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cs.LG2024
Towards Better Performance in Incomplete LDL: Addressing Data Imbalance
Zhiqiang Kou, Haoyuan Xuan, Jing Wang +2
Label Distribution Learning (LDL) is a novel machine learning paradigm that addresses the problem of label ambiguity and has found widespread applications. Obtaining complete label…
cs.LG2024★ 1 cited
Inaccurate Label Distribution Learning with Dependency Noise
Zhiqiang Kou, Jing Wang, Yuheng Jia +1
In this paper, we introduce the Dependent Noise-based Inaccurate Label Distribution Learning (DN-ILDL) framework to tackle the challenges posed by noise in label distribution learn…