:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Pasteris, Stephen, Savani, Rahul, Turocy, Theodore
Format:	Preprint
Published:	2026
Subjects:	Cryptography and Security Machine Learning
Online Access:	https://arxiv.org/abs/2605.05266
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Differential Privacy in Kernelized Contextual Bandits via Random Projections
by: Pavlovic, Nikola, et al.
Published: (2025)

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

A Survey on Differential Privacy for SpatioTemporal Data in Transportation Research
by: Bhadani, Rahul
Published: (2024)

Wasserstein Differential Privacy
by: Yang, Chengyi, et al.
Published: (2024)

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

Private Linear Regression with Differential Privacy and PAC Privacy
by: Yang, Hillary, et al.
Published: (2024)

Limits of Personalizing Differential Privacy Budgets
by: Cyffers, Edwige, et al.
Published: (2026)

Laplace Transform Interpretation of Differential Privacy
by: Chourasia, Rishav, et al.
Published: (2024)

Setting $\varepsilon$ is not the Issue in Differential Privacy
by: Cyffers, Edwige
Published: (2025)

Contrastive Explainable Clustering with Differential Privacy
by: Nguyen, Dung, et al.
Published: (2024)

Revisiting Hyperparameter Tuning with Differential Privacy
by: Ding, Youlong, et al.
Published: (2022)

Local Differential Privacy is Not Enough: A Sample Reconstruction Attack against Federated Learning with Local Differential Privacy
by: You, Zhichao, et al.
Published: (2025)

Optimal Fairness under Local Differential Privacy
by: Ghoukasian, Hrad, et al.
Published: (2025)

Auditing $f$-Differential Privacy in One Run
by: Mahloujifar, Saeed, et al.
Published: (2024)

A Privacy-Preserving Framework for Advertising Personalization Incorporating Federated Learning and Differential Privacy
by: Li, Xiang, et al.
Published: (2025)

Sequentially Auditing Differential Privacy
by: González, Tomás, et al.
Published: (2025)

Deep Learning under Fractional-Order Differential Privacy
by: Partohaghighi, Mohammad, et al.
Published: (2026)

Empirical Calibration and Metric Differential Privacy in Language Models
by: Faustini, Pedro, et al.
Published: (2025)

Convergent Differential Privacy Analysis for General Federated Learning
by: Sun, Yan, et al.
Published: (2024)

Auditing Differential Privacy Guarantees Using Density Estimation
by: Koskela, Antti, et al.
Published: (2024)

Poincaré Differential Privacy for Hierarchy-Aware Graph Embedding
by: Wei, Yuecen, et al.
Published: (2023)

A New Analysis of Differential Privacy's Generalization Guarantees
by: Jung, Christopher, et al.
Published: (2019)

Multi-Class Support Vector Machine with Differential Privacy
by: Park, Jinseong, et al.
Published: (2025)

Purifying Approximate Differential Privacy with Randomized Post-processing
by: Lin, Yingyu, et al.
Published: (2025)

Augment then Smooth: Reconciling Differential Privacy with Certified Robustness
by: Wu, Jiapeng, et al.
Published: (2023)

Efficient Federated Unlearning with Adaptive Differential Privacy Preservation
by: Jiang, Yu, et al.
Published: (2024)

Differentially Private High-dimensional Variable Selection via Integer Programming
by: Prastakos, Petros, et al.
Published: (2025)

DDP-SA: Scalable Privacy-Preserving Federated Learning via Distributed Differential Privacy and Secure Aggregation
by: Wei, Wenjing, et al.
Published: (2026)

Improved Communication-Privacy Trade-offs in $L_2$ Mean Estimation under Streaming Differential Privacy
by: Chen, Wei-Ning, et al.
Published: (2024)

Rao Differential Privacy
by: Soto, Carlos
Published: (2025)

RAG with Differential Privacy
by: Grislain, Nicolas
Published: (2024)

Differentially Private Linear Bandits with Partial Distributed Feedback
by: Li, Fengjiao, et al.
Published: (2022)

Towards Explainable Federated Learning: Understanding the Impact of Differential Privacy
by: Oliveira, Júlio, et al.
Published: (2026)

How Well Can Differential Privacy Be Audited in One Run?
by: Keinan, Amit, et al.
Published: (2025)

Beyond Membership: Limitations of Add/Remove Adjacency in Differential Privacy
by: Pradhan, Gauri, et al.
Published: (2025)

Cape: Context-Aware Prompt Perturbation Mechanism with Differential Privacy
by: Wu, Haoqi, et al.
Published: (2025)

Differentially Private Relational Learning with Entity-level Privacy Guarantees
by: Huang, Yinan, et al.
Published: (2025)

Complex-valued Federated Learning with Differential Privacy and MRI Applications
by: Riess, Anneliese, et al.
Published: (2021)

Poisoning Attacks to Local Differential Privacy Protocols for Trajectory Data
by: Hsu, I-Jung, et al.
Published: (2025)

Calibrating Practical Privacy Risks for Differentially Private Machine Learning
by: Gu, Yuechun, et al.
Published: (2024)