Active learning represents a transformative paradigm in machine learning, aimed at reducing the annotation burden by selectively querying the most informative data points. This approach leverages ...

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 ...

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