Showing 2026Show all
2 papers · 1 filter
cs.LG2026
Evaluating and Recalibrating Probabilistic Classifiers from One-Bit Threshold Queries
Roman Plaud, Antoine Saillenfest, Matthieu Labeau +2
Standard calibration evaluation and recalibration methods assume access to predicted probabilities. We study one-bit threshold access, a setting in which probabilities are hidden a…
cs.LG2026
Tailoring Strictly Proper Scoring Rules for Downstream Tasks: An Application to Causal Inference
Roman Plaud, Alexandre Perez-Lebel, Antoine Saillenfest +4
Probabilistic models are typically trained using task-agnostic objectives like log-loss, which can lead to significant errors in downstream estimation. This disconnect is especiall…