:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Flynn, Donald, Granziol, Diego
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Cryptography and Security Statistics Theory
Online Access:	https://arxiv.org/abs/2505.15175
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

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

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

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

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

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

DP-SPRT: Differentially Private Sequential Probability Ratio Tests
by: Michel, Thomas, et al.
Published: (2025)

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

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)

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

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

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

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

Privacy of SGD under Gaussian or Heavy-Tailed Noise: Guarantees without Gradient Clipping
by: Şimşekli, Umut, et al.
Published: (2024)

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

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

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

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

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

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

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

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

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

Bayesian Adversarial Privacy
by: Bell, Cameron, et al.
Published: (2026)

Nonparametric extensions of randomized response for private confidence sets
by: Waudby-Smith, Ian, et al.
Published: (2022)

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

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

Uncertainty quantification by block bootstrap for differentially private stochastic gradient descent
by: Dette, Holger, et al.
Published: (2024)

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

Infinitely divisible privacy and beyond I: resolution of the $s^2=2k$ conjecture
by: Pandey, Aaradhya, et al.
Published: (2025)

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

Optimal Detection for Language Watermarks with Pseudorandom Collision
by: Cai, T. Tony, et al.
Published: (2025)

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

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

Cryptographic Hardness of Score Estimation
by: Song, Min Jae
Published: (2024)

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

A Statistical Hypothesis Testing Framework for Data Misappropriation Detection in Large Language Models
by: Cai, Yinpeng, et al.
Published: (2025)

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

A Bias-Accuracy-Privacy Trilemma for Statistical Estimation
by: Kamath, Gautam, et al.
Published: (2023)

Six Levels of Privacy: A Framework for Financial Synthetic Data
by: Balch, Tucker, et al.
Published: (2024)