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Privacy
2794 directly classified papers
Papers per year
2006: 1
2007: 2
2008: 1
2011: 2
2012: 7
2013: 10
2014: 7
2015: 18
2016: 23
2017: 40
2018: 65
2019: 133
2020: 167
2021: 289
2022: 342
2023: 484
2024: 502
2025: 522
2026: 179
Papers
Better Private Linear Regression Through Better Private Feature Selection
NIPS 2023
Private Everlasting Prediction
NIPS 2023
Generalized Linear Models in Non-interactive Local Differential Privacy with Public Data
JMLR 2023
Generalization in the Face of Adaptivity: A Bayesian Perspective
NIPS 2023
Unified Enhancement of Privacy Bounds for Mixture Mechanisms via $f$-Differential Privacy
NIPS 2023
Revisiting Data-Free Knowledge Distillation with Poisoned Teachers
ICML 2023
Privacy-Aware Rejection Sampling
JMLR 2023
DP-HyPO: An Adaptive Private Framework for Hyperparameter Optimization
NIPS 2023
Black-box Backdoor Defense via Zero-shot Image Purification
NIPS 2023
A Randomized Approach to Tight Privacy Accounting
NIPS 2023
On Private and Robust Bandits
NIPS 2023
PPGenCDR: A Stable and Robust Framework for Privacy-Preserving Cross-Domain Recommendation
AAAI 2023
PRIOR: Personalized Prior for Reactivating the Information Overlooked in Federated Learning.
NIPS 2023
Gradient Descent with Linearly Correlated Noise: Theory and Applications to Differential Privacy
NIPS 2023
Exact Optimality of Communication-Privacy-Utility Tradeoffs in Distributed Mean Estimation
NIPS 2023
Minimax Risks and Optimal Procedures for Estimation under Functional Local Differential Privacy
NIPS 2023
Black-Box Differential Privacy for Interactive ML
NIPS 2023
The Test of Tests: A Framework for Differentially Private Hypothesis Testing
ICML 2023
An Optimal and Scalable Matrix Mechanism for Noisy Marginals under Convex Loss Functions
NIPS 2023
Functional Renyi Differential Privacy for Generative Modeling
NIPS 2023
Privacy-Preserving Representation Learning for Text-Attributed Networks with Simplicial Complexes
AAAI 2023
User-Level Differential Privacy With Few Examples Per User
NIPS 2023
Label Robust and Differentially Private Linear Regression: Computational and Statistical Efficiency
NIPS 2023
Participatory Personalization in Classification
NIPS 2023
PP4AV: A Benchmarking Dataset for Privacy-Preserving Autonomous Driving
WACV 2023
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