:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Qiao, Yiran, Yin, Yu, Chen, Chen, Ma, Jing
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Cryptography and Security Methodology
Online Access:	https://arxiv.org/abs/2408.15451
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

CausalArmor: Efficient Indirect Prompt Injection Guardrails via Causal Attribution
by: Kim, Minbeom, et al.
Published: (2026)

Differentially Private Covariate Balancing Causal Inference
by: Ohnishi, Yuki, et al.
Published: (2024)

Auditing Differential Privacy in the Black-Box Setting
by: Shi, Kaining, et al.
Published: (2025)

Majority Vote for Distributed Differentially Private Sign Selection
by: Liu, Weidong, et al.
Published: (2022)

Watermarking Counterfactual Explanations
by: Guo, Hangzhi, et al.
Published: (2024)

Causal Discovery Under Local Privacy
by: Binkytė, Rūta, et al.
Published: (2023)

PrAda-GAN: A Private Adaptive Generative Adversarial Network with Bayes Network Structure
by: Jia, Ke, et al.
Published: (2025)

Towards Causal Deep Learning for Vulnerability Detection
by: Rahman, Md Mahbubur, et al.
Published: (2023)

Disentangle Estimation of Causal Effects from Cross-Silo Data
by: Liu, Yuxuan, et al.
Published: (2024)

CURATE: Scaling-up Differentially Private Causal Graph Discovery
by: Bhattacharjee, Payel, et al.
Published: (2024)

Certified Defense on the Fairness of Graph Neural Networks
by: Dong, Yushun, et al.
Published: (2023)

Differentially Private Range Queries with Correlated Input Perturbation
by: Dharangutte, Prathamesh, et al.
Published: (2024)

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

Estimation of conditional average treatment effects on distributed confidential data
by: Kawamata, Yuji, et al.
Published: (2024)

Privacy Preserving Adaptive Experiment Design
by: Li, Jiachun, et al.
Published: (2024)

Resampling methods for private statistical inference
by: Chadha, Karan, et al.
Published: (2024)

Improving the Variance of Differentially Private Randomized Experiments through Clustering
by: Javanmard, Adel, et al.
Published: (2023)

Differentially Private E-Values
by: Csillag, Daniel, et al.
Published: (2025)

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

PrivATE: Differentially Private Confidence Intervals for Average Treatment Effects
by: Schröder, Maresa, et al.
Published: (2025)

Towards Strong Certified Defense with Universal Asymmetric Randomization
by: Hong, Hanbin, et al.
Published: (2025)

PECAN: A Deterministic Certified Defense Against Backdoor Attacks
by: Zhang, Yuhao, et al.
Published: (2023)

Collective Certified Robustness against Graph Injection Attacks
by: Lai, Yuni, et al.
Published: (2024)

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

Inference With Combining Rules From Multiple Differentially Private Synthetic Datasets
by: Nombo, Leila, et al.
Published: (2024)

Privacy-Preserving Customer Support: A Framework for Secure and Scalable Interactions
by: Awasthi, Anant Prakash, et al.
Published: (2024)

Methods for generating and evaluating synthetic longitudinal patient data: a systematic review
by: Perkonoja, Katariina, et al.
Published: (2023)

Certifiable Black-Box Attacks with Randomized Adversarial Examples: Breaking Defenses with Provable Confidence
by: Hong, Hanbin, et al.
Published: (2023)

Automated Cyber Defense with Generalizable Graph-based Reinforcement Learning Agents
by: King, Isaiah J., et al.
Published: (2025)

Debiasing Watermarks for Large Language Models via Maximal Coupling
by: Xie, Yangxinyu, et al.
Published: (2024)

De-amplifying Bias from Differential Privacy in Language Model Fine-tuning
by: Srivastava, Sanjari, et al.
Published: (2024)

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

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

Distribution-Aware Mean Estimation under User-level Local Differential Privacy
by: Pla, Corentin, et al.
Published: (2024)

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)

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

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

Private Prediction Sets
by: Angelopoulos, Anastasios N., et al.
Published: (2021)

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