| Differentially Private Neural Tangent Kernels for Privacy-Preserving Data Generation | Mar 3, 2023 | Privacy Preserving | —Unverified | 0 |
| Differentially Private Non Parametric Copulas: Generating synthetic data with non parametric copulas under privacy guarantees | Sep 27, 2024 | Privacy PreservingSynthetic Data Generation | —Unverified | 0 |
| DeFL: Decentralized Weight Aggregation for Cross-silo Federated Learning | Aug 1, 2022 | Federated LearningPrivacy Preserving | —Unverified | 0 |
| A Unified Framework for Generic, Query-Focused, Privacy Preserving and Update Summarization using Submodular Information Measures | Oct 12, 2020 | Privacy PreservingQuery-focused Summarization | —Unverified | 0 |
| Defense Against Gradient Leakage Attacks via Learning to Obscure Data | Jun 1, 2022 | Federated LearningPrivacy Preserving | —Unverified | 0 |
| Differentially Private Online Learning for Cloud-Based Video Recommendation with Multimedia Big Data in Social Networks | Sep 1, 2015 | Privacy PreservingRecommendation Systems | —Unverified | 0 |
| Defending Label Inference Attacks in Split Learning under Regression Setting | Aug 18, 2023 | Federated LearningPrivacy Preserving | —Unverified | 0 |
| A2-DIDM: Privacy-preserving Accumulator-enabled Auditing for Distributed Identity of DNN Model | May 7, 2024 | Privacy Preserving | —Unverified | 0 |
| Beyond Inferring Class Representatives: User-Level Privacy Leakage From Federated Learning | Dec 3, 2018 | Edge-computingFederated Learning | —Unverified | 0 |
| Defending against Reconstruction Attack in Vertical Federated Learning | Jul 21, 2021 | Federated LearningPrivacy Preserving | —Unverified | 0 |
