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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

A Randomized Approach to Tight Privacy Accounting NIPS 2023
On Private and Robust Bandits NIPS 2023
Private Image Generation With Dual-Purpose Auxiliary Classifier CVPR 2023
Private Distribution Learning with Public Data: The View from Sample Compression NIPS 2023
A Unified Fast Gradient Clipping Framework for DP-SGD NIPS 2023
Sparsity-Preserving Differentially Private Training of Large Embedding Models NIPS 2023
Enhancing Privacy Preservation in Federated Learning via Learning Rate Perturbation ICCV 2023
Automatic Clipping: Differentially Private Deep Learning Made Easier and Stronger NIPS 2023
Near-Optimal Differentially Private Reinforcement Learning AISTATS 2023
A Smooth Binary Mechanism for Efficient Private Continual Observation NIPS 2023
Disentangling the Linguistic Competence of Privacy-Preserving BERT EMNLP 2023
Improving the Privacy and Practicality of Objective Perturbation for Differentially Private Linear Learners NIPS 2023
Driving Context into Text-to-Text Privatization ACL 2023
Differentially Private Synthetic Control AISTATS 2023
Differentially Private Approximate Near Neighbor Counting in High Dimensions NIPS 2023
DP-Mix: Mixup-based Data Augmentation for Differentially Private Learning NIPS 2023
Incentives in Private Collaborative Machine Learning NIPS 2023
Private Federated Frequency Estimation: Adapting to the Hardness of the Instance NIPS 2023
Why Is Public Pretraining Necessary for Private Model Training? ICML 2023
Optimal and Private Learning from Human Response Data AISTATS 2023
Differentially Private Stochastic Convex Optimization under a Quantile Loss Function ICML 2023
Jointly Reparametrized Multi-Layer Adaptation for Efficient and Private Tuning ACL 2023
An Optimal and Scalable Matrix Mechanism for Noisy Marginals under Convex Loss Functions NIPS 2023
Gradient Descent with Linearly Correlated Noise: Theory and Applications to Differential Privacy NIPS 2023
XRand: Differentially Private Defense against Explanation-Guided Attacks AAAI 2023