Weakly-supervised label distribution feature selection via label-specific features and label correlation
Wenhao Shu,
Jiayu Hu,
Wenbin Qian
Abstract:Label Distribution Learning (LDL) stands out as an innovative method to address the challenges posed by label ambiguity. Current LDL algorithms are predominantly designed for datasets with comprehensive supervised information. However, in real-world scenarios, it’s common to encounter partial missing labels within the label space. This phenomenon disrupts the structure and correlation between labels, posing a challenge to the precise design of learning algorithms. Furthermore, in label distribution learning, i… Show more
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