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Privacy

363 directly classified papers

Papers per year

Papers

ENSEI: Efficient Secure Inference via Frequency-Domain Homomorphic Convolution for Privacy-Preserving Visual Recognition CVPR 2020
On Log-Loss Scores and (No) Privacy EMNLP 2020
Gradient Perturbation is Underrated for Differentially Private Convex Optimization IJCAI 2020
Inferring Nighttime Satellite Imagery from Human Mobility AAAI 2020
Empirical Risk Minimization in the Non-interactive Local Model of Differential Privacy JMLR 2020
On Differentially Private Graph Sparsification and Applications NIPS 2019
A Necessary and Sufficient Stability Notion for Adaptive Generalization NIPS 2019
Privacy Amplification by Mixing and Diffusion Mechanisms NIPS 2019
Private Center Points and Learning of Halfspaces COLT 2019
Practical Differentially Private Top-k Selection with Pay-what-you-get Composition NIPS 2019
Locally Private Gaussian Estimation NIPS 2019
Private Hypothesis Selection NIPS 2019
Private Testing of Distributions via Sample Permutations NIPS 2019
Minimax Optimal Estimation of Approximate Differential Privacy on Neighboring Databases NIPS 2019
Oblivious Sampling Algorithms for Private Data Analysis NIPS 2019
Communication Complexity in Locally Private Distribution Estimation and Heavy Hitters ICML 2019
Traffic Updates: Saying a Lot While Revealing a Little AAAI 2019
Mitigating Information Leakage in Image Representations: A Maximum Entropy Approach CVPR 2019
Private Learning Implies Online Learning: An Efficient Reduction NIPS 2019
Privacy-Preserving Q-Learning with Functional Noise in Continuous Spaces NIPS 2019
Locally Private Learning without Interaction Requires Separation NIPS 2019
KNG: The K-Norm Gradient Mechanism NIPS 2019
Private Stochastic Convex Optimization with Optimal Rates NIPS 2019
An Algorithmic Framework For Differentially Private Data Analysis on Trusted Processors NIPS 2019
Differentially Private Anonymized Histograms NIPS 2019