Support by the National High Technology Research and Development Program of China(No.2012AA120802);National Natural Science Foundation of China(No.61771186);Postdoctoral Research Project of Heilongjiang Province(No.LBH-Q15121);Undergraduate University Project of Young Scientist Creative Talent of Heilongjiang Province(No.UNPYSCT-2017125)
Multi-label learning is an active research area which plays an important role in machine learning. Traditional learning algorithms, however, have to depend on samples with complete labels. The existing learning algori...
Supported by Australian Research Council Discovery(DP130102691);the National Science Foundation of China(61302157);China National 863 Project(2012AA12A308);China Pre-research Project of Nuclear Industry(FZ1402-08)
In this paper a novel coupled attribute similarity learning method is proposed with the basis on the multi-label categorical data(CASonMLCD).The CASonMLCD method not only computes the correlations between different ...
Supported by Australian Research Council Discovery(DP130102691);the National Science Foundation of China(61302157);China National 863 Project(2012AA12A308);China Pre-research Project of Nuclear Industry(FZ1402-08)
It is a key challenge to exploit the label coupling relationship in multi-label classification(MLC)problems.Most previous work focused on label pairwise relations,in which generally only global statistical informati...