Abstract: Unsupervised feature selection plays a crucial role in dealing with unlabeled high-dimensional data. However, traditional unsupervised feature selection methods have some limitations. They ...
Abstract: Active learning (AL) and semi-supervised learning (SSL) both aim to reduce annotation costs: AL selectively annotates high-value samples from the unlabeled data, while SSL leverages abundant ...
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