8 citations · 8 across the 2 of their papers we have counts for
2 papers
stat.ML2021
Targeted Active Learning for Bayesian Decision-Making
Louis Filstroff, Iiris Sundin, Petrus Mikkola +3
Active learning is usually applied to acquire labels of informative data points in supervised learning, to maximize accuracy in a sample-efficient way. However, maximizing the accu…
stat.ML2019★ 8 cited
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…