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cs.LG2025
Latent label distribution grid representation for modeling uncertainty
ShuNing Sun, YinSong Xiong, Yu Zhang +1
Although \textbf{L}abel \textbf{D}istribution \textbf{L}earning (LDL) has promising representation capabilities for characterizing the polysemy of an instance, the complexity and h…
cs.LG2025
UAKNN: Label Distribution Learning via Uncertainty-Aware KNN
Pu Wang, Yu Zhang, Zhuoran Zheng
Label Distribution Learning (LDL) aims to characterize the polysemy of an instance by building a set of descriptive degrees corresponding to the instance. In recent years, research…