52 citations · 168 across the 28 of their papers we have counts for
5 papers · 1 filter
Exploiting Multi-Label Correlation in Label Distribution Learning
Zhiqiang Kou jing wang yuheng jia xin geng
Label Distribution Learning (LDL) is a novel machine learning paradigm that assigns label distribution to each instance. Many LDL methods proposed to leverage label correlation in…
Complementary Classifier Induced Partial Label Learning
Yuheng Jia, Chongjie Si, Min-ling Zhang
In partial label learning (PLL), each training sample is associated with a set of candidate labels, among which only one is valid. The core of PLL is to disambiguate the candidate…
Data Augmentation For Label Enhancement
Zhiqiang Kou, Yuheng Jia, Jing Wang +2
Label distribution (LD) uses the description degree to describe instances, which provides more fine-grained supervision information when learning with label ambiguity. Nevertheless…
Label Distribution Learning from Logical Label
Yuheng Jia, Jiawei Tang, Jiahao Jiang
Label distribution learning (LDL) is an effective method to predict the label description degree (a.k.a. label distribution) of a sample. However, annotating label distribution (LD…
Inaccurate Label Distribution Learning
Zhiqiang Kou, Yuheng Jia, Jing Wang +1
Label distribution learning (LDL) trains a model to predict the relevance of a set of labels (called label distribution (LD)) to an instance. The previous LDL methods all assumed t…