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Privacy

363 directly classified papers

Papers per year

Papers

Capacity Bounded Differential Privacy NIPS 2019
Limits of Private Learning with Access to Public Data NIPS 2019
Differentially Private Contextual Linear Bandits NIPS 2018
Empirical Risk Minimization in Non-interactive Local Differential Privacy Revisited NIPS 2018
The Price of Privacy for Low-rank Factorization 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
Local Differential Privacy for Evolving Data NIPS 2018
Model-Agnostic Private Learning NIPS 2018
Differential Privacy for Growing Databases NIPS 2018
Bounded-Loss Private Prediction Markets NIPS 2018
Differentially Private Change-Point Detection NIPS 2018
Improving the Gaussian Mechanism for Differential Privacy: Analytical Calibration and Optimal Denoising ICML 2018
Privacy Issues Regarding the Application of DNNs to Activity-Recognition using Wearables and Its Countermeasures by Use of Adversarial Training IJCAI 2017
A Group-Based Personalized Model for Image Privacy Classification and Labeling IJCAI 2017
Efficient Private ERM for Smooth Objectives IJCAI 2017
Collecting Telemetry Data Privately NIPS 2017
Deanonymization in the Bitcoin P2P Network NIPS 2017
Differentially Private Empirical Risk Minimization Revisited: Faster and More General NIPS 2017
Privacy Odometers and Filters: Pay-as-you-Go Composition NIPS 2016
Efficient Private Empirical Risk Minimization for High-dimensional Learning ICML 2016
A Market Framework for Eliciting Private Data NIPS 2015
Secure Multi-party Differential Privacy NIPS 2015
Private Graphon Estimation for Sparse Graphs NIPS 2015