detection for Multiple Data Streams with Differential Privacy
by: Zhang, Lixing, et al.
Published: (2026)

Beyond the Calibration Point: Mechanism Comparison in Differential Privacy
by: Kaissis, Georgios, et al.
Published: (2024)

Instance-Optimal Private Density Estimation in the Wasserstein Distance
by: Feldman, Vitaly, et al.
Published: (2024)

Training Set Reconstruction from Differentially Private Forests: How Effective is DP?
by: Gorgé, Alice, et al.
Published: (2025)

A Linear Approach to Data Poisoning
by: Flynn, Donald, et al.
Published: (2025)

On Rate-Optimal Partitioning Classification from Observable and from Privatised Data
by: Csáji, Balázs Csanád, et al.
Published: (2023)

Generalization Bound and New Algorithm for Clean-Label Backdoor Attack
by: Yu, Lijia, et al.
Published: (2024)

Optimal Classification-based Anomaly Detection with Neural Networks: Theory and Practice
by: Zhou, Tian-Yi, et al.
Published: (2024)