4 papers
Learnability with Partial Labels and Adaptive Nearest Neighbors
Nicolas A. Errandonea, Santiago Mazuelas, Jose A. Lozano +1
Prior work on partial labels learning (PLL) has shown that learning is possible even when each instance is associated with a bag of labels, rather than a single accurate but costly…
Reliable Programmatic Weak Supervision with Confidence Intervals for Label Probabilities
Verónica Ãlvarez, 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…
Learning Smooth Distance Functions via Queries
Akash Kumar, Sanjoy Dasgupta
In this work, we investigate the problem of learning distance functions within the query-based learning framework, where a learner is able to pose triplet queries of the form: ``Is…
Online Consistency of the Nearest Neighbor Rule
Sanjoy Dasgupta, Geelon So
In the realizable online setting, a learner is tasked with making predictions for a stream of instances, where the correct answer is revealed after each prediction. A learning rule…