69 citations · 1.1k across the 120 of their papers we have counts for
3 papers · 2 filters
Privacy-preserving data sharing via probabilistic modelling
Joonas Jälkö, Eemil Lagerspetz, Jari Haukka +3
Differential privacy allows quantifying privacy loss resulting from accessing sensitive personal data. Repeated accesses to underlying data incur increasing loss. Releasing data as…
Learning spectrograms with convolutional spectral kernels
Zheyang Shen, Markus Heinonen, Samuel Kaski
We introduce the convolutional spectral kernel (CSK), a novel family of non-stationary, nonparametric covariance kernels for Gaussian process (GP) models, derived from the convolut…
Active Learning for Decision-Making from Imbalanced Observational Data
Iiris Sundin, Peter Schulam, Eero Siivola +3
Machine learning can help personalized decision support by learning models to predict individual treatment effects (ITE). This work studies the reliability of prediction-based deci…