differential privacy

1010 papers

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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

Optimizing Noise for f-Differential Privacy via Anti-Concentration and Stochastic Dominance JMLR 2024

A Unified Characterization of Private Learnability via Graph Theory COLT 2024

Thompson Sampling Itself is Differentially Private AISTATS 2024

Differentially Private Natural Language Models: Recent Advances and Future Directions EACL 2024

Instance-Optimal Private Density Estimation in the Wasserstein Distance NIPS 2024

Private Edge Density Estimation for Random Graphs: Optimal, Efficient and Robust NIPS 2024

Multitask Online Learning: Listen to the Neighborhood Buzz AISTATS 2024

On the Privacy of Selection Mechanisms with Gaussian Noise AISTATS 2024

Open Problem: Optimal Rates for Stochastic Decision-Theoretic Online Learning Under Differentially Privacy COLT 2024

DP-NMT: Scalable Differentially Private Machine Translation EACL 2024

Federated Experiment Design under Distributed Differential Privacy AISTATS 2024

Privacy-Enhancing Person Re-Identification Framework - A Dual-Stage Approach WACV 2024

A Comparative Analysis of Word-Level Metric Differential Privacy: Benchmarking the Privacy-Utility Trade-off COLING 2024

Pre-training Differentially Private Models with Limited Public Data NIPS 2024

Mirror Descent Algorithms with Nearly Dimension-Independent Rates for Differentially-Private Stochastic Saddle-Point Problems extended abstract COLT 2024

Compression with Exact Error Distribution for Federated Learning AISTATS 2024

Some Constructions of Private, Efficient, and Optimal $K$-Norm and Elliptic Gaussian Noise COLT 2024

Open LLMs are Necessary for Current Private Adaptations and Outperform their Closed Alternatives NIPS 2024

Private Learning with Public Features AISTATS 2024

No Prejudice! Fair Federated Graph Neural Networks for Personalized Recommendation AAAI 2024

On the Growth of Mistakes in Differentially Private Online Learning: A Lower Bound Perspective COLT 2024

On the Benefits of Public Representations for Private Transfer Learning under Distribution Shift NIPS 2024

Computing epidemic metrics with edge differential privacy AISTATS 2024

Poincaré Differential Privacy for Hierarchy-Aware Graph Embedding AAAI 2024

Auditing Privacy Mechanisms via Label Inference Attacks NIPS 2024