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Learning embedded label-specific features for partial multi-label learning
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DOI：10.1016/j.patcog.2025.112005.png)
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Abstract
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• Leveraging embedded label-specific features for partial multi-label learning. • Feature learning and disambiguation interact iteratively to improve classification. • Achieve state-of-the-art results on diverse benchmark datasets.
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IEEE ACCESSIF3.6
OAAIShareSaveShareSaveShareSaveShareSaveIntegrating label confidence-based feature selection for partial multi-label learningPATTERN RECOGNITION
PATTERN RECOGNITIONIF7.6
PREAI
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