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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

Facility Location Problem in Differential Privacy Model Revisited NIPS 2019
Differentially Private Empirical Risk Minimization with Non-convex Loss Functions ICML 2019
Differentially Private Empirical Risk Minimization with Smooth Non-Convex Loss Functions: A Non-Stationary View AAAI 2019
Differentially Private Community Detection in Attributed Social Networks ACML 2019
Privacy-Preserving Q-Learning with Functional Noise in Continuous Spaces NIPS 2019
Privately Learning High-Dimensional Distributions COLT 2019
Privacy-Preserving Stacking with Application to Cross-organizational Diabetes Prediction IJCAI 2019
Private Model Compression via Knowledge Distillation AAAI 2019
Private Testing of Distributions via Sample Permutations NIPS 2019
Elliptical Perturbations for Differential Privacy NIPS 2019
Private Hypothesis Selection NIPS 2019
Differentially Private Iterative Gradient Hard Thresholding for Sparse Learning IJCAI 2019
Locally Private Gaussian Estimation NIPS 2019
A Necessary and Sufficient Stability Notion for Adaptive Generalization NIPS 2019
Noninteractive Locally Private Learning of Linear Models via Polynomial Approximations ALT 2019
Unified Sample-Optimal Property Estimation in Near-Linear Time NIPS 2019
On Privacy Protection of Latent Dirichlet Allocation Model Training IJCAI 2019
Efficiently Estimating Erdos-Renyi Graphs with Node Differential Privacy NIPS 2019
Oblivious Sampling Algorithms for Private Data Analysis NIPS 2019
Private Learning Implies Online Learning: An Efficient Reduction NIPS 2019
Differentially Private Algorithms for Learning Mixtures of Separated Gaussians NIPS 2019
Differentially Private Bagging: Improved utility and cheaper privacy than subsample-and-aggregate NIPS 2019
Improving the Gaussian Mechanism for Differential Privacy: Analytical Calibration and Optimal Denoising ICML 2018
Model-Agnostic Private Learning NIPS 2018
Differentially Private Database Release via Kernel Mean Embeddings ICML 2018