Learning from Label Proportion with Online Pseudo-Label Decision by Regret Minimization

This paper proposes a novel and efficient method for Learning from Label Proportions (LLP), whose goal is to train a classifier only by using the class label proportions of instance sets, called bags. We propose a novel LLP method based on an online pseudo-labeling method with regret minimization. A...

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Hauptverfasser:	Matsuo, Shinnosuke, Bise, Ryoma, Uchida, Seiichi, Suehiro, Daiki
Format:	Artikel
Sprache:	eng
Schlagworte:	Computer Science - Computer Vision and Pattern Recognition
Online-Zugang:	Volltext bestellen
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