Differential Privacy
545 papers
Papers per year
1
2
1
6
8
5
9
4
9
18
29
25
49
99
87
103
61
29
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'15
'20
'25
Papers
Abstract Gradient Training: A Unified Certification Framework for Data Poisoning, Unlearning, and Differential Privacy
JMLR 2026
Agent-based Substructure Counting under Local Differential Privacy
ACL 2026
Classification Under Local Differential Privacy with Model Reversal and Model Averaging
JMLR 2026
Cocoon: A System Architecture for Differentially Private Training with Correlated Noises
OSDI 2026
Differentially Private 2D Human Pose Estimation
CVPR 2026
Differentially Private Approval-Based Committee Voting
UAI 2026
Differentially Private Best-Arm Identification
JMLR 2026
Differentially Private Bilevel Optimization
ALT 2026
Differentially Private Estimation and Inference in High-Dimensional Regression with FDR Control
JMLR 2026
Differentially Private Language Generation and Identification in the Limit (Extended Abstract)
COLT 2026
FedAlign: Differentially Private Distribution Alignment for Non-IID Federated Learning
CVPR 2026
Fixed-Parameter Tractability of Private Synthetic Data Generation
COLT 2026
Fully Decentralized Certified Unlearning
CVPR 2026
Improved Regret in Stochastic Decision-Theoretic Online Learning under Differential Privacy
ALT 2026
Improving the Convergence of Private Shuffled Gradient Methods with Public Data
UAI 2026
Invited Open Problem: Does Differential Privacy Make PAC Learning Much Harder?
COLT 2026
LDP-Slicing: Local Differential Privacy for Images via Randomized Bit-Plane Slicing
CVPR 2026
Minimax density estimation in the adversarial framework under local differential privacy
JMLR 2026
Minimax optimal differentially private synthetic data for smooth queries
COLT 2026
Nearly Linear-Time User-Level DP-SCO with Optimal Rates
COLT 2026
On Purely Private Covariance Estimation
ALT 2026
On the Curse of Dimensionality in Private Sparse Covariance Estimation and PCA
COLT 2026
Personalized Federated Training of Diffusion Models with Privacy Guarantees
CVPR 2026
Private Linear Regression via a Down-Sensitivity to Privacy Reduction
COLT 2026
Privately Estimating Black-Box Statistics
COLT 2026