| On the Inherent Privacy Properties of Discrete Denoising Diffusion Models | Oct 24, 2023 | Dataset GenerationDenoising | —Unverified | 0 |
| On the Price of Differential Privacy for Spectral Clustering over Stochastic Block Models | May 9, 2025 | ClusteringCommunity Detection | —Unverified | 0 |
| On the Privacy-Preserving Properties of Spiking Neural Networks with Unique Surrogate Gradients and Quantization Levels | Feb 25, 2025 | Privacy PreservingQuantization | —Unverified | 0 |
| On the Privacy-Utility Tradeoff in Peer-Review Data Analysis | Jun 29, 2020 | Privacy Preserving | —Unverified | 0 |
| On the security of randomly transformed quadratic programs for privacy-preserving cloud-based control | Nov 9, 2023 | Model Predictive ControlPrivacy Preserving | —Unverified | 0 |
| On the Theory and Practice of Privacy-Preserving Bayesian Data Analysis | Mar 23, 2016 | Bayesian InferencePrivacy Preserving | —Unverified | 0 |
| On the Usefulness of Synthetic Tabular Data Generation | Jun 27, 2023 | Data AugmentationData Summarization | —Unverified | 0 |
| On the utility and protection of optimization with differential privacy and classic regularization techniques | Sep 7, 2022 | Deep LearningL2 Regularization | —Unverified | 0 |
| Ontology- and LLM-based Data Harmonization for Federated Learning in Healthcare | May 26, 2025 | Federated LearningPrivacy Preserving | —Unverified | 0 |
| Open LLMs are Necessary for Current Private Adaptations and Outperform their Closed Alternatives | Nov 2, 2024 | Privacy Preserving | —Unverified | 0 |