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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

Improving On-Device Speaker Verification Using Federated Learning with Privacy INTERSPEECH 2020
Inferring Nighttime Satellite Imagery from Human Mobility AAAI 2020
GS-WGAN: A Gradient-Sanitized Approach for Learning Differentially Private Generators NIPS 2020
Privately Answering Classification Queries in the Agnostic PAC Model ALT 2020
Efficient Private Algorithms for Learning Large-Margin Halfspaces ALT 2020
Auditing Differentially Private Machine Learning: How Private is Private SGD? NIPS 2020
Differentially Private Language Models Benefit from Public Pre-training EMNLP 2020
Learning discrete distributions: user vs item-level privacy NIPS 2020
A Computational Separation between Private Learning and Online Learning NIPS 2020
Adversarially Robust Streaming Algorithms via Differential Privacy NIPS 2020
Privacy-Preserving News Recommendation Model Learning EMNLP 2020
The Secret Revealer: Generative Model-Inversion Attacks Against Deep Neural Networks CVPR 2020
Learning from Mixtures of Private and Public Populations NIPS 2020
Optimal Private Median Estimation under Minimal Distributional Assumptions NIPS 2020
Breaking the Communication-Privacy-Accuracy Trilemma NIPS 2020
Stability of Stochastic Gradient Descent on Nonsmooth Convex Losses NIPS 2020
Privacy Amplification via Random Check-Ins NIPS 2020
Federated Principal Component Analysis NIPS 2020
Synthetic Data Generators -- Sequential and Private NIPS 2020
Faster Differentially Private Samplers via Rényi Divergence Analysis of Discretized Langevin MCMC NIPS 2020
Private Identity Testing for High-Dimensional Distributions NIPS 2020
Locally Differentially Private (Contextual) Bandits Learning NIPS 2020
Private Learning of Halfspaces: Simplifying the Construction and Reducing the Sample Complexity NIPS 2020
Smoothly Bounding User Contributions in Differential Privacy NIPS 2020
Instance-optimality in differential privacy via approximate inverse sensitivity mechanisms NIPS 2020