Contrastive Approach to Prior Free Positive Unlabeled Learning

Positive Unlabeled (PU) learning refers to the task of learning a binary classifier given a few labeled positive samples, and a set of unlabeled samples (which could be positive or negative). In this paper, we propose a novel PU learning framework, that starts by learning a feature space through pre...

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Hauptverfasser:	Acharya, Anish, Sanghavi, Sujay
Format:	Artikel
Sprache:	eng
Schlagworte:	Computer Science - Artificial Intelligence Computer Science - Computer Vision and Pattern Recognition Computer Science - Learning
Online-Zugang:	Volltext bestellen
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