conftrace_

user-level privacy

17 papers

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Co-occurring keywords

differential privacy (1016) stochastic convex optimization (69) mean estimation (70) federated learning (1333) discrete distribution (49) gradient descent (1144) privacy-preserving learning (117) stochastic gradient descent (1091) federated bandit (3) finite sample (8)

Papers

User-level Differentially Private Stochastic Convex Optimization: Efficient Algorithms with Optimal Rates AISTATS 2024
A Huber Loss Minimization Approach to Mean Estimation under User-level Differential Privacy NIPS 2024
Faster Algorithms for User-Level Private Stochastic Convex Optimization NIPS 2024
Federated Linear Contextual Bandits with User-level Differential Privacy ICML 2023
Algorithms for bounding contribution for histogram estimation under user-level privacy ICML 2023
On User-Level Private Convex Optimization ICML 2023
User-level Private Stochastic Convex Optimization with Optimal Rates ICML 2023
Discrete Distribution Estimation under User-level Local Differential Privacy AISTATS 2023
Tight and Robust Private Mean Estimation with Few Users ICML 2022
Improved Differential Privacy for SGD via Optimal Private Linear Operators on Adaptive Streams NIPS 2022
Mean Estimation with User-level Privacy under Data Heterogeneity NIPS 2022
Differentially Private Federated Learning With Local Regularization and Sparsification CVPR 2022
Private Alternating Least Squares: Practical Private Matrix Completion with Tighter Rates ICML 2021
User-Level Differentially Private Learning via Correlated Sampling NIPS 2021
Learning with User-Level Privacy NIPS 2021
Differentially Private Model Personalization NIPS 2021
Learning discrete distributions: user vs item-level privacy NIPS 2020