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

On provable privacy vulnerabilities of graph representations NIPS 2024

Lower Bounds for Differential Privacy Under Continual Observation and Online Threshold Queries COLT 2024

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

Universal Exact Compression of Differentially Private Mechanisms NIPS 2024

All Rivers Run to the Sea: Private Learning with Asymmetric Flows CVPR 2024

Langevin Unlearning: A New Perspective of Noisy Gradient Descent for Machine Unlearning NIPS 2024

Certified private data release for sparse Lipschitz functions AISTATS 2024

Differentially Private Equivalence Testing for Continuous Distributions and Applications NIPS 2024

Differentially Private Graph Diffusion with Applications in Personalized PageRanks NIPS 2024

Differentially Private Reward Estimation with Preference Feedback AISTATS 2024

Differentially Private Optimization with Sparse Gradients NIPS 2024

Frequency Oracle for Sensitive Data Monitoring (Student Abstract) AAAI 2024

Implicit Bias in Noisy-SGD: With Applications to Differentially Private Training AISTATS 2024

Revisiting Differentially Private ReLU Regression NIPS 2024

Finding ε and δ of Traditional Disclosure Control Systems AAAI 2024

On Differentially Private Subspace Estimation in a Distribution-Free Setting NIPS 2024

Computing epidemic metrics with edge differential privacy AISTATS 2024

User-level Differentially Private Stochastic Convex Optimization: Efficient Algorithms with Optimal Rates AISTATS 2024

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

Private Learning with Public Features AISTATS 2024

Differentially Private Conditional Independence Testing AISTATS 2024

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

On Mitigating the Utility-Loss in Differentially Private Learning: A New Perspective by a Geometrically Inspired Kernel Approach (Abstract Reprint) IJCAI 2024

Taming Nonconvex Stochastic Mirror Descent with General Bregman Divergence AISTATS 2024

PrIsing: Privacy-Preserving Peer Effect Estimation via Ising Model AISTATS 2024