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 ...
The chain of the first 3 blocks can be organized in a parallel multi-channel structure that is followed by one or several aggregation blocks. The final decision about the class is made based on the ...
Multi-view learning is gradually becoming a well-established domain within machine learning that tackles problems involving the availability of multiple views or sources of data. Existing multi-view ...
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