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Differential Privacy

414 papers

Papers per year

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20
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Papers

Differentially Private Submodular Maximization: Data Summarization in Disguise ICML 2017
Differentially Private Ordinary Least Squares ICML 2017
Collect at Once, Use Effectively: Making Non-interactive Locally Private Learning Possible ICML 2017
Efficient Private ERM for Smooth Objectives IJCAI 2017
Differential Privacy for Bayesian Inference through Posterior Sampling JMLR 2017
Privacy Odometers and Filters: Pay-as-you-Go Composition NIPS 2016
Private Causal Inference AISTATS 2016
Efficient Private Empirical Risk Minimization for High-dimensional Learning ICML 2016
Differentially Private Data Releasing for Smooth Queries JMLR 2016
Differentially private subspace clustering NIPS 2015
Nearly Optimal Private LASSO NIPS 2015
Private Graphon Estimation for Sparse Graphs NIPS 2015
Secure Multi-party Differential Privacy NIPS 2015
Truthful Linear Regression COLT 2015
Differentially Private Bayesian Optimization ICML 2015
Rademacher Observations, Private Data, and Boosting ICML 2015
Privacy for Free: Posterior Sampling and Stochastic Gradient Monte Carlo ICML 2015
The Noisy Power Method: A Meta Algorithm with Applications NIPS 2014
The Large Margin Mechanism for Differentially Private Maximization NIPS 2014
Extremal Mechanisms for Local Differential Privacy NIPS 2014
Learning Coverage Functions and Private Release of Marginals COLT 2014
Sample Complexity Bounds on Differentially Private Learning via Communication Complexity COLT 2014
Efficient Algorithm for Privately Releasing Smooth Queries NIPS 2013
Statistical Active Learning Algorithms NIPS 2013
(Nearly) Optimal Algorithms for Private Online Learning in Full-information and Bandit Settings NIPS 2013