1 citations · 1 across the 4 of their papers we have counts for
4 papers
High-Fidelity Synthetic ECG Generation via Mel-Spectrogram Informed Diffusion Training
Zhuoyi Huang, Nutan Sahoo, Anamika Kumari +13
The development of machine learning for cardiac care is severely hampered by privacy restrictions on sharing real patient electrocardiogram (ECG) data. Although generative AI offer…
Differentially Private Synthetic High-dimensional Tabular Stream
Girish Kumar, Thomas Strohmer, Roman Vershynin
While differentially private synthetic data generation has been explored extensively in the literature, how to update this data in the future if the underlying private data changes…
An Algorithm for Streaming Differentially Private Data
Girish Kumar, Thomas Strohmer, Roman Vershynin
Much of the research in differential privacy has focused on offline applications with the assumption that all data is available at once. When these algorithms are applied in practi…
Synthetic Text Generation with Differential Privacy: A Simple and Practical Recipe
Xiang Yue, Huseyin A. Inan, Xuechen Li +6
Privacy concerns have attracted increasing attention in data-driven products due to the tendency of machine learning models to memorize sensitive training data. Generating syntheti…