Classify and Generate Reciprocally: Simultaneous Positive-Unlabelled Learning and Conditional Generation with Extra Data

The scarcity of class-labeled data is a ubiquitous bottleneck in many machine learning problems. While abundant unlabeled data typically exist and provide a potential solution, it is highly challenging to exploit them. In this paper, we address this problem by leveraging Positive-Unlabeled~(PU) clas...

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Veröffentlicht in:	arXiv.org 2024-02
Hauptverfasser:	Yu, Bing, Sun, Ke, Wang, He, Lin, Zhouchen, Zhu, Zhanxing
Format:	Artikel
Sprache:	eng
Schlagworte:	Classification Classifiers Labels Machine learning
Online-Zugang:	Volltext
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