Research map / Federated learning and privacy / Differential privacy
Bridging Central and Local Differential Privacy in Data Acquisition Mechanisms
Read the paperCheck your idea against 108,967 papers
AI-extracted summary. Written by AI from the paper's title only (no summary yet). Numbers and claims can be wrong or missing context, so check the paper before you cite or build on it.
Closest papers by meaning
- Minimax Optimal Estimation of Approximate Differential Privacy on Neighboring Databases (NeurIPS 2019 · similarity 0.90)
- A Huber Loss Minimization Approach to Mean Estimation under User-level Differential Privacy (NeurIPS 2024 · similarity 0.89)
- Optimal Survey Design for Private Mean Estimation (ICML 2025 · similarity 0.89)
- Privacy Guarantees in Posterior Sampling under Contamination (NeurIPS 2026 · similarity 0.89)
- Prior-itizing Privacy: A Bayesian Approach to Setting the Privacy Budget in Differential Privacy (NeurIPS 2024 · similarity 0.88)
- Universal Exact Compression of Differentially Private Mechanisms (NeurIPS 2024 · similarity 0.87)
Writing a paper in this area? scime draft is a free LaTeX editor with AI included, real-time co-authors and a check of your references and venue rules before you submit. It also imports OpenAI Prism projects.
