2 papers
stat.ML2025
Reliable Programmatic Weak Supervision with Confidence Intervals for Label Probabilities
Verónica Álvarez, Santiago Mazuelas, Steven An +1
The accurate labeling of datasets is often both costly and time-consuming. Given an unlabeled dataset, programmatic weak supervision obtains probabilistic predictions for the label…
cs.LG2024
Convergence Behavior of an Adversarial Weak Supervision Method
Steven An, Sanjoy Dasgupta
Labeling data via rules-of-thumb and minimal label supervision is central to Weak Supervision, a paradigm subsuming subareas of machine learning such as crowdsourced learning and s…