Research Explorer
Papers
Trends
Conferences
Explore
Authors
Topics
Keywords
Papers
Trends
Conferences
Explore
Authors
Topics
Keywords
Achievements
About
Methodology
← Keywords
differential privacy
1010 papers
Explore in graph
Also known as
DPDL
DP-SGD
DP
DPSGD
MDP
LDP
Co-occurring keywords
federated learning
(1320)
stochastic gradient descent
(1088)
sample complexity
(1158)
privacy preservation
(376)
privacy-preserving learning
(115)
regret bound
(1918)
privacy-preserving machine learning
(99)
large language model
(12755)
exponential mechanism
(30)
online learning
(1770)
Papers
Thinking Outside of the Differential Privacy Box: A Case Study in Text Privatization with Language Model Prompting
EMNLP 2024
Online Sensitivity Optimization in Differentially Private Learning
AAAI 2024
Scalable DP-SGD: Shuffling vs. Poisson Subsampling
NIPS 2024
Adversarially Robust Dense-Sparse Tradeoffs via Heavy-Hitters
NIPS 2024
PrivSGP-VR: Differentially Private Variance-Reduced Stochastic Gradient Push with Tight Utility Bounds
IJCAI 2024
Generate Synthetic Text Approximating the Private Distribution with Differential Privacy
IJCAI 2024
Protect Your Score: Contact-Tracing with Differential Privacy Guarantees
AAAI 2024
Continual Counting with Gradual Privacy Expiration
NIPS 2024
Differentially Private Set Representations
NIPS 2024
Poincaré Differential Privacy for Hierarchy-Aware Graph Embedding
AAAI 2024
Multi-Dimensional Fair Federated Learning
AAAI 2024
No Prejudice! Fair Federated Graph Neural Networks for Personalized Recommendation
AAAI 2024
Noise-Aware Differentially Private Regression via Meta-Learning
NIPS 2024
Privacy Amplification by Iteration for ADMM with (Strongly) Convex Objective Functions
AAAI 2024
Differential Privacy in Scalable General Kernel Learning via $K$-means Nystr{\"o}m Random Features
NIPS 2024
Federated Graph Learning for Cross-Domain Recommendation
NIPS 2024
Differentially private methods for managing model uncertainty in linear regression
JMLR 2024
Faster Rates of Differentially Private Stochastic Convex Optimization
JMLR 2024
Pure Differential Privacy for Functional Summaries with a Laplace-like Process
JMLR 2024
Optimal Learning Policies for Differential Privacy in Multi-armed Bandits
JMLR 2024
Analysis of Privacy Leakage in Federated Large Language Models
AISTATS 2024
Optimal Private and Communication Constraint Distributed Goodness-of-Fit Testing for Discrete Distributions in the Large Sample Regime
NIPS 2024
Can Public Large Language Models Help Private Cross-device Federated Learning?
NAACL 2024
On the Computational Complexity of Private High-dimensional Model Selection
NIPS 2024
DP-AdamBC: Your DP-Adam Is Actually DP-SGD (Unless You Apply Bias Correction)
AAAI 2024
<
1
…
4
5
6
…
41
>