80 citations · 243 across the 11 of their papers we have counts for
Showing 2017 · stat.MLShow all
2 papers · 2 filters
stat.ML2017★ 3 cited
Information-Theoretic Representation Learning for Positive-Unlabeled Classification
Tomoya Sakai, Gang Niu, Masashi Sugiyama
Recent advances in weakly supervised classification allow us to train a classifier only from positive and unlabeled (PU) data. However, existing PU classification methods typically…
stat.ML2017★ 54 cited
Semi-Supervised AUC Optimization based on Positive-Unlabeled Learning
Tomoya Sakai, Gang Niu, Masashi Sugiyama
Maximizing the area under the receiver operating characteristic curve (AUC) is a standard approach to imbalanced classification. So far, various supervised AUC optimization methods…