:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Liu, Jingcheng, Upadhyay, Jalaj, Zou, Zongrui
Format:	Preprint
Published:	2024
Subjects:	Cryptography and Security Machine Learning
Online Access:	https://arxiv.org/abs/2406.02140
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Almost linear time differentially private release of synthetic graphs
by: Liu, Jingcheng, et al.
Published: (2024)

Back to Square Roots: An Optimal Bound on the Matrix Factorization Error for Multi-Epoch Differentially Private SGD
by: Kalinin, Nikita P., et al.
Published: (2025)

Differentially Private Decentralized Learning with Random Walks
by: Cyffers, Edwige, et al.
Published: (2024)

Normalized Square Root: Sharper Matrix Factorization Bounds for Differentially Private Continual Counting
by: Henzinger, Monika, et al.
Published: (2025)

Almost Tight Error Bounds on Differentially Private Continual Counting
by: Henzinger, Monika, et al.
Published: (2022)

On the Price of Differential Privacy for Hierarchical Clustering
by: Deng, Chengyuan, et al.
Published: (2025)

Correlated Noise Mechanisms for Differentially Private Learning
by: Pillutla, Krishna, et al.
Published: (2025)

Near-Optimal Generalized Private Testing
by: Chaturvedi, Anamay, et al.
Published: (2026)

Deterministic Hardness of Approximation of Unique-SVP and GapSVP in $\ell_p$ norms for $p>2$
by: Hecht, Yahli, et al.
Published: (2025)

Privacy Amplification for Matrix Mechanisms
by: Choquette-Choo, Christopher A., et al.
Published: (2023)

Sampling-Free Privacy Accounting for Matrix Mechanisms under Random Allocation
by: Schuchardt, Jan, et al.
Published: (2026)

Generalization Properties of Adversarial Training for $\ell_0$-Bounded Adversarial Attacks
by: Delgosha, Payam, et al.
Published: (2024)

DMM: Distributed Matrix Mechanism for Differentially-Private Federated Learning Based on Constant-Overhead Linear Secret Resharing
by: Bienstock, Alexander, et al.
Published: (2024)

The Price of Privacy For Approximating Max-CSP
by: Dharangutte, Prathamesh, et al.
Published: (2026)

RAMP: Boosting Adversarial Robustness Against Multiple $l_p$ Perturbations for Universal Robustness
by: Jiang, Enyi, et al.
Published: (2024)

Contrastive Learning-Based privacy metrics in Tabular Synthetic Datasets
by: Palacios, Milton Nicolás Plasencia, et al.
Published: (2025)

Banded Square Root Matrix Factorization for Differentially Private Model Training
by: Kalinin, Nikita P., et al.
Published: (2024)

Secure Sparse Matrix Multiplications and their Applications to Privacy-Preserving Machine Learning
by: Damie, Marc, et al.
Published: (2025)

Improved Privacy-Preserving PCA Using Optimized Homomorphic Matrix Multiplication
by: Ma, Xirong
Published: (2023)

Scaling up the Banded Matrix Factorization Mechanism for Differentially Private ML
by: McKenna, Ryan
Published: (2024)

Fusing Pruned and Backdoored Models: Optimal Transport-based Data-free Backdoor Mitigation
by: Lin, Weilin, et al.
Published: (2024)

Authority Backdoor: A Certifiable Backdoor Mechanism for Authoring DNNs
by: Yang, Han, et al.
Published: (2025)

Constructing Adversarial Examples for Vertical Federated Learning: Optimal Client Corruption through Multi-Armed Bandit
by: Yao, Duanyi, et al.
Published: (2024)

Practical Bayes-Optimal Membership Inference Attacks
by: Lassila, Marcus, et al.
Published: (2025)

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

PIShield: Detecting Prompt Injection Attacks via Intrinsic LLM Features
by: Zou, Wei, et al.
Published: (2025)

Attack Smarter: Attention-Driven Fine-Grained Webpage Fingerprinting Attacks
by: Yuan, Yali, et al.
Published: (2025)

Privacy-Preserving Optimal Parameter Selection for Collaborative Clustering
by: Ghasemian, Maryam, et al.
Published: (2024)

Exactly Minimax-Optimal Locally Differentially Private Sampling
by: Park, Hyun-Young, et al.
Published: (2024)

Rate-Optimal Rank Aggregation with Private Pairwise Rankings
by: Xu, Shirong, et al.
Published: (2024)

On the Optimal Regret of Locally Private Linear Contextual Bandit
by: Li, Jiachun, et al.
Published: (2024)

Optimal Locally Private Nonparametric Classification with Public Data
by: Ma, Yuheng, et al.
Published: (2023)

Property-Preserving Hashing for $\ell_1$-Distance Predicates: Applications to Countering Adversarial Input Attacks
by: Asghar, Hassan, et al.
Published: (2025)

On the Privacy of Selection Mechanisms with Gaussian Noise
by: Lebensold, Jonathan, et al.
Published: (2024)

Differentially Private Algorithms for Graph Cuts: A Shifting Mechanism Approach and More
by: Chandra, Rishi, et al.
Published: (2024)

PoisonedRAG: Knowledge Corruption Attacks to Retrieval-Augmented Generation of Large Language Models
by: Zou, Wei, et al.
Published: (2024)

Privacy Amplification for the Gaussian Mechanism via Bounded Support
by: Hu, Shengyuan, et al.
Published: (2024)

Auditing Privacy Mechanisms via Label Inference Attacks
by: Busa-Fekete, Róbert István, et al.
Published: (2024)

Evaluating Generalization Mechanisms in Autonomous Cyber Attack Agents
by: Lukáš, Ondřej, et al.
Published: (2026)

Optimal Client Sampling in Federated Learning with Client-Level Heterogeneous Differential Privacy
by: Xu, Jiahao, et al.
Published: (2025)