… space, and treat the label as a meaningless multi-hot vector. In this paper, we put … -label
text classification algorithm LELC(joint learning from Label Embedding and Label Correlation) …

… • We propose a novel multi-label learning method by learning label-specific features based
on correlation information, named LFCMLL. • l1-regularization is applied to sparse the weight …

… share different label correlations, and few label correlations are … In this paper, two novel label
distribution learning algorithms … two label distribution learning algorithms by exploiting label …

… is applied to capture the global label correlations. In addition, the label correlation among
local samples are adopted to modify the label correlation matrix. The experimental results on …

… -order label correlations and make predictions in a joint manner. To show the effectiveness of
joint learning… that the joint learning manner outperforms the step-wise learning significantly. …

… explicit label correlations. In this paper, we deal with this problem by … learning the binary
classifiers and pairwise label correlations (JBP) in an end-to-end manner. For pairwise learning, …

… multi-label learning. In this work, the label correlation is divided into the global label correlation
… In order to prove the effect of global and local label joint correlations, we remove the low …

… can use label correlations to enhance the learning process of label-… the algorithms combine
label correlations and label-specific … In this paper, a new multi-label joint learning algorithm …

… consider the label correlation and the instance correlation … of label correlation used in many
existing multi-label learning … label correlations, that is, if two labels are strongly correlated, …

… also allows the joint learning of multi-label classification and label correlations. Meanwhile,
… In this paper, we try to address the following problems in a joint learning framework, ie, how …