2 citations · 3 across the 8 of their papers we have counts for
4 papers · 1 filter
Efficient Provably Private Classification with a Tabular Foundation Model
Talal Alrawajfeh, Cristiana Diaconu, Ossi Räisä +5
Tabular data underpin prediction and decision-making in medicine, finance, government and science, but often contain sensitive individual-level information, creating a need for acc…
On Reliability of Membership Inference Vulnerability Evaluation
Joonas Jälkö, Gauri Pradhan, Ossi Räisä +1
Membership inference attacks (MIAs) are popular methods for empirically assessing the leakage of sensitive information in the training data through models or statistics learned fro…
Noise-Aware Differentially Private Regression via Meta-Learning
Ossi Räisä, Stratis Markou, Matthew Ashman +4
Many high-stakes applications require machine learning models that protect user privacy and provide well-calibrated, accurate predictions. While Differential Privacy (DP) is the go…
A Bias-Variance Decomposition for Ensembles over Multiple Synthetic Datasets
Ossi Räisä, Antti Honkela
Recent studies have highlighted the benefits of generating multiple synthetic datasets for supervised learning, from increased accuracy to more effective model selection and uncert…