In many real-world machine learning problems, inadequate labeled data and extensive unlabeled data are usually available. Normally, unlabeled data is collected routinely, though the high cost associated with labeling the data is high for generating the labeled training dataset for supervised learning. Moreover, the lack of domain experts and the time-consuming data labeling, especially in […]
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