Review re-maps multi-view learning into four supervised scenarios and three granular sub-tiers, delivering the first unified ...

Active learning for multi-label classification addresses the challenge of labelling data in situations where each instance may belong to several overlapping categories. This paradigm aims to enhance ...

Self-supervised models generate implicit labels from unstructured data rather than relying on labeled datasets for supervisory signals. Self-supervised learning (SSL), a transformative subset of ...

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