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Privacy

2,847 papers

Papers per year

18
172
532
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Papers

Differentially Private k-Means with Constant Multiplicative Error NIPS 2018
Contamination Attacks and Mitigation in Multi-Party Machine Learning NIPS 2018
Privacy Amplification by Subsampling: Tight Analyses via Couplings and Divergences NIPS 2018
Distributed Learning without Distress: Privacy-Preserving Empirical Risk Minimization NIPS 2018
Query Complexity of Bayesian Private Learning NIPS 2018
Differentially Private Testing of Identity and Closeness of Discrete Distributions NIPS 2018
Local Differential Privacy for Evolving Data NIPS 2018
Differentially Private Contextual Linear Bandits NIPS 2018
Differentially Private Robust Low-Rank Approximation NIPS 2018
Model-Agnostic Private Learning NIPS 2018
Differential Privacy for Growing Databases NIPS 2018
Using Trusted Data to Train Deep Networks on Labels Corrupted by Severe Noise NIPS 2018
Bounded-Loss Private Prediction Markets NIPS 2018
Differentially Private Change-Point Detection NIPS 2018
Towards Robust and Privacy-preserving Text Representations ACL 2018
SecureNets: Secure Inference of Deep Neural Networks on an Untrusted Cloud ACML 2018
Personalized and Private Peer-to-Peer Machine Learning AISTATS 2018
Differentially Private Regression with Gaussian Processes AISTATS 2018
Cheap Checking for Cloud Computing: Statistical Analysis via Annotated Data Streams AISTATS 2018
Minimax-Optimal Privacy-Preserving Sparse PCA in Distributed Systems AISTATS 2018
Corrupt Bandits for Preserving Local Privacy ALT 2018
Smooth Sensitivity Based Approach for Differentially Private PCA ALT 2018
Clustering Algorithms for the Centralized and Local Models ALT 2018
Calibrating Noise to Variance in Adaptive Data Analysis COLT 2018
Private Sequential Learning COLT 2018