3 papers
cs.CV2025
Learning from Majority Label: A Novel Problem in Multi-class Multiple-Instance Learning
Shiku Kaito, Shinnosuke Matsuo, Daiki Suehiro +1
The paper proposes a novel multi-class Multiple-Instance Learning (MIL) problem called Learning from Majority Label (LML). In LML, the majority class of instances in a bag is assig…
stat.ML2025
Bounding the Worst-class Error: A Boosting Approach
Yuya Saito, Shinnosuke Matsuo, Seiichi Uchida +1
This paper tackles the problem of the worst-class error rate, instead of the standard error rate averaged over all classes. For example, a three-class classification task with clas…
cs.CV2024
Ordinal Multiple-instance Learning for Ulcerative Colitis Severity Estimation with Selective Aggregated Transformer
Kaito Shiku, Kazuya Nishimura, Daiki Suehiro +2
Patient-level diagnosis of severity in ulcerative colitis (UC) is common in real clinical settings, where the most severe score in a patient is recorded. However, previous UC class…