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differential privacy

1010 papers

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Also known as

DPDL DP-SGD DP DPSGD MDP LDP

Co-occurring keywords

federated learning (1320) stochastic gradient descent (1088) sample complexity (1158) privacy preservation (376) privacy-preserving learning (115) regret bound (1918) privacy-preserving machine learning (99) large language model (12755) exponential mechanism (30) online learning (1770)

Papers

Private Graph All-Pairwise-Shortest-Path Distance Release with Improved Error Rate NIPS 2022
Private Estimation with Public Data NIPS 2022
Archimedes Meets Privacy: On Privately Estimating Quantiles in High Dimensions Under Minimal Assumptions NIPS 2022
Differentially Private Linear Sketches: Efficient Implementations and Applications NIPS 2022
The Privacy Onion Effect: Memorization is Relative NIPS 2022
Data Augmentation MCMC for Bayesian Inference from Privatized Data NIPS 2022
SeqPATE: Differentially Private Text Generation via Knowledge Distillation NIPS 2022
Groove: Flexible Metadata-Private Messaging OSDI 2022
Post-processing of Differentially Private Data: A Fairness Perspective IJCAI 2022
The Limits of Word Level Differential Privacy NAACL 2022
Privacy Amplification via Shuffling for Linear Contextual Bandits ALT 2022
Faster Rates of Private Stochastic Convex Optimization ALT 2022
Infinitely Divisible Noise in the Low Privacy Regime ALT 2022
A Private and Computationally-Efficient Estimator for Unbounded Gaussians COLT 2022
A bounded-noise mechanism for differential privacy COLT 2022
Private Robust Estimation by Stabilizing Convex Relaxations COLT 2022
Mitigating statistical bias within differentially private synthetic data UAI 2022
Ensembling Neural Networks for Improved Prediction and Privacy in Early Diagnosis of Sepsis MLHC 2022
Differentially Private Estimation of Heterogeneous Causal Effects CLEAR 2022
Hypothesis Testing for Differentially Private Linear Regression NIPS 2022
Locally Differentially-Private Randomized Response for Discrete Distribution Learning JMLR 2021
Accuracy, Interpretability, and Differential Privacy via Explainable Boosting ICML 2021
Practical One-Shot Federated Learning for Cross-Silo Setting IJCAI 2021
Towards Fair and Transparent Algorithmic Systems IJCAI 2021
Privately Publishable Per-instance Privacy NIPS 2021